From f1eb927d581c83019c0d0d46a2707cf6a64133ad Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 10 Jun 2024 08:42:37 -0400 Subject: [PATCH 01/71] Initial dump Signed-off-by: Charles Hu --- src/.vuepress/navbar.ts | 3 +- src/.vuepress/sidebar.ts | 9 +- src/README.md | 3 + src/courses/mappers/02.md | 74 +++++++++ src/courses/mappers/03.md | 118 +++++++++++++ src/courses/mappers/04.md | 301 ++++++++++++++++++++++++++++++++++ src/courses/mappers/05.md | 36 ++++ src/courses/mappers/06.md | 88 ++++++++++ src/courses/mappers/07.md | 55 +++++++ src/courses/mappers/08.md | 222 +++++++++++++++++++++++++ src/courses/mappers/09.md | 269 ++++++++++++++++++++++++++++++ src/courses/mappers/10.md | 10 ++ src/courses/mappers/11.md | 158 ++++++++++++++++++ src/courses/mappers/README.md | 14 ++ 14 files changed, 1358 insertions(+), 2 deletions(-) create mode 100644 src/courses/mappers/02.md create mode 100644 src/courses/mappers/03.md create mode 100644 src/courses/mappers/04.md create mode 100644 src/courses/mappers/05.md create mode 100644 src/courses/mappers/06.md create mode 100644 src/courses/mappers/07.md create mode 100644 src/courses/mappers/08.md create mode 100644 src/courses/mappers/09.md create mode 100644 src/courses/mappers/10.md create mode 100644 src/courses/mappers/11.md create mode 100644 src/courses/mappers/README.md diff --git a/src/.vuepress/navbar.ts b/src/.vuepress/navbar.ts index 06d85e9eb..a03b38ac8 100644 --- a/src/.vuepress/navbar.ts +++ b/src/.vuepress/navbar.ts @@ -10,7 +10,8 @@ export default navbar([ { text: "Beginner Security Automation Developer Class", link: "/courses/beginner/", icon: "creative" }, { text: "Advanced Security Automation Developer Class", link: "/courses/advanced/", icon: "creative" }, { text: "Security Guidance Developer Class", link: "/courses/guidance/", icon: "creative" }, - { text: "InSpec Profile Development & Testing", link: "/courses/profile-dev-test", icon: "creative"} + { text: "InSpec Profile Development & Testing", link: "/courses/profile-dev-test", icon: "creative"}, + { text: "OHDF Mapper Development Class", link: "/courses/mapper/", icon: "creative"} ]}, { text: "Resources", icon: "book", diff --git a/src/.vuepress/sidebar.ts b/src/.vuepress/sidebar.ts index 60cb04788..e10b0a459 100644 --- a/src/.vuepress/sidebar.ts +++ b/src/.vuepress/sidebar.ts @@ -32,12 +32,19 @@ export default sidebar({ children: "structure", collapsible: true }, - { + { icon: "creative", text: "InSpec Profile Development & Testing", prefix: "courses/profile-dev-test/", children: "structure", collapsible: true }, + { + icon: "creative", + text: "OHDF Mapper Development Class", + prefix: "courses/mapper/", + children: "structure", + collapsible: true + }, ], }); diff --git a/src/README.md b/src/README.md index a229adcee..53f3d5e6d 100644 --- a/src/README.md +++ b/src/README.md @@ -21,6 +21,9 @@ actions: - text: InSpec Profile Updating & Development type: primary link: /courses/profile-dev-test + - text: OHDF Mapper Development Class + type: primary + link: /courses/mapper/ highlights: - header: What You Will Learn diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md new file mode 100644 index 000000000..96d6798a3 --- /dev/null +++ b/src/courses/mappers/02.md @@ -0,0 +1,74 @@ +--- +order: 2 +next: 03.md +title: Background & Overview 1 +author: Charles Hu +--- + +### HDF Schema + +The full generalized HDF schema is as follows: + +``` +{ + platform: { //required field + name //required field + release //required field + target_id + } + version //required field + statistics: { //required field + duration + } + profiles: [ //required field + 0: { + name //required field + version + sha256 //required field + title + maintainer + summary + license + copyright + copyright_email + supports //required field + attributes //required field + groups //required field + controls: [ //required field + 0: { + id //required field + title + desc + descriptions + impact //required field + refs //required field + tags //required field + code + source_location //required field + results: [ //required field + 0: { + status + code_desc //required field + message + run_time + start_time //required field + } + ] + } + ] + status + } + ] + passthrough: { + auxiliary_data: [ + 0: { + name + data + } + ] + raw + } +} +``` + +(Note: The documented schema is subject to change and not all required fields need to be populated; for the full schema and more information on the fields, refer to [saf.mitre.org/#/normalize](https://saf.mitre.org/#/normalize)) diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md new file mode 100644 index 000000000..ae3780d05 --- /dev/null +++ b/src/courses/mappers/03.md @@ -0,0 +1,118 @@ +--- +order: 3 +next: 04.md +title: Background & Overview 2 +author: Charles Hu +--- + + +### HDF Schema Breakdown + +The HDF schema can be grouped into 3 sets of structures, with each structure being a subset of the previous structure. These groupings are: profiles, controls, and results. + +The profiles structure contains metadata on the scan target of the original security service export and on the run performed by the security tool. This provides a high-level overview of the scan service run and target which are both digestible and easily accessible to the user. A generalized format is as follows: + +``` +profiles: [ + 0: { + name //Name of profile, usually the original security service tool; should be unique + version //Version of security service tool + sha256 //Hash of HDF file; NOTE: AUTOMATICALLY GENERATED BY HDF CONVERTERS, DO NOT POPULATE + title //Title of security service scan; should be human readable + maintainer //Maintainer + summary //Summary of security service export + license //Copyright license + copyright //Copyright holder + copyright_email //Copyright holder's email + supports //Supported platform targets + attributes //Inputs/attributes used in scan + groups //Set of descriptions for the control groups + controls //Controls substructure (see below) + status //Status of profile (typically 'loaded') + } + ... //More items may exist if the security service produces multiple scan targets per export +] +``` + +Controls are security parameters used to prevent unauthorized access to sensitive information or infrastructure. In the case of HDF Converters, the controls structure is a collection of such controls tested for retroactively by an external security service to ensure that the target complies with vulnerability and weakness prevention standards. The controls structure is a subset of the profiles structure. A generalized format is as follows: + +``` +controls: [ + 0: { + id //ID of control; used for sorting, should be unique for each unique control + title //Title of control + desc //Description of the control + descriptions //Additional descriptions; usually 'check' and 'fix' text for control + impact //Security severity of control + refs //References to external control documentation + tags //Control tags; typically correlate to existing vulnerability/weakness database (e.g., NIST, CVE, CWE) + code //Control source code for code preservation + source_location //Location of control within source code + results //Results substructure (see below) + } + ... //More items may exist if there are multiple controls reported per profile +] +``` + +The results structure contains information on the results of specific tests ran by the security service on the scan target against a set of security controls. These results will always correlate to a certain control and will either report 'passed' or 'failed' to indicate the test status (other statuses exist but are rare), which cumulatively affect the compliance level of the scan target with the indicated control set. The results structure is a subset of the controls structure. A generalized structure is as follows: + +``` +results: [ + 0: { + status //Pass/fail status of test (other statuses exist but are rare) + code_desc //Test expectations as defined by control + message //Demonstration of expected and actual result of test to justify test status + run_time //Overall runtime of test + start_time //Starting time of test + } + ... //More items may exist if there are multiple results reported per control +] +``` + +These aforementioned structures cumulatively result in the following generalized structure which primarily defines the HDF: + +``` +//Data fields have been removed for the sake of demonstration +profiles: [ + 0: { + controls: [ + 0: { + results: [ + 0: { + }, + ... + ] + }, + ... + ] + }, + ... +] +``` + +There are additional structures in the HDF schema which are used for metadata/extraneous information storage. These exist alongside the profiles structure on the top level of the HDF schema. The general structure for the top level of the HDF schema is as follows: + +``` +{ + platform: { //Information on the platform handling the HDF file; usually 'Heimdall Tools' + name //Platform name + release //Platform version + target_id //Platform target ID + } + version //Platform version + statistics: { //Statistics relating to target scan run + duration //Duration of run + } + profiles //Profiles structure + passthrough: { //Extraneous information storage + auxiliary_data: [ //Storage for unused data from the sample file + 0: { + name //Name of auxiliary data source + data //Auxiliary data + } + ... //More items may exist if there are multiple auxiliary data sources available + ] + raw //Raw data dump of input security service export + } +} +``` diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md new file mode 100644 index 000000000..6c447ac4f --- /dev/null +++ b/src/courses/mappers/04.md @@ -0,0 +1,301 @@ +--- +order: 4 +next: 05.md +title: Background & Overview 3 +author: Charles Hu +--- + +### HDF Schema Mapping Example Walkthrough + +The following is an example of a high-level mapping from the Twistlock file format to the HDF. The purpose of this demonstration is to give an easy, non-technical approach to generating a prototype for \*-to-HDF mappers that can be used as a guideline for the development of actual technical mappers for the HDF Converter. This process is generally recommended as the first step for the development of any mapper for the HDF Converter. + +(NOTE: The format used by your export may not match the one being used in this demonstration. The mappings used in this example are for demonstration purposes and should not be taken as a definitive resource; creative interpretation is necessary for the most accurate mapping according to the specifics of your security service export.) + +Given a sample Twistlock scan export (as seen below), our goal is to roughly identify and group data fields according to our 3 primary structures in HDF (profiles, controls, and results) and the non-applicable structure (passthrough). For profiles, we want to find metadata; for controls, we want to find general security control information; for results, we want to find specific security control testing information; and we can place everything else into passthrough. + +``` +//Sample Twistlock scan export +{ + "results": [ + { + "id": "sha256:111", + "name": "registry.io/test", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:222", + "collections": [ + "All", + "TEST-COLLECTION" + ], + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": [ + "MPLv2.0" + ] + } + ], + "vulnerabilities": [ + { + "id": "CVE-2021-43529", + "status": "affected", + "cvss": 9.8, + "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "severity": "critical", + "packageName": "nss-util", + "packageVersion": "3.67.0-7.el8_5", + "link": "https://access.redhat.com/security/cve/CVE-2021-43529", + "riskFactors": [ + "Remote execution", + "Attack complexity: low", + "Attack vector: network", + "Critical severity", + "Recent vulnerability" + ], + "impactedVersions": [ + "*" + ], + "publishedDate": "2021-12-01T00:00:00Z", + "discoveredDate": "2022-05-18T12:24:22Z", + "layerTime": "2022-05-16T23:12:25Z" + } + ], + "vulnerabilityDistribution": { + "critical": 1, + "high": 0, + "medium": 0, + "low": 0, + "total": 1 + }, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-03T08:38:31Z" + }, + { + "created": "2022-05-03T08:39:27Z" + } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "asdfghjkl" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%333" +} +``` + +Thus, upon successive passes we can roughly outline what we expect each data field in the Twistlock scan export to correlate to in the HDF. We first want to identify metadata which will most likely belong in the profiles structure. Such data fields will primarily be related to the general security scan itself or be related to the target system that is being scanned, as seen below: + +``` +//Data values are removed for visual clarity +{ + "results": [ + { + "id", //Scan target metadata -> profiles + "name", // + "distro", // + "distroRelease", // + "digest", // + "collections", // + "packages": [], // + "vulnerabilities": [ + { + "id", + "status", + "cvss", + "description", + "severity", + "packageName", + "packageVersion", + "link", + "riskFactors": [], + "impactedVersions": [], + "publishedDate", + "discoveredDate", + "layerTime" + } + ], + "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles + "vulnerabilityScanPassed", // + "history": [], //Scan target package install history -> profiles + "scanTime", //Twistlock scan metadata -> profiles + "scanID" // + } + ], + "consoleURL" //Twistlock scan metadata -> profiles +} +``` + +Next, we want to roughly outline general security control information that correlates to our controls structure. For this, we want to look for information that provides a background for the tests performed by the security service. Usually, this strongly correlates to information that gives us a why, what, and how for the tests that are performed, as seen with the fields that are highlighted below: + +``` +//Data values are removed for visual clarity +{ + "results": [ + { + "id", //Scan target metadata -> profiles + "name", // + "distro", // + "distroRelease", // + "digest", // + "collections", // + "packages": [], // + "vulnerabilities": [ + { + "id", //ID of control tested against -> controls + "status", + "cvss", //CVSS severity score of control -> controls + "description", //Description of control -> controls + "severity", //Severity of control failure -> controls + "packageName", + "packageVersion", + "link", //Link to control documentation -> controls + "riskFactors": [], + "impactedVersions": [], + "publishedDate", //Control discovery date -> controls + "discoveredDate", + "layerTime" + } + ], + "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles + "vulnerabilityScanPassed", // + "history": [], //Scan target package install history -> profiles + "scanTime", //Twistlock scan metadata -> profiles + "scanID" // + } + ], + "consoleURL" //Twistlock scan metadata -> profiles +} +``` + +After that, we want to outline items that relate to specific instances of control tests ran against the scan target as part of the results structure. Usually, this strongly correlates to information that gives us a who, what, and when for the specific tests that are performed, as seen with the fields that are highlighted below: + +``` +//Data values are removed for visual clarity +{ + "results": [ + { + "id", //Scan target metadata -> profiles + "name", // + "distro", // + "distroRelease", // + "digest", // + "collections", // + "packages": [], // + "vulnerabilities": [ + { + "id", //ID of control tested against -> controls + "status", //Pass/fail result of the control test -> results + "cvss", //CVSS severity score of control -> controls + "description", //Description of control -> controls + "severity", //Severity of control failure -> controls + "packageName", //Package ran against control test -> results + "packageVersion", //Version of package ran against control test -> results + "link", //Link to control documentation -> controls + "riskFactors": [], //Risk factors associated with failing this specific control test -> results + "impactedVersions": [], //Vulnerable versions of package ran against control test -> results + "publishedDate", //Control discovery date -> controls + "discoveredDate", //Date this control result was discovered -> results + "layerTime" + } + ], + "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles + "vulnerabilityScanPassed", // + "history": [], //Scan target package install history -> profiles + "scanTime", //Twistlock scan metadata -> profiles + "scanID" // + } + ], + "consoleURL" //Twistlock scan metadata -> profiles +} +``` + +For fields that we cannot reasonably categorize or have no information about, we can instead just place them into the passthrough structure, as seen below: + +``` +//Data values are removed for visual clarity +{ + "results": [ + { + "id", //Scan target metadata -> profiles + "name", // + "distro", // + "distroRelease", // + "digest", // + "collections", // + "packages": [], // + "vulnerabilities": [ + { + "id", //ID of control tested against -> controls + "status", //Pass/fail result of the control test -> results + "cvss", //CVSS severity score of control -> controls + "description", //Description of control -> controls + "severity", //Severity of control failure -> controls + "packageName", //Package ran against control test -> results + "packageVersion", //Version of package ran against control test -> results + "link", //Link to control documentation -> controls + "riskFactors": [], //Risk factors associated with failing this specific control test -> results + "impactedVersions": [], //Vulnerable versions of package ran against control test -> results + "publishedDate", //Control discovery date -> controls + "discoveredDate", //Date this control result was discovered -> results + "layerTime" //Information on package install time; extraneous -> passthrough + } + ], + "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles + "vulnerabilityScanPassed", // + "history": [], //Scan target package install history -> profiles + "scanTime", //Twistlock scan metadata -> profiles + "scanID" // + } + ], + "consoleURL" //Twistlock scan metadata -> profiles +} +``` + +With this, we now have a general outline which roughly connects each data field in the Twistlock sample export to one of our structures in the HDF. In order to improve the accuracy of this mapping, we can now begin connecting [specific fields in the HDF schema](#fullschema) with the data fields in the sample export using our rough draft as a guide. + +If we cannot find a field in the HDF schema that fits with a certain field in the sample export per our original groupings, we can instead look to the other structures to see if they have applicable fields or place the field into the passthrough structure as a last resort. + +``` +//Data values are removed for visual clarity +{ + "results": [ + { + "id", //profiles -> passthrough.auxiliary_data.data + "name", //profiles -> profiles.name + "distro", //profiles -> passthrough.auxiliary_data.data + "distroRelease", //profiles -> passthrough.auxiliary_data.data + "digest", //profiles -> passthrough.auxiliary_data.data + "collections", //profiles -> profiles.title + "packages": [], //profiles -> passthrough.auxiliary_data.data + "vulnerabilities": [ + { + "id", //controls -> profiles.controls.id + "status", //results -> profiles.controls.results.status + "cvss", //controls -> profiles.controls.code + "description", //controls -> profiles.controls.desc + "severity", //controls -> profiles.controls.impact + "packageName", //results -> profiles.controls.results.code_desc + "packageVersion", //results -> profiles.controls.results.code_desc + "link", //controls -> profiles.controls.code + "riskFactors": [], //results -> profiles.controls.code + "impactedVersions": [], //results -> profiles.controls.results.code_desc + "publishedDate", //controls -> profiles.controls.code + "discoveredDate", //results -> profiles.controls.results.start_time + "layerTime" //passthrough -> profiles.controls.code + } + ], + "vulnerabilityDistribution": {}, //profiles -> profiles.summary + "vulnerabilityScanPassed", //profiles -> passthrough.auxiliary_data.data + "history": [], //profiles -> passthrough.auxiliary_data.data + "scanTime", //profiles -> passthrough.auxiliary_data.data + "scanID" //profiles -> passthrough.auxiliary_data.data + } + ], + "consoleURL" //profiles -> passthrough.auxiliary_data.data +} +``` + +With this, we now have a detailed high-level mapping for the conversion from an external file format to the HDF, which we can use for the [technical implementation of a \*-to-HDF mapper](#create). diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md new file mode 100644 index 000000000..7795fed4c --- /dev/null +++ b/src/courses/mappers/05.md @@ -0,0 +1,36 @@ +--- +order: 5 +next: 06.md +title: Background & Overview 4 +author: Charles Hu +--- + +### HDF Converters Structure + +The following is a simplified depiction of the directory tree for the HDF Converter. Only noteworthy and potentially useful files and directories are included. It is not imperative to memorize the structure, but it is useful to familiarize yourself with it to better understand what exists where within the HDF Converter for future reference. + +``` +hdf-converters ++-- data +| +-- converters +| | +-- csv2json.ts +| | +-- xml2json.ts ++-- sample_jsons //Sample exports for mapper testing are located here ++-- src //*-to-HDF mappers are located here +| +-- converters-from-hdf //HDF-to-* mappers are located here +| | +-- reverse-any-base-converter.ts +| | +-- reverse-base-converter.ts +| +-- mappings //Non-HDF mappers are located here (e.g., CVE, CCI, NIST) +| +-- utils +| | +-- fingerprinting.ts +| | +-- global.ts +| +-- base-converter.ts ++-- test //Mapper tests are located here +| +-- mappers +| | +-- forward //*-to-HDF tests +| | +-- reverse //HDF-to-* tests +| | +-- utils.ts ++-- types //Explicit data typing for known export schemas ++-- index.ts ++-- package.json +``` diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md new file mode 100644 index 000000000..d7276606a --- /dev/null +++ b/src/courses/mappers/06.md @@ -0,0 +1,88 @@ +--- +order: 6 +next: 07.md +title: Background & Overview 5 +author: Charles Hu +--- + +### Base Converter Tools + +[//] # WIP + +The base-converter class is the underlying foundation which enables \*-to-HDF mapping in HDF Converters. It defines \*-to-HDF mappers and provides critical tools which allow for the construction of such mappers. All \*-to-HDF mappers inherit from this class and therefore have access to the tools that this class provides; it is thus imperative that you utilize these tools to their fullest potential to ease and simplify mapper development. The provided tools are as follows: + +- path: Denote JSON object path to go to + + - Use: + + ``` + path: PATH_AS_STRING + ``` + + - Example: + + ``` + //Attribute 'id' will be set as whatever JSON object attribute 'vulnerability.id' is + id: {path: 'vulnerability.id'} + ``` + +- transformer: Execute given code sequence; operates similar to an anonymous function + + - Use: + + ``` + transformer: (PARAMETERS): OUTPUT_TYPE => {CODE_TO_EXECUTE} + ``` + + - Example: + + ``` + //Attribute 'code' will be set as the returned stringified JSON object of input 'vulnerability' + code: { + transformer: (vulnerability: Record): string => { + return JSON.stringify(vulnerability, null, 2); + } + } + ``` + +- arrayTransformer: Execute given code sequence on a given array; primarily used when in an attribute that is an array of objects + + - Use: + + ``` + arrayTransformer: CODE_TO_EXECUTE + ``` + + - Example: + + ``` + //The function 'deduplicateId' will run against all items in the current array that the 'arrayTransformer' was called inside + arrayTransformer: deduplicateId + ``` + +- pathTransform: + + - Use: + + ``` + ``` + + - Example: + + ``` + ``` + +- key: Used by Base Converter to sort the an array of objects by + + - Use: + + ``` + key: KEY_AS_STRING + ``` + + - Example: + + ``` + //'id' is now considered the key by which this section will be sorted by + key: 'id' + ``` diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md new file mode 100644 index 000000000..9bd94a1e5 --- /dev/null +++ b/src/courses/mappers/07.md @@ -0,0 +1,55 @@ +--- +order: 7 +next: 08.md +title: Mapper Creation 1 +author: Charles Hu +--- + +## Mapper Creation + +### Environment Set Up + +Node.js (a runtime environment for Javascript) and Yarn (a package manager for Node.js) are external utilities which are utilized extensively within this guide. The following section details their installation process. + +Linux/Mac OS: + +1. Install [nvm](https://github.com/nvm-sh/nvm#install--update-script). + + - 1a. Use either of the following commands to install nvm: + + ``` + curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.1/install.sh | bash + ``` + ``` + wget -qO- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.1/install.sh | bash + ``` + + - 1b. Either restart the terminal or run the following commands to use nvm: + + ``` + export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")" + + [ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh" # This loads nvm + ``` + +2. Run the following command to install and use Node.js v16: + +``` +nvm install 16 +``` + +3. Install [Yarn](https://classic.yarnpkg.com/en/): + +``` +npm install --global yarn +``` + +Windows: + +1. Install [Node.js v16 via the installer](https://nodejs.org/en/download/). If v16 is not available from the page, use this [archive](https://nodejs.org/dist/v16.16.0/). + +2. Install [Yarn](https://classic.yarnpkg.com/en/): + +``` +npm install --global yarn +``` diff --git a/src/courses/mappers/08.md b/src/courses/mappers/08.md new file mode 100644 index 000000000..fc99cb4aa --- /dev/null +++ b/src/courses/mappers/08.md @@ -0,0 +1,222 @@ +--- +order: 8 +next: 09.md +title: Mapper Creation 2 +author: Charles Hu +--- + +### \*-to-HDF Creation Guide + +1. Fork/branch a development repository from the main [Heimdall2 GitHub repository](https://github.com/mitre/heimdall2). + + - SAF team developers have write access to the main repository and should [create a branch](https://docs.github.com/en/desktop/contributing-and-collaborating-using-github-desktop/making-changes-in-a-branch/managing-branches#creating-a-branch) on the primary development repository. Non-SAF team developers should instead [create a fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo#forking-a-repository) of the main repository and create a development branch there. + +2. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. + +3. Have a rough, high-level outline of how your export translates to the HDF. For an example of this process, refer to the [HDF Schema Mapping Example Walkthrough](#example) section. + +4. Set up for \*-to-HDF mapper development. + + - 4a. Install the necessary dependencies for Heimdall2. Under the heimdall2 directory, enter the following command in the terminal: + + ``` + yarn install + ``` + + - 4b. Create a blank TypeScript file under the src directory in hdf-converters. It should be named: + + ``` + {YOUR-EXPORT-NAME-HERE}-mapper.ts + ``` + + - 4c. Select the appropriate [mapper skeleton](#skeleton) for your export type. Place them in the file created in step 4b. Replace names (skeleton by default) as necessary. + + - 4d. Export your mapper class created in the previous steps by specifying its export in the index.ts file. Add the following line: + + ``` + export * from './src/{YOUR-EXPORT-NAME-HERE}-mapper'; + ``` + + - 4e. Create a new directory named {YOUR-EXPORT-NAME-HERE}_mapper under the sample_jsons directory in hdf-converters. Create another directory named sample_input_report in the directory you just made. The file structure should look like this: + + ``` + +-- sample_jsons + | +-- {YOUR-EXPORT-NAME-HERE}-mapper + | | +-- sample_input_report + ``` + + - 4f. Place your sample export under the sample_input_report directory. Your sample export should be genericized to avoid any leaking of sensitive information. The file structure should now look like this: + + ``` + +-- sample_jsons + | +-- {YOUR-EXPORT-NAME-HERE}-mapper + | | +-- sample_input_report + | | | +-- {YOUR-SAMPLE-EXPORT} + ``` + + - 4g. Create a blank TypeScript file under the test/mappers/forward directory in hdf-converters. It should be named: + + ``` + {YOUR-EXPORT-NAME-HERE}_mapper.spec.ts + ``` + + - 4h. Select the appropriate [mapper testing skeleton](#skeleton) for your export type. Place it in the file created in step 4g. Replace names (skeleton by default) as necessary. + +5. Add fingerprinting to identify your security service scan export. + + - 5a. Go to the file report_intake.ts under the heimdall2/apps/frontend/src/store directory. + + - 5b. Import your mapper file. You should be able to add the name of your mapper class to a pre-existing import statement pointing at hdf-converters as follows: + + ``` + import { + ASFFResults as ASFFResultsMapper, + BurpSuiteMapper, + ... + {YOUR-MAPPER-CLASS-HERE} + } from '@mitre/hdf-converters'; + ``` + + - 5c. Instantiate your mapper class in the convertToHdf switch block. Add the following lines: + + ``` + case '{YOUR-EXPORT-SERVICE-NAME-HERE}': + return new {YOUR-MAPPER-CLASS-HERE}(convertOptions.data).toHdf(); + ``` + + - 5d. Navigate to the file fingerprinting.ts in the src/utils directory in hdf-converters. Add keywords that are unique to your sample export to the fileTypeFingerprints variable. It should be formatted as follows: + + ``` + export const fileTypeFingerprints = { + asff: ['Findings', 'AwsAccountId', 'ProductArn'], + ... + {YOUR-EXPORT-SERVICE-NAME-HERE}: [{UNIQUE KEYWORDS AS STRINGS}] + }; + ``` + +6. Create the \*-to-HDF mapper. + + - 6a. Return to the {YOUR-EXPORT-NAME-HERE}-mapper.ts file. In the file, you should have a generic skeleton mapper picked according to your export type. + + - 6b. Certain security services produce exports which are not immediately usable by the skeleton mapper. In this case, pre-processing on the export and post-processing on the generated HDF file is necessary in order to ensure compatibility. + + - 6c. The skeleton mapper and [base-converter](#base) have been designed to provide the base functionality needed for \*-to-HDF mapper generation. For most developers, mapper creation will be limited to assigning objects from the export structure to correlating attributes in the mapper according to the HDF schema. + + - An example of this process is provided in the [\*-to-HDF Mapper Construction Example](#example2) section. + + - 6d. [Commit your changes](https://github.com/git-guides/git-commit) with the [signoff option](https://git-scm.com/docs/git-commit) and [push the changes](https://github.com/git-guides/git-push) to your development branch. This should queue up the Github Actions pipeline which includes a Netlify instance of Heimdall2 which you can use to test if your mapper is generating a HDF file correctly. + +7. Set up and use regression testing on your mapper. + + - 7a. Uncomment out the commented out lines in the {YOUR-SAMPLE-EXPORT}-hdf.json file created in step 4f. This will allow the regression tests to automatically generate a HDF output file whenever you run the tests. The commented out lines should look similar to the following: + + ``` + // fs.writeFileSync( + // 'sample_jsons/skeleton_mapper/skeleton-hdf.json', + // JSON.stringify(mapper.toHdf(), null, 2) + // ); + ``` + + - 7b. Using the terminal, cd into the hdf-converters directory and run the following command. This command will run your mapper against the sample export file in sample_jsons and test to see if the output is generated as expected. + + ``` + yarn run test --verbose --silent=false ./test/mappers/forward/{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts + ``` + + - 7c. Your tests should generate HDF output files for when --with-raw is not flagged (default behavior) and when it is flagged (denoted by -withraw in the filename). It will also compare the contents of these generated files with a temporary mapper instance created in the test itself. Review the test output to ensure that the tests are all passing and review the HDF output files to ensure that the contents of the mapping are being generated correctly. + + - 7d. Recomment out the lines from step 7b. + +8. Document your new mapper in the README for hdf-converters under the Supported Formats section. It should be formatted as follows: + +``` +{#}. [{YOUR-EXPORT-NAME-HERE}] - {MAPPER INPUT DESCRIPTION} +``` + +9. Commit your final changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, your mapper will be merged into the main development branch and [scheduled for release](https://github.com/mitre/heimdall2/wiki/How-to-create-a-Heimdall2-release) as an officially supported conversion format for the HDF Converters. + +10. Create a development branch against the [SAF CLI repository](https://github.com/mitre/saf) and create a draft pull request for your new branch. + +11. Set up for SAF CLI mapper integration. + + - 11a. In the package.json file, update the versions of @mitre/hdf-converters and @mitre/heimdall-lite to the [latest release of Heimdall2](https://github.com/mitre/heimdall2/releases). + + - 11b. In the src/commands/convert directory, create a blank TypeScript file. It should be named: + + ``` + {YOUR-EXPORT-NAME-HERE}2hdf.ts + ``` + + - 11c. In the test/sample_data directory, create a directory named {YOUR-EXPORT-NAME-HERE}. Underneath it, create a directory named sample_input_report. The file structure should now look like this: + + ``` + +-- sample_data + | +-- {YOUR-EXPORT-NAME-HERE} + | | +-- sample_input_report + ``` + + - 11d. Place your sample export under the sample_input_report directory. Your sample export should be genericized to avoid any leaking of sensitive information. Under the {YOUR-EXPORT-NAME-HERE} directory, place your output HDF files generated during the testing phase of step 7c. The file structure should now look like this: + + ``` + +-- sample_data + | +-- {YOUR-EXPORT-NAME-HERE} + | | +-- sample_input_report + | | | +-- {YOUR-SAMPLE-EXPORT} + | | +-- {YOUR-EXPORT-NAME-HERE}-hdf.json + | | +-- {YOUR-EXPORT-NAME-HERE}-hdf-withraw.json + ``` + + - 11e. In the test/commands/convert directory, create a blank TypeScript file. It should be named: + + ``` + {YOUR-EXPORT-NAME-HERE}2hdf.test.ts + ``` + +12. Integrate your mapper with the SAF CLI. + + - 12a. Insert the [skeleton](#skeleton) for integrating a HDF mapper with the SAF CLI. Replace names (skeleton by default) as necessary. + + - 12b. Insert the [skeleton](#skeleton) for a convert command test for the SAF CLI. Replace names (skeleton by default) as necessary. + + - 12c. Navigate to the index.ts file under the src/commands/convert directory. Import your mapper using the existing import block as follows: + + ``` + import { + ASFFResults, + ... + {YOUR-MAPPER-CLASS-HERE} + } from '@mitre/hdf-converters' + ``` + + - 12d. Under the switch block in the getFlagsForInputFile function, add your mapper class as it is defined in step 5d for fingerprinting for the generic convert command. If the convert command for your mapper has any additional flags beyond the standard --input and --output flags, return the entire flag block in the switch case. This is demonstrated as follows: + + ``` + switch (Convert.detectedType) { + ... + case {YOUR-EXPORT-SERVICE-NAME-HERE}: + return {YOUR-CLI-CONVERT-CLASS}.flags //Only add if special flags exist + ... + return {} + } + ``` + +13. Edit the README file to reflect your newly added conversion command under the To HDF section. It should be formatted as follows: + +``` +##### {YOUR-EXPORT-NAME-HERE} to HDF + +\``` +convert {YOUR-EXPORT-NAME-HERE}2hdf Translate a {YOUR-EXPORT-NAME-HERE} results {EXPORT-TYPE} into + a Heimdall Data Format JSON file + +OPTIONS + -i, --input=input Input {EXPORT-TYPE} File + -o, --output=output Output HDF JSON File + -w, --with-raw Include raw input file in HDF JSON file + +EXAMPLES + saf convert {YOUR-EXPORT-NAME-HERE}2hdf -i {INPUT-NAME} -o output-hdf-name.json +\``` +``` + +14. Commit your changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, merged, and [released](https://github.com/mitre/saf/wiki/Creating-a-Release-of-the-SAF-CLI), your mapper will be callable using the SAF CLI. diff --git a/src/courses/mappers/09.md b/src/courses/mappers/09.md new file mode 100644 index 000000000..0325c5914 --- /dev/null +++ b/src/courses/mappers/09.md @@ -0,0 +1,269 @@ +--- +order: 9 +next: 10.md +title: Mapper Creation 3 +author: Charles Hu +--- + +### Mapper Creation Skeletons + +- Skeleton for a general file-based \*-to-HDF mapper: + +``` +import {ExecJSON} from 'inspecjs'; +import _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform +} from './base-converter'; + +const IMPACT_MAPPING: Map = new Map([ + ['critical', 0.9], + ['high', 0.7], + ['medium', 0.5], + ['low', 0.3] +]); + +export class SkeletonMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id: null //Insert data + }, + version: HeimdallToolsVersion, + statistics: { + duration: null //Insert data + }, + profiles: [ + { + name: '', //Insert data + title: null, //Insert data + maintainer: null, //Insert data + summary: null, //Insert data + license: null, //Insert data + copyright: null, //Insert data + copyright_email: null, //Insert data + supports: [], //Insert data + attributes: [], //Insert data + depends: [], //Insert data + groups: [], //Insert data + status: 'loaded', //Insert data + controls: [ + { + key: 'id', + tags: {}, //Insert data + descriptions: [], //Insert data + refs: [], //Insert data + source_location: {}, //Insert data + title: null, //Insert data + id: '', //Insert data + desc: null, //Insert data + impact: 0, //Insert data + code: null, //Insert data + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, //Insert data + code_desc: '', //Insert data + message: null, //Insert data + run_time: null, //Insert data + start_time: '' //Insert data + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed + ...(this.withRaw && {raw: data}) + }; + } + } + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw + } +} +``` + +- Skeleton for a general test for a \*-to-HDF mapper in HDF Converters: + +``` +import fs from 'fs'; +import {SkeletonMapper} from '../../../src/skeleton-mapper'; +import {omitVersions} from '../../utils'; + +describe('skeleton_mapper', () => { + it('Successfully converts Skeleton targeted at a local/cloned repository data', () => { + const mapper = new SkeletonMapper( + fs.readFileSync( + 'sample_jsons/skeleton_mapper/sample_input_report/skeleton.json', + {encoding: 'utf-8'} + ) + ); + + // fs.writeFileSync( + // 'sample_jsons/skeleton_mapper/skeleton-hdf.json', + // JSON.stringify(mapper.toHdf(), null, 2) + // ); + + expect(omitVersions(mapper.toHdf())).toEqual( + omitVersions( + JSON.parse( + fs.readFileSync( + 'sample_jsons/skeleton_mapper/skeleton-hdf.json', + { + encoding: 'utf-8' + } + ) + ) + ) + ); + }); +}); + +describe('skeleton_mapper_withraw', () => { + it('Successfully converts withraw flagged Skeleton targeted at a local/cloned repository data', () => { + const mapper = new SkeletonMapper( + fs.readFileSync( + 'sample_jsons/skeleton_mapper/sample_input_report/skeleton.json', + {encoding: 'utf-8'} + ), + true + ); + + // fs.writeFileSync( + // 'sample_jsons/skeleton_mapper/skeleton-hdf-withraw.json', + // JSON.stringify(mapper.toHdf(), null, 2) + // ); + + expect(omitVersions(mapper.toHdf())).toEqual( + omitVersions( + JSON.parse( + fs.readFileSync( + 'sample_jsons/skeleton_mapper/skeleton-hdf-withraw.json', + { + encoding: 'utf-8' + } + ) + ) + ) + ); + }); +}); +``` + +- Skeleton for SAF CLI mapper conversion integration: + +``` +import {Command, Flags} from '@oclif/core' +import fs from 'fs' +import {SkeletonMapper as Mapper} from '@mitre/hdf-converters' +import {checkSuffix} from '../../utils/global' + +export default class Skeleton2HDF extends Command { + static usage = 'convert skeleton2hdf -i -o ' + + static description = 'Translate a Skeleton output file into an HDF results set' + + static examples = ['saf convert skeleton2hdf -i skeleton.json -o output-hdf-name.json'] + + static flags = { + help: Flags.help({char: 'h'}), + input: Flags.string({char: 'i', required: true, description: 'Input Skeleton file'}), + output: Flags.string({char: 'o', required: true, description: 'Output HDF file'}), + 'with-raw': Flags.boolean({char: 'w', required: false}), + } + + async run() { + const {flags} = await this.parse(Skeleton2HDF) + const input = fs.readFileSync(flags.input, 'utf8') + + const converter = new Mapper(input, flags.['with-raw']) + fs.writeFileSync(checkSuffix(flags.output), JSON.stringify(converter.toHdf())) + } +} +``` +- Skeleton for a convert command test for the SAF CLI: + +``` +import {expect, test} from '@oclif/test' +import tmp from 'tmp' +import path from 'path' +import fs from 'fs' +import {omitHDFChangingFields} from '../utils' + +describe('Test skeleton', () => { + const tmpobj = tmp.dirSync({unsafeCleanup: true}) + + test + .stdout() + .command([ + 'convert skeleton2hdf', + '-i', + path.resolve( + './test/sample_data/skeleton/sample_input_report/skeleton_sample.json', + ), + '-o', + `${tmpobj.name}/skeletontest.json`, + ]) + .it('hdf-converter output test', () => { + const converted = JSON.parse( + fs.readFileSync(`${tmpobj.name}/skeletontest.json`, 'utf8'), + ) + const sample = JSON.parse( + fs.readFileSync( + path.resolve('./test/sample_data/skeleton/skeleton-hdf.json'), + 'utf8', + ), + ) + expect(omitHDFChangingFields(converted)).to.eql( + omitHDFChangingFields(sample), + ) + }) +}) + +describe('Test skeleton withraw flag', () => { + const tmpobj = tmp.dirSync({unsafeCleanup: true}) + + test + .stdout() + .command([ + 'convert skeleton2hdf', + '-i', + path.resolve( + './test/sample_data/skeleton/sample_input_report/skeleton_sample.json', + ), + '-o', + `${tmpobj.name}/skeletontest.json`, + '-w', + ]) + .it('hdf-converter withraw output test', () => { + const converted = JSON.parse( + fs.readFileSync(`${tmpobj.name}/skeletontest.json`, 'utf8'), + ) + const sample = JSON.parse( + fs.readFileSync( + path.resolve('./test/sample_data/skeleton/skeleton-hdf-withraw.json'), + 'utf8', + ), + ) + expect(omitHDFChangingFields(converted)).to.eql( + omitHDFChangingFields(sample), + ) + }) +}) +``` diff --git a/src/courses/mappers/10.md b/src/courses/mappers/10.md new file mode 100644 index 000000000..c4b78978f --- /dev/null +++ b/src/courses/mappers/10.md @@ -0,0 +1,10 @@ +--- +order: 10 +next: 11.md +title: Mapper Creation 4 +author: Charles Hu +--- + +### Best Practices + +[//] # WIP diff --git a/src/courses/mappers/11.md b/src/courses/mappers/11.md new file mode 100644 index 000000000..2492dc93f --- /dev/null +++ b/src/courses/mappers/11.md @@ -0,0 +1,158 @@ +--- +order: 11 +next: 12.md +title: Mapper Creation 5 +author: Charles Hu +--- + +### \*-to-HDF Mapper Construction Example + +The following is an example of a implemented HDF mapper for Twistlock created using a [high-level Twistlock-to-HDF mapping](#example) and [tools from base-converter](#base). + +``` +const IMPACT_MAPPING: Map = new Map([ + ['critical', 0.9], + ['important', 0.9], + ['high', 0.7], + ['medium', 0.5], + ['moderate', 0.5], + ['low', 0.3] +]); + +export class TwistlockMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id: {path: 'results[0].name'} + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + path: 'results', + name: 'Twistlock Scan', + title: { + transformer: (data: Record): string => { + const projectArr = _.has(data, 'collections') + ? _.get(data, 'collections') + : 'N/A'; + const projectName = Array.isArray(projectArr) + ? projectArr.join(' / ') + : projectArr; + return `Twistlock Project: ${projectName}`; + } + }, + summary: { + transformer: (data: Record): string => { + const vulnerabilityTotal = _.has(data, 'vulnerabilityDistribution') + ? `${JSON.stringify( + _.get(data, 'vulnerabilityDistribution.total') + )}` + : 'N/A'; + const complianceTotal = _.has(data, 'complianceDistribution') + ? `${JSON.stringify(_.get(data, 'complianceDistribution.total'))}` + : 'N/A'; + return `Package Vulnerability Summary: ${vulnerabilityTotal} Application Compliance Issue Total: ${complianceTotal}`; + } + }, + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + path: 'vulnerabilities', + key: 'id', + tags: { + nist: ['SI-2', 'RA-5'], + cci: ['CCI-002605', 'CCI-001643'], + cveid: {path: 'id'} + }, + refs: [], + source_location: {}, + title: {path: 'id'}, + id: {path: 'id'}, + desc: {path: 'description'}, + impact: { + path: 'severity', + transformer: impactMapping(IMPACT_MAPPING) + }, + code: { + transformer: (vulnerability: Record): string => { + return JSON.stringify(vulnerability, null, 2); + } + }, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: { + transformer: (data: Record): string => { + const packageName = _.has(data, 'packageName') + ? `${JSON.stringify(_.get(data, 'packageName'))}` + : 'N/A'; + const impactedVersions = _.has(data, 'impactedVersions') + ? `${JSON.stringify(_.get(data, 'impactedVersions'))}` + : 'N/A'; + return `Package ${packageName} should be updated to latest version above impacted versions ${impactedVersions}`; + } + }, + message: { + transformer: (data: Record): string => { + const packageName = _.has(data, 'packageName') + ? `${JSON.stringify(_.get(data, 'packageName'))}` + : 'N/A'; + const packageVersion = _.has(data, 'packageVersion') + ? `${JSON.stringify(_.get(data, 'packageVersion'))}` + : 'N/A'; + return `Expected latest version of ${packageName}\nDetected vulnerable version ${packageVersion} of ${packageName}`; + } + }, + start_time: {path: 'discoveredDate'} + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + let resultsData = _.get(data, 'results'); + if (Array.isArray(resultsData)) { + resultsData = resultsData.map((result: Record) => + _.omit(result, [ + 'name', + 'collections', + 'complianceDistribution', + 'vulnerabilities', + 'vulnerabilityDistribution' + ]) + ); + } + return { + auxiliary_data: [ + { + name: 'Twistlock', + data: { + results: resultsData, + consoleURL: _.get(data, 'consoleURL') + } + } + ], + ...(this.withRaw && {raw: data}) + }; + } + } + }; + constructor(twistlockJson: string, withRaw = false) { + super(JSON.parse(twistlockJson), true); + this.withRaw = withRaw; + } +} +``` diff --git a/src/courses/mappers/README.md b/src/courses/mappers/README.md new file mode 100644 index 000000000..257c08ec7 --- /dev/null +++ b/src/courses/mappers/README.md @@ -0,0 +1,14 @@ +--- +order: 1 +next: 02.md +title: Introduction +author: Charles Hu +--- + +## Introduction + +HDF Converters is a custom data normalization tool for transforming exported data from various security tool formats into the [Heimdall Data Format (HDF)](https://saf.mitre.org/#/normalize). It is currently integrated into [Heimdall2](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance and testing within an automated build pipeline. + +Mappers are frameworks that allow the underlying conversion infrastructure to correlate certain objects or values from one overarching object or file to another overarching object or file. In the case of HDF Converters, these mappers allow for the conversion of some security service formats to HDF (\*-to-HDF) and vice-versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. + +The process for creating a mapper for HDF Converters is detailed below. In order to ensure that the created mapper produces a HDF file that is both accurate and detailed, it is important that you provide as much information as possible for prototyping and understand the full (or general) schema of your security export for comprehensive information conversion. From d4c67ddb274974732395251a421187aaf6738748 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 10 Jun 2024 11:27:03 -0400 Subject: [PATCH 02/71] Intro Signed-off-by: Charles Hu --- src/.vuepress/navbar.ts | 2 +- src/.vuepress/sidebar.ts | 2 +- src/README.md | 6 +- src/courses/mappers/02.md | 129 ++++++++------- src/courses/mappers/03.md | 118 ------------- src/courses/mappers/04.md | 301 ---------------------------------- src/courses/mappers/05.md | 36 ---- src/courses/mappers/06.md | 88 ---------- src/courses/mappers/07.md | 55 ------- src/courses/mappers/08.md | 222 ------------------------- src/courses/mappers/09.md | 269 ------------------------------ src/courses/mappers/10.md | 10 -- src/courses/mappers/11.md | 158 ------------------ src/courses/mappers/README.md | 24 ++- 14 files changed, 90 insertions(+), 1330 deletions(-) delete mode 100644 src/courses/mappers/03.md delete mode 100644 src/courses/mappers/04.md delete mode 100644 src/courses/mappers/05.md delete mode 100644 src/courses/mappers/06.md delete mode 100644 src/courses/mappers/07.md delete mode 100644 src/courses/mappers/08.md delete mode 100644 src/courses/mappers/09.md delete mode 100644 src/courses/mappers/10.md delete mode 100644 src/courses/mappers/11.md diff --git a/src/.vuepress/navbar.ts b/src/.vuepress/navbar.ts index a03b38ac8..ae269cd0f 100644 --- a/src/.vuepress/navbar.ts +++ b/src/.vuepress/navbar.ts @@ -11,7 +11,7 @@ export default navbar([ { text: "Advanced Security Automation Developer Class", link: "/courses/advanced/", icon: "creative" }, { text: "Security Guidance Developer Class", link: "/courses/guidance/", icon: "creative" }, { text: "InSpec Profile Development & Testing", link: "/courses/profile-dev-test", icon: "creative"}, - { text: "OHDF Mapper Development Class", link: "/courses/mapper/", icon: "creative"} + { text: "OHDF Mapper Development Class", link: "/courses/mappers/", icon: "creative"} ]}, { text: "Resources", icon: "book", diff --git a/src/.vuepress/sidebar.ts b/src/.vuepress/sidebar.ts index e10b0a459..cf8c179a1 100644 --- a/src/.vuepress/sidebar.ts +++ b/src/.vuepress/sidebar.ts @@ -42,7 +42,7 @@ export default sidebar({ { icon: "creative", text: "OHDF Mapper Development Class", - prefix: "courses/mapper/", + prefix: "courses/mappers/", children: "structure", collapsible: true }, diff --git a/src/README.md b/src/README.md index 53f3d5e6d..0e885bf8c 100644 --- a/src/README.md +++ b/src/README.md @@ -16,14 +16,14 @@ actions: link: /courses/advanced/ type: primary - text: Guidance Development - type: primary link: /courses/guidance/ - - text: InSpec Profile Updating & Development type: primary + - text: InSpec Profile Updating & Development link: /courses/profile-dev-test + type: primary - text: OHDF Mapper Development Class + link: /courses/mappers/ type: primary - link: /courses/mapper/ highlights: - header: What You Will Learn diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 96d6798a3..82c56a423 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -1,74 +1,77 @@ --- order: 2 next: 03.md -title: Background & Overview 1 +title: What Is an OHDF Mapper? author: Charles Hu --- -### HDF Schema +## What is OHDF? -The full generalized HDF schema is as follows: +OASIS Heimdall Data Format (OHDF) is a security data format used to normalize a plethora of generated security data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security validation profiles, controls, and results. +You can read more about OHDF [here](https://saf.mitre.org/framework/normalize). + +## What Is a Mapper? + +A mapper is a design pattern used to correlate (or map) items in two different objects with one another. Mappers are useful in that they allow us to connect items in objects that are nominally different but semantically the same. A result of this is that we can easily transform one object type into another through the use of mappings which define the direct relationship of items in each object type. + +Here are some scenarios which demonstrate some key aspects of mappers: + +::: details Transferring IDs +Say we have to transfer the credentials of an employee who is moving from Business A to Business B. The data formats the businesses use for IDs are as follows: +``` +// Business A +{Name, DoB, Age, Title} + +// Business B +{employee, employeeBirthday, employeeAge, jobTitle} +``` +How do we transfer John's credentials from Business A to Business B? ``` -{ - platform: { //required field - name //required field - release //required field - target_id - } - version //required field - statistics: { //required field - duration - } - profiles: [ //required field - 0: { - name //required field - version - sha256 //required field - title - maintainer - summary - license - copyright - copyright_email - supports //required field - attributes //required field - groups //required field - controls: [ //required field - 0: { - id //required field - title - desc - descriptions - impact //required field - refs //required field - tags //required field - code - source_location //required field - results: [ //required field - 0: { - status - code_desc //required field - message - run_time - start_time //required field - } - ] - } - ] - status - } - ] - passthrough: { - auxiliary_data: [ - 0: { - name - data - } - ] - raw - } -} +{Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} ``` -(Note: The documented schema is subject to change and not all required fields need to be populated; for the full schema and more information on the fields, refer to [saf.mitre.org/#/normalize](https://saf.mitre.org/#/normalize)) +What we can do is create a mapping which correlates the items from Business A's ID scheme to Business B's: +``` +{employee: Name, employeeBirthday: DoB, employeeAge: Age, jobTitle: Title} +``` + +With this, we can then develop a mapper which takes John's credentials from Business A and transforms it to Business B's format as so: +``` +{Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} + + || +\ / + \/ + +MAPPER + + || +\ / + \/ + +{employee: 'John Doe', employeeBirthday: 10-6-1992, employeeAge: 32, jobTitle: 'Security Technician'} +``` + +The important thing to note here is that mappers rely on underlying mappings which match semantically similar fields between two objects. These matches allow us to correctly convert each item in one object to the other. +::: + +::: details Translating a foreign language +Say we are given the job to translate the traditional Chinese sentence '我愛貓' into English. + +Without knowledge of the language, this is an impossible task. + +However, say we now also had a mapper which utilized the following mapping: +``` +{'愛': 'love', '我': 'I', '貓': 'cats'} +``` + +Now this task becomes much more easier. We can apply this mapper which will translate the sentence from '我愛貓' to 'I love cats' and vice versa. + +The important thing to note here is that mappers make translating between two objects trivial, which means that anyone can do it and we can automate mappers to perform object conversions for us. +::: + + +## What Is an OHDF Mapper? + + diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md deleted file mode 100644 index ae3780d05..000000000 --- a/src/courses/mappers/03.md +++ /dev/null @@ -1,118 +0,0 @@ ---- -order: 3 -next: 04.md -title: Background & Overview 2 -author: Charles Hu ---- - - -### HDF Schema Breakdown - -The HDF schema can be grouped into 3 sets of structures, with each structure being a subset of the previous structure. These groupings are: profiles, controls, and results. - -The profiles structure contains metadata on the scan target of the original security service export and on the run performed by the security tool. This provides a high-level overview of the scan service run and target which are both digestible and easily accessible to the user. A generalized format is as follows: - -``` -profiles: [ - 0: { - name //Name of profile, usually the original security service tool; should be unique - version //Version of security service tool - sha256 //Hash of HDF file; NOTE: AUTOMATICALLY GENERATED BY HDF CONVERTERS, DO NOT POPULATE - title //Title of security service scan; should be human readable - maintainer //Maintainer - summary //Summary of security service export - license //Copyright license - copyright //Copyright holder - copyright_email //Copyright holder's email - supports //Supported platform targets - attributes //Inputs/attributes used in scan - groups //Set of descriptions for the control groups - controls //Controls substructure (see below) - status //Status of profile (typically 'loaded') - } - ... //More items may exist if the security service produces multiple scan targets per export -] -``` - -Controls are security parameters used to prevent unauthorized access to sensitive information or infrastructure. In the case of HDF Converters, the controls structure is a collection of such controls tested for retroactively by an external security service to ensure that the target complies with vulnerability and weakness prevention standards. The controls structure is a subset of the profiles structure. A generalized format is as follows: - -``` -controls: [ - 0: { - id //ID of control; used for sorting, should be unique for each unique control - title //Title of control - desc //Description of the control - descriptions //Additional descriptions; usually 'check' and 'fix' text for control - impact //Security severity of control - refs //References to external control documentation - tags //Control tags; typically correlate to existing vulnerability/weakness database (e.g., NIST, CVE, CWE) - code //Control source code for code preservation - source_location //Location of control within source code - results //Results substructure (see below) - } - ... //More items may exist if there are multiple controls reported per profile -] -``` - -The results structure contains information on the results of specific tests ran by the security service on the scan target against a set of security controls. These results will always correlate to a certain control and will either report 'passed' or 'failed' to indicate the test status (other statuses exist but are rare), which cumulatively affect the compliance level of the scan target with the indicated control set. The results structure is a subset of the controls structure. A generalized structure is as follows: - -``` -results: [ - 0: { - status //Pass/fail status of test (other statuses exist but are rare) - code_desc //Test expectations as defined by control - message //Demonstration of expected and actual result of test to justify test status - run_time //Overall runtime of test - start_time //Starting time of test - } - ... //More items may exist if there are multiple results reported per control -] -``` - -These aforementioned structures cumulatively result in the following generalized structure which primarily defines the HDF: - -``` -//Data fields have been removed for the sake of demonstration -profiles: [ - 0: { - controls: [ - 0: { - results: [ - 0: { - }, - ... - ] - }, - ... - ] - }, - ... -] -``` - -There are additional structures in the HDF schema which are used for metadata/extraneous information storage. These exist alongside the profiles structure on the top level of the HDF schema. The general structure for the top level of the HDF schema is as follows: - -``` -{ - platform: { //Information on the platform handling the HDF file; usually 'Heimdall Tools' - name //Platform name - release //Platform version - target_id //Platform target ID - } - version //Platform version - statistics: { //Statistics relating to target scan run - duration //Duration of run - } - profiles //Profiles structure - passthrough: { //Extraneous information storage - auxiliary_data: [ //Storage for unused data from the sample file - 0: { - name //Name of auxiliary data source - data //Auxiliary data - } - ... //More items may exist if there are multiple auxiliary data sources available - ] - raw //Raw data dump of input security service export - } -} -``` diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md deleted file mode 100644 index 6c447ac4f..000000000 --- a/src/courses/mappers/04.md +++ /dev/null @@ -1,301 +0,0 @@ ---- -order: 4 -next: 05.md -title: Background & Overview 3 -author: Charles Hu ---- - -### HDF Schema Mapping Example Walkthrough - -The following is an example of a high-level mapping from the Twistlock file format to the HDF. The purpose of this demonstration is to give an easy, non-technical approach to generating a prototype for \*-to-HDF mappers that can be used as a guideline for the development of actual technical mappers for the HDF Converter. This process is generally recommended as the first step for the development of any mapper for the HDF Converter. - -(NOTE: The format used by your export may not match the one being used in this demonstration. The mappings used in this example are for demonstration purposes and should not be taken as a definitive resource; creative interpretation is necessary for the most accurate mapping according to the specifics of your security service export.) - -Given a sample Twistlock scan export (as seen below), our goal is to roughly identify and group data fields according to our 3 primary structures in HDF (profiles, controls, and results) and the non-applicable structure (passthrough). For profiles, we want to find metadata; for controls, we want to find general security control information; for results, we want to find specific security control testing information; and we can place everything else into passthrough. - -``` -//Sample Twistlock scan export -{ - "results": [ - { - "id": "sha256:111", - "name": "registry.io/test", - "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", - "distroRelease": "RHEL8", - "digest": "sha256:222", - "collections": [ - "All", - "TEST-COLLECTION" - ], - "packages": [ - { - "type": "os", - "name": "nss-util", - "version": "3.67.0-7.el8_5", - "licenses": [ - "MPLv2.0" - ] - } - ], - "vulnerabilities": [ - { - "id": "CVE-2021-43529", - "status": "affected", - "cvss": 9.8, - "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", - "severity": "critical", - "packageName": "nss-util", - "packageVersion": "3.67.0-7.el8_5", - "link": "https://access.redhat.com/security/cve/CVE-2021-43529", - "riskFactors": [ - "Remote execution", - "Attack complexity: low", - "Attack vector: network", - "Critical severity", - "Recent vulnerability" - ], - "impactedVersions": [ - "*" - ], - "publishedDate": "2021-12-01T00:00:00Z", - "discoveredDate": "2022-05-18T12:24:22Z", - "layerTime": "2022-05-16T23:12:25Z" - } - ], - "vulnerabilityDistribution": { - "critical": 1, - "high": 0, - "medium": 0, - "low": 0, - "total": 1 - }, - "vulnerabilityScanPassed": true, - "history": [ - { - "created": "2022-05-03T08:38:31Z" - }, - { - "created": "2022-05-03T08:39:27Z" - } - ], - "scanTime": "2022-05-18T12:24:32.855444532Z", - "scanID": "asdfghjkl" - } - ], - "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%333" -} -``` - -Thus, upon successive passes we can roughly outline what we expect each data field in the Twistlock scan export to correlate to in the HDF. We first want to identify metadata which will most likely belong in the profiles structure. Such data fields will primarily be related to the general security scan itself or be related to the target system that is being scanned, as seen below: - -``` -//Data values are removed for visual clarity -{ - "results": [ - { - "id", //Scan target metadata -> profiles - "name", // - "distro", // - "distroRelease", // - "digest", // - "collections", // - "packages": [], // - "vulnerabilities": [ - { - "id", - "status", - "cvss", - "description", - "severity", - "packageName", - "packageVersion", - "link", - "riskFactors": [], - "impactedVersions": [], - "publishedDate", - "discoveredDate", - "layerTime" - } - ], - "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles - "vulnerabilityScanPassed", // - "history": [], //Scan target package install history -> profiles - "scanTime", //Twistlock scan metadata -> profiles - "scanID" // - } - ], - "consoleURL" //Twistlock scan metadata -> profiles -} -``` - -Next, we want to roughly outline general security control information that correlates to our controls structure. For this, we want to look for information that provides a background for the tests performed by the security service. Usually, this strongly correlates to information that gives us a why, what, and how for the tests that are performed, as seen with the fields that are highlighted below: - -``` -//Data values are removed for visual clarity -{ - "results": [ - { - "id", //Scan target metadata -> profiles - "name", // - "distro", // - "distroRelease", // - "digest", // - "collections", // - "packages": [], // - "vulnerabilities": [ - { - "id", //ID of control tested against -> controls - "status", - "cvss", //CVSS severity score of control -> controls - "description", //Description of control -> controls - "severity", //Severity of control failure -> controls - "packageName", - "packageVersion", - "link", //Link to control documentation -> controls - "riskFactors": [], - "impactedVersions": [], - "publishedDate", //Control discovery date -> controls - "discoveredDate", - "layerTime" - } - ], - "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles - "vulnerabilityScanPassed", // - "history": [], //Scan target package install history -> profiles - "scanTime", //Twistlock scan metadata -> profiles - "scanID" // - } - ], - "consoleURL" //Twistlock scan metadata -> profiles -} -``` - -After that, we want to outline items that relate to specific instances of control tests ran against the scan target as part of the results structure. Usually, this strongly correlates to information that gives us a who, what, and when for the specific tests that are performed, as seen with the fields that are highlighted below: - -``` -//Data values are removed for visual clarity -{ - "results": [ - { - "id", //Scan target metadata -> profiles - "name", // - "distro", // - "distroRelease", // - "digest", // - "collections", // - "packages": [], // - "vulnerabilities": [ - { - "id", //ID of control tested against -> controls - "status", //Pass/fail result of the control test -> results - "cvss", //CVSS severity score of control -> controls - "description", //Description of control -> controls - "severity", //Severity of control failure -> controls - "packageName", //Package ran against control test -> results - "packageVersion", //Version of package ran against control test -> results - "link", //Link to control documentation -> controls - "riskFactors": [], //Risk factors associated with failing this specific control test -> results - "impactedVersions": [], //Vulnerable versions of package ran against control test -> results - "publishedDate", //Control discovery date -> controls - "discoveredDate", //Date this control result was discovered -> results - "layerTime" - } - ], - "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles - "vulnerabilityScanPassed", // - "history": [], //Scan target package install history -> profiles - "scanTime", //Twistlock scan metadata -> profiles - "scanID" // - } - ], - "consoleURL" //Twistlock scan metadata -> profiles -} -``` - -For fields that we cannot reasonably categorize or have no information about, we can instead just place them into the passthrough structure, as seen below: - -``` -//Data values are removed for visual clarity -{ - "results": [ - { - "id", //Scan target metadata -> profiles - "name", // - "distro", // - "distroRelease", // - "digest", // - "collections", // - "packages": [], // - "vulnerabilities": [ - { - "id", //ID of control tested against -> controls - "status", //Pass/fail result of the control test -> results - "cvss", //CVSS severity score of control -> controls - "description", //Description of control -> controls - "severity", //Severity of control failure -> controls - "packageName", //Package ran against control test -> results - "packageVersion", //Version of package ran against control test -> results - "link", //Link to control documentation -> controls - "riskFactors": [], //Risk factors associated with failing this specific control test -> results - "impactedVersions": [], //Vulnerable versions of package ran against control test -> results - "publishedDate", //Control discovery date -> controls - "discoveredDate", //Date this control result was discovered -> results - "layerTime" //Information on package install time; extraneous -> passthrough - } - ], - "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles - "vulnerabilityScanPassed", // - "history": [], //Scan target package install history -> profiles - "scanTime", //Twistlock scan metadata -> profiles - "scanID" // - } - ], - "consoleURL" //Twistlock scan metadata -> profiles -} -``` - -With this, we now have a general outline which roughly connects each data field in the Twistlock sample export to one of our structures in the HDF. In order to improve the accuracy of this mapping, we can now begin connecting [specific fields in the HDF schema](#fullschema) with the data fields in the sample export using our rough draft as a guide. - -If we cannot find a field in the HDF schema that fits with a certain field in the sample export per our original groupings, we can instead look to the other structures to see if they have applicable fields or place the field into the passthrough structure as a last resort. - -``` -//Data values are removed for visual clarity -{ - "results": [ - { - "id", //profiles -> passthrough.auxiliary_data.data - "name", //profiles -> profiles.name - "distro", //profiles -> passthrough.auxiliary_data.data - "distroRelease", //profiles -> passthrough.auxiliary_data.data - "digest", //profiles -> passthrough.auxiliary_data.data - "collections", //profiles -> profiles.title - "packages": [], //profiles -> passthrough.auxiliary_data.data - "vulnerabilities": [ - { - "id", //controls -> profiles.controls.id - "status", //results -> profiles.controls.results.status - "cvss", //controls -> profiles.controls.code - "description", //controls -> profiles.controls.desc - "severity", //controls -> profiles.controls.impact - "packageName", //results -> profiles.controls.results.code_desc - "packageVersion", //results -> profiles.controls.results.code_desc - "link", //controls -> profiles.controls.code - "riskFactors": [], //results -> profiles.controls.code - "impactedVersions": [], //results -> profiles.controls.results.code_desc - "publishedDate", //controls -> profiles.controls.code - "discoveredDate", //results -> profiles.controls.results.start_time - "layerTime" //passthrough -> profiles.controls.code - } - ], - "vulnerabilityDistribution": {}, //profiles -> profiles.summary - "vulnerabilityScanPassed", //profiles -> passthrough.auxiliary_data.data - "history": [], //profiles -> passthrough.auxiliary_data.data - "scanTime", //profiles -> passthrough.auxiliary_data.data - "scanID" //profiles -> passthrough.auxiliary_data.data - } - ], - "consoleURL" //profiles -> passthrough.auxiliary_data.data -} -``` - -With this, we now have a detailed high-level mapping for the conversion from an external file format to the HDF, which we can use for the [technical implementation of a \*-to-HDF mapper](#create). diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md deleted file mode 100644 index 7795fed4c..000000000 --- a/src/courses/mappers/05.md +++ /dev/null @@ -1,36 +0,0 @@ ---- -order: 5 -next: 06.md -title: Background & Overview 4 -author: Charles Hu ---- - -### HDF Converters Structure - -The following is a simplified depiction of the directory tree for the HDF Converter. Only noteworthy and potentially useful files and directories are included. It is not imperative to memorize the structure, but it is useful to familiarize yourself with it to better understand what exists where within the HDF Converter for future reference. - -``` -hdf-converters -+-- data -| +-- converters -| | +-- csv2json.ts -| | +-- xml2json.ts -+-- sample_jsons //Sample exports for mapper testing are located here -+-- src //*-to-HDF mappers are located here -| +-- converters-from-hdf //HDF-to-* mappers are located here -| | +-- reverse-any-base-converter.ts -| | +-- reverse-base-converter.ts -| +-- mappings //Non-HDF mappers are located here (e.g., CVE, CCI, NIST) -| +-- utils -| | +-- fingerprinting.ts -| | +-- global.ts -| +-- base-converter.ts -+-- test //Mapper tests are located here -| +-- mappers -| | +-- forward //*-to-HDF tests -| | +-- reverse //HDF-to-* tests -| | +-- utils.ts -+-- types //Explicit data typing for known export schemas -+-- index.ts -+-- package.json -``` diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md deleted file mode 100644 index d7276606a..000000000 --- a/src/courses/mappers/06.md +++ /dev/null @@ -1,88 +0,0 @@ ---- -order: 6 -next: 07.md -title: Background & Overview 5 -author: Charles Hu ---- - -### Base Converter Tools - -[//] # WIP - -The base-converter class is the underlying foundation which enables \*-to-HDF mapping in HDF Converters. It defines \*-to-HDF mappers and provides critical tools which allow for the construction of such mappers. All \*-to-HDF mappers inherit from this class and therefore have access to the tools that this class provides; it is thus imperative that you utilize these tools to their fullest potential to ease and simplify mapper development. The provided tools are as follows: - -- path: Denote JSON object path to go to - - - Use: - - ``` - path: PATH_AS_STRING - ``` - - - Example: - - ``` - //Attribute 'id' will be set as whatever JSON object attribute 'vulnerability.id' is - id: {path: 'vulnerability.id'} - ``` - -- transformer: Execute given code sequence; operates similar to an anonymous function - - - Use: - - ``` - transformer: (PARAMETERS): OUTPUT_TYPE => {CODE_TO_EXECUTE} - ``` - - - Example: - - ``` - //Attribute 'code' will be set as the returned stringified JSON object of input 'vulnerability' - code: { - transformer: (vulnerability: Record): string => { - return JSON.stringify(vulnerability, null, 2); - } - } - ``` - -- arrayTransformer: Execute given code sequence on a given array; primarily used when in an attribute that is an array of objects - - - Use: - - ``` - arrayTransformer: CODE_TO_EXECUTE - ``` - - - Example: - - ``` - //The function 'deduplicateId' will run against all items in the current array that the 'arrayTransformer' was called inside - arrayTransformer: deduplicateId - ``` - -- pathTransform: - - - Use: - - ``` - ``` - - - Example: - - ``` - ``` - -- key: Used by Base Converter to sort the an array of objects by - - - Use: - - ``` - key: KEY_AS_STRING - ``` - - - Example: - - ``` - //'id' is now considered the key by which this section will be sorted by - key: 'id' - ``` diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md deleted file mode 100644 index 9bd94a1e5..000000000 --- a/src/courses/mappers/07.md +++ /dev/null @@ -1,55 +0,0 @@ ---- -order: 7 -next: 08.md -title: Mapper Creation 1 -author: Charles Hu ---- - -## Mapper Creation - -### Environment Set Up - -Node.js (a runtime environment for Javascript) and Yarn (a package manager for Node.js) are external utilities which are utilized extensively within this guide. The following section details their installation process. - -Linux/Mac OS: - -1. Install [nvm](https://github.com/nvm-sh/nvm#install--update-script). - - - 1a. Use either of the following commands to install nvm: - - ``` - curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.1/install.sh | bash - ``` - ``` - wget -qO- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.1/install.sh | bash - ``` - - - 1b. Either restart the terminal or run the following commands to use nvm: - - ``` - export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")" - - [ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh" # This loads nvm - ``` - -2. Run the following command to install and use Node.js v16: - -``` -nvm install 16 -``` - -3. Install [Yarn](https://classic.yarnpkg.com/en/): - -``` -npm install --global yarn -``` - -Windows: - -1. Install [Node.js v16 via the installer](https://nodejs.org/en/download/). If v16 is not available from the page, use this [archive](https://nodejs.org/dist/v16.16.0/). - -2. Install [Yarn](https://classic.yarnpkg.com/en/): - -``` -npm install --global yarn -``` diff --git a/src/courses/mappers/08.md b/src/courses/mappers/08.md deleted file mode 100644 index fc99cb4aa..000000000 --- a/src/courses/mappers/08.md +++ /dev/null @@ -1,222 +0,0 @@ ---- -order: 8 -next: 09.md -title: Mapper Creation 2 -author: Charles Hu ---- - -### \*-to-HDF Creation Guide - -1. Fork/branch a development repository from the main [Heimdall2 GitHub repository](https://github.com/mitre/heimdall2). - - - SAF team developers have write access to the main repository and should [create a branch](https://docs.github.com/en/desktop/contributing-and-collaborating-using-github-desktop/making-changes-in-a-branch/managing-branches#creating-a-branch) on the primary development repository. Non-SAF team developers should instead [create a fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo#forking-a-repository) of the main repository and create a development branch there. - -2. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. - -3. Have a rough, high-level outline of how your export translates to the HDF. For an example of this process, refer to the [HDF Schema Mapping Example Walkthrough](#example) section. - -4. Set up for \*-to-HDF mapper development. - - - 4a. Install the necessary dependencies for Heimdall2. Under the heimdall2 directory, enter the following command in the terminal: - - ``` - yarn install - ``` - - - 4b. Create a blank TypeScript file under the src directory in hdf-converters. It should be named: - - ``` - {YOUR-EXPORT-NAME-HERE}-mapper.ts - ``` - - - 4c. Select the appropriate [mapper skeleton](#skeleton) for your export type. Place them in the file created in step 4b. Replace names (skeleton by default) as necessary. - - - 4d. Export your mapper class created in the previous steps by specifying its export in the index.ts file. Add the following line: - - ``` - export * from './src/{YOUR-EXPORT-NAME-HERE}-mapper'; - ``` - - - 4e. Create a new directory named {YOUR-EXPORT-NAME-HERE}_mapper under the sample_jsons directory in hdf-converters. Create another directory named sample_input_report in the directory you just made. The file structure should look like this: - - ``` - +-- sample_jsons - | +-- {YOUR-EXPORT-NAME-HERE}-mapper - | | +-- sample_input_report - ``` - - - 4f. Place your sample export under the sample_input_report directory. Your sample export should be genericized to avoid any leaking of sensitive information. The file structure should now look like this: - - ``` - +-- sample_jsons - | +-- {YOUR-EXPORT-NAME-HERE}-mapper - | | +-- sample_input_report - | | | +-- {YOUR-SAMPLE-EXPORT} - ``` - - - 4g. Create a blank TypeScript file under the test/mappers/forward directory in hdf-converters. It should be named: - - ``` - {YOUR-EXPORT-NAME-HERE}_mapper.spec.ts - ``` - - - 4h. Select the appropriate [mapper testing skeleton](#skeleton) for your export type. Place it in the file created in step 4g. Replace names (skeleton by default) as necessary. - -5. Add fingerprinting to identify your security service scan export. - - - 5a. Go to the file report_intake.ts under the heimdall2/apps/frontend/src/store directory. - - - 5b. Import your mapper file. You should be able to add the name of your mapper class to a pre-existing import statement pointing at hdf-converters as follows: - - ``` - import { - ASFFResults as ASFFResultsMapper, - BurpSuiteMapper, - ... - {YOUR-MAPPER-CLASS-HERE} - } from '@mitre/hdf-converters'; - ``` - - - 5c. Instantiate your mapper class in the convertToHdf switch block. Add the following lines: - - ``` - case '{YOUR-EXPORT-SERVICE-NAME-HERE}': - return new {YOUR-MAPPER-CLASS-HERE}(convertOptions.data).toHdf(); - ``` - - - 5d. Navigate to the file fingerprinting.ts in the src/utils directory in hdf-converters. Add keywords that are unique to your sample export to the fileTypeFingerprints variable. It should be formatted as follows: - - ``` - export const fileTypeFingerprints = { - asff: ['Findings', 'AwsAccountId', 'ProductArn'], - ... - {YOUR-EXPORT-SERVICE-NAME-HERE}: [{UNIQUE KEYWORDS AS STRINGS}] - }; - ``` - -6. Create the \*-to-HDF mapper. - - - 6a. Return to the {YOUR-EXPORT-NAME-HERE}-mapper.ts file. In the file, you should have a generic skeleton mapper picked according to your export type. - - - 6b. Certain security services produce exports which are not immediately usable by the skeleton mapper. In this case, pre-processing on the export and post-processing on the generated HDF file is necessary in order to ensure compatibility. - - - 6c. The skeleton mapper and [base-converter](#base) have been designed to provide the base functionality needed for \*-to-HDF mapper generation. For most developers, mapper creation will be limited to assigning objects from the export structure to correlating attributes in the mapper according to the HDF schema. - - - An example of this process is provided in the [\*-to-HDF Mapper Construction Example](#example2) section. - - - 6d. [Commit your changes](https://github.com/git-guides/git-commit) with the [signoff option](https://git-scm.com/docs/git-commit) and [push the changes](https://github.com/git-guides/git-push) to your development branch. This should queue up the Github Actions pipeline which includes a Netlify instance of Heimdall2 which you can use to test if your mapper is generating a HDF file correctly. - -7. Set up and use regression testing on your mapper. - - - 7a. Uncomment out the commented out lines in the {YOUR-SAMPLE-EXPORT}-hdf.json file created in step 4f. This will allow the regression tests to automatically generate a HDF output file whenever you run the tests. The commented out lines should look similar to the following: - - ``` - // fs.writeFileSync( - // 'sample_jsons/skeleton_mapper/skeleton-hdf.json', - // JSON.stringify(mapper.toHdf(), null, 2) - // ); - ``` - - - 7b. Using the terminal, cd into the hdf-converters directory and run the following command. This command will run your mapper against the sample export file in sample_jsons and test to see if the output is generated as expected. - - ``` - yarn run test --verbose --silent=false ./test/mappers/forward/{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts - ``` - - - 7c. Your tests should generate HDF output files for when --with-raw is not flagged (default behavior) and when it is flagged (denoted by -withraw in the filename). It will also compare the contents of these generated files with a temporary mapper instance created in the test itself. Review the test output to ensure that the tests are all passing and review the HDF output files to ensure that the contents of the mapping are being generated correctly. - - - 7d. Recomment out the lines from step 7b. - -8. Document your new mapper in the README for hdf-converters under the Supported Formats section. It should be formatted as follows: - -``` -{#}. [{YOUR-EXPORT-NAME-HERE}] - {MAPPER INPUT DESCRIPTION} -``` - -9. Commit your final changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, your mapper will be merged into the main development branch and [scheduled for release](https://github.com/mitre/heimdall2/wiki/How-to-create-a-Heimdall2-release) as an officially supported conversion format for the HDF Converters. - -10. Create a development branch against the [SAF CLI repository](https://github.com/mitre/saf) and create a draft pull request for your new branch. - -11. Set up for SAF CLI mapper integration. - - - 11a. In the package.json file, update the versions of @mitre/hdf-converters and @mitre/heimdall-lite to the [latest release of Heimdall2](https://github.com/mitre/heimdall2/releases). - - - 11b. In the src/commands/convert directory, create a blank TypeScript file. It should be named: - - ``` - {YOUR-EXPORT-NAME-HERE}2hdf.ts - ``` - - - 11c. In the test/sample_data directory, create a directory named {YOUR-EXPORT-NAME-HERE}. Underneath it, create a directory named sample_input_report. The file structure should now look like this: - - ``` - +-- sample_data - | +-- {YOUR-EXPORT-NAME-HERE} - | | +-- sample_input_report - ``` - - - 11d. Place your sample export under the sample_input_report directory. Your sample export should be genericized to avoid any leaking of sensitive information. Under the {YOUR-EXPORT-NAME-HERE} directory, place your output HDF files generated during the testing phase of step 7c. The file structure should now look like this: - - ``` - +-- sample_data - | +-- {YOUR-EXPORT-NAME-HERE} - | | +-- sample_input_report - | | | +-- {YOUR-SAMPLE-EXPORT} - | | +-- {YOUR-EXPORT-NAME-HERE}-hdf.json - | | +-- {YOUR-EXPORT-NAME-HERE}-hdf-withraw.json - ``` - - - 11e. In the test/commands/convert directory, create a blank TypeScript file. It should be named: - - ``` - {YOUR-EXPORT-NAME-HERE}2hdf.test.ts - ``` - -12. Integrate your mapper with the SAF CLI. - - - 12a. Insert the [skeleton](#skeleton) for integrating a HDF mapper with the SAF CLI. Replace names (skeleton by default) as necessary. - - - 12b. Insert the [skeleton](#skeleton) for a convert command test for the SAF CLI. Replace names (skeleton by default) as necessary. - - - 12c. Navigate to the index.ts file under the src/commands/convert directory. Import your mapper using the existing import block as follows: - - ``` - import { - ASFFResults, - ... - {YOUR-MAPPER-CLASS-HERE} - } from '@mitre/hdf-converters' - ``` - - - 12d. Under the switch block in the getFlagsForInputFile function, add your mapper class as it is defined in step 5d for fingerprinting for the generic convert command. If the convert command for your mapper has any additional flags beyond the standard --input and --output flags, return the entire flag block in the switch case. This is demonstrated as follows: - - ``` - switch (Convert.detectedType) { - ... - case {YOUR-EXPORT-SERVICE-NAME-HERE}: - return {YOUR-CLI-CONVERT-CLASS}.flags //Only add if special flags exist - ... - return {} - } - ``` - -13. Edit the README file to reflect your newly added conversion command under the To HDF section. It should be formatted as follows: - -``` -##### {YOUR-EXPORT-NAME-HERE} to HDF - -\``` -convert {YOUR-EXPORT-NAME-HERE}2hdf Translate a {YOUR-EXPORT-NAME-HERE} results {EXPORT-TYPE} into - a Heimdall Data Format JSON file - -OPTIONS - -i, --input=input Input {EXPORT-TYPE} File - -o, --output=output Output HDF JSON File - -w, --with-raw Include raw input file in HDF JSON file - -EXAMPLES - saf convert {YOUR-EXPORT-NAME-HERE}2hdf -i {INPUT-NAME} -o output-hdf-name.json -\``` -``` - -14. Commit your changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, merged, and [released](https://github.com/mitre/saf/wiki/Creating-a-Release-of-the-SAF-CLI), your mapper will be callable using the SAF CLI. diff --git a/src/courses/mappers/09.md b/src/courses/mappers/09.md deleted file mode 100644 index 0325c5914..000000000 --- a/src/courses/mappers/09.md +++ /dev/null @@ -1,269 +0,0 @@ ---- -order: 9 -next: 10.md -title: Mapper Creation 3 -author: Charles Hu ---- - -### Mapper Creation Skeletons - -- Skeleton for a general file-based \*-to-HDF mapper: - -``` -import {ExecJSON} from 'inspecjs'; -import _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - ILookupPath, - impactMapping, - MappedTransform -} from './base-converter'; - -const IMPACT_MAPPING: Map = new Map([ - ['critical', 0.9], - ['high', 0.7], - ['medium', 0.5], - ['low', 0.3] -]); - -export class SkeletonMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion, - target_id: null //Insert data - }, - version: HeimdallToolsVersion, - statistics: { - duration: null //Insert data - }, - profiles: [ - { - name: '', //Insert data - title: null, //Insert data - maintainer: null, //Insert data - summary: null, //Insert data - license: null, //Insert data - copyright: null, //Insert data - copyright_email: null, //Insert data - supports: [], //Insert data - attributes: [], //Insert data - depends: [], //Insert data - groups: [], //Insert data - status: 'loaded', //Insert data - controls: [ - { - key: 'id', - tags: {}, //Insert data - descriptions: [], //Insert data - refs: [], //Insert data - source_location: {}, //Insert data - title: null, //Insert data - id: '', //Insert data - desc: null, //Insert data - impact: 0, //Insert data - code: null, //Insert data - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, //Insert data - code_desc: '', //Insert data - message: null, //Insert data - run_time: null, //Insert data - start_time: '' //Insert data - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return { - auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed - ...(this.withRaw && {raw: data}) - }; - } - } - }; - constructor(exportJson: string, withRaw = false) { - super(JSON.parse(exportJson), true); - this.withRaw = withRaw - } -} -``` - -- Skeleton for a general test for a \*-to-HDF mapper in HDF Converters: - -``` -import fs from 'fs'; -import {SkeletonMapper} from '../../../src/skeleton-mapper'; -import {omitVersions} from '../../utils'; - -describe('skeleton_mapper', () => { - it('Successfully converts Skeleton targeted at a local/cloned repository data', () => { - const mapper = new SkeletonMapper( - fs.readFileSync( - 'sample_jsons/skeleton_mapper/sample_input_report/skeleton.json', - {encoding: 'utf-8'} - ) - ); - - // fs.writeFileSync( - // 'sample_jsons/skeleton_mapper/skeleton-hdf.json', - // JSON.stringify(mapper.toHdf(), null, 2) - // ); - - expect(omitVersions(mapper.toHdf())).toEqual( - omitVersions( - JSON.parse( - fs.readFileSync( - 'sample_jsons/skeleton_mapper/skeleton-hdf.json', - { - encoding: 'utf-8' - } - ) - ) - ) - ); - }); -}); - -describe('skeleton_mapper_withraw', () => { - it('Successfully converts withraw flagged Skeleton targeted at a local/cloned repository data', () => { - const mapper = new SkeletonMapper( - fs.readFileSync( - 'sample_jsons/skeleton_mapper/sample_input_report/skeleton.json', - {encoding: 'utf-8'} - ), - true - ); - - // fs.writeFileSync( - // 'sample_jsons/skeleton_mapper/skeleton-hdf-withraw.json', - // JSON.stringify(mapper.toHdf(), null, 2) - // ); - - expect(omitVersions(mapper.toHdf())).toEqual( - omitVersions( - JSON.parse( - fs.readFileSync( - 'sample_jsons/skeleton_mapper/skeleton-hdf-withraw.json', - { - encoding: 'utf-8' - } - ) - ) - ) - ); - }); -}); -``` - -- Skeleton for SAF CLI mapper conversion integration: - -``` -import {Command, Flags} from '@oclif/core' -import fs from 'fs' -import {SkeletonMapper as Mapper} from '@mitre/hdf-converters' -import {checkSuffix} from '../../utils/global' - -export default class Skeleton2HDF extends Command { - static usage = 'convert skeleton2hdf -i -o ' - - static description = 'Translate a Skeleton output file into an HDF results set' - - static examples = ['saf convert skeleton2hdf -i skeleton.json -o output-hdf-name.json'] - - static flags = { - help: Flags.help({char: 'h'}), - input: Flags.string({char: 'i', required: true, description: 'Input Skeleton file'}), - output: Flags.string({char: 'o', required: true, description: 'Output HDF file'}), - 'with-raw': Flags.boolean({char: 'w', required: false}), - } - - async run() { - const {flags} = await this.parse(Skeleton2HDF) - const input = fs.readFileSync(flags.input, 'utf8') - - const converter = new Mapper(input, flags.['with-raw']) - fs.writeFileSync(checkSuffix(flags.output), JSON.stringify(converter.toHdf())) - } -} -``` -- Skeleton for a convert command test for the SAF CLI: - -``` -import {expect, test} from '@oclif/test' -import tmp from 'tmp' -import path from 'path' -import fs from 'fs' -import {omitHDFChangingFields} from '../utils' - -describe('Test skeleton', () => { - const tmpobj = tmp.dirSync({unsafeCleanup: true}) - - test - .stdout() - .command([ - 'convert skeleton2hdf', - '-i', - path.resolve( - './test/sample_data/skeleton/sample_input_report/skeleton_sample.json', - ), - '-o', - `${tmpobj.name}/skeletontest.json`, - ]) - .it('hdf-converter output test', () => { - const converted = JSON.parse( - fs.readFileSync(`${tmpobj.name}/skeletontest.json`, 'utf8'), - ) - const sample = JSON.parse( - fs.readFileSync( - path.resolve('./test/sample_data/skeleton/skeleton-hdf.json'), - 'utf8', - ), - ) - expect(omitHDFChangingFields(converted)).to.eql( - omitHDFChangingFields(sample), - ) - }) -}) - -describe('Test skeleton withraw flag', () => { - const tmpobj = tmp.dirSync({unsafeCleanup: true}) - - test - .stdout() - .command([ - 'convert skeleton2hdf', - '-i', - path.resolve( - './test/sample_data/skeleton/sample_input_report/skeleton_sample.json', - ), - '-o', - `${tmpobj.name}/skeletontest.json`, - '-w', - ]) - .it('hdf-converter withraw output test', () => { - const converted = JSON.parse( - fs.readFileSync(`${tmpobj.name}/skeletontest.json`, 'utf8'), - ) - const sample = JSON.parse( - fs.readFileSync( - path.resolve('./test/sample_data/skeleton/skeleton-hdf-withraw.json'), - 'utf8', - ), - ) - expect(omitHDFChangingFields(converted)).to.eql( - omitHDFChangingFields(sample), - ) - }) -}) -``` diff --git a/src/courses/mappers/10.md b/src/courses/mappers/10.md deleted file mode 100644 index c4b78978f..000000000 --- a/src/courses/mappers/10.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -order: 10 -next: 11.md -title: Mapper Creation 4 -author: Charles Hu ---- - -### Best Practices - -[//] # WIP diff --git a/src/courses/mappers/11.md b/src/courses/mappers/11.md deleted file mode 100644 index 2492dc93f..000000000 --- a/src/courses/mappers/11.md +++ /dev/null @@ -1,158 +0,0 @@ ---- -order: 11 -next: 12.md -title: Mapper Creation 5 -author: Charles Hu ---- - -### \*-to-HDF Mapper Construction Example - -The following is an example of a implemented HDF mapper for Twistlock created using a [high-level Twistlock-to-HDF mapping](#example) and [tools from base-converter](#base). - -``` -const IMPACT_MAPPING: Map = new Map([ - ['critical', 0.9], - ['important', 0.9], - ['high', 0.7], - ['medium', 0.5], - ['moderate', 0.5], - ['low', 0.3] -]); - -export class TwistlockMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion, - target_id: {path: 'results[0].name'} - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - path: 'results', - name: 'Twistlock Scan', - title: { - transformer: (data: Record): string => { - const projectArr = _.has(data, 'collections') - ? _.get(data, 'collections') - : 'N/A'; - const projectName = Array.isArray(projectArr) - ? projectArr.join(' / ') - : projectArr; - return `Twistlock Project: ${projectName}`; - } - }, - summary: { - transformer: (data: Record): string => { - const vulnerabilityTotal = _.has(data, 'vulnerabilityDistribution') - ? `${JSON.stringify( - _.get(data, 'vulnerabilityDistribution.total') - )}` - : 'N/A'; - const complianceTotal = _.has(data, 'complianceDistribution') - ? `${JSON.stringify(_.get(data, 'complianceDistribution.total'))}` - : 'N/A'; - return `Package Vulnerability Summary: ${vulnerabilityTotal} Application Compliance Issue Total: ${complianceTotal}`; - } - }, - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - path: 'vulnerabilities', - key: 'id', - tags: { - nist: ['SI-2', 'RA-5'], - cci: ['CCI-002605', 'CCI-001643'], - cveid: {path: 'id'} - }, - refs: [], - source_location: {}, - title: {path: 'id'}, - id: {path: 'id'}, - desc: {path: 'description'}, - impact: { - path: 'severity', - transformer: impactMapping(IMPACT_MAPPING) - }, - code: { - transformer: (vulnerability: Record): string => { - return JSON.stringify(vulnerability, null, 2); - } - }, - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, - code_desc: { - transformer: (data: Record): string => { - const packageName = _.has(data, 'packageName') - ? `${JSON.stringify(_.get(data, 'packageName'))}` - : 'N/A'; - const impactedVersions = _.has(data, 'impactedVersions') - ? `${JSON.stringify(_.get(data, 'impactedVersions'))}` - : 'N/A'; - return `Package ${packageName} should be updated to latest version above impacted versions ${impactedVersions}`; - } - }, - message: { - transformer: (data: Record): string => { - const packageName = _.has(data, 'packageName') - ? `${JSON.stringify(_.get(data, 'packageName'))}` - : 'N/A'; - const packageVersion = _.has(data, 'packageVersion') - ? `${JSON.stringify(_.get(data, 'packageVersion'))}` - : 'N/A'; - return `Expected latest version of ${packageName}\nDetected vulnerable version ${packageVersion} of ${packageName}`; - } - }, - start_time: {path: 'discoveredDate'} - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - let resultsData = _.get(data, 'results'); - if (Array.isArray(resultsData)) { - resultsData = resultsData.map((result: Record) => - _.omit(result, [ - 'name', - 'collections', - 'complianceDistribution', - 'vulnerabilities', - 'vulnerabilityDistribution' - ]) - ); - } - return { - auxiliary_data: [ - { - name: 'Twistlock', - data: { - results: resultsData, - consoleURL: _.get(data, 'consoleURL') - } - } - ], - ...(this.withRaw && {raw: data}) - }; - } - } - }; - constructor(twistlockJson: string, withRaw = false) { - super(JSON.parse(twistlockJson), true); - this.withRaw = withRaw; - } -} -``` diff --git a/src/courses/mappers/README.md b/src/courses/mappers/README.md index 257c08ec7..58f9d6f81 100644 --- a/src/courses/mappers/README.md +++ b/src/courses/mappers/README.md @@ -1,14 +1,28 @@ --- order: 1 next: 02.md -title: Introduction +title: OHDF Mapper Development Class author: Charles Hu --- -## Introduction +## Overview -HDF Converters is a custom data normalization tool for transforming exported data from various security tool formats into the [Heimdall Data Format (HDF)](https://saf.mitre.org/#/normalize). It is currently integrated into [Heimdall2](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance and testing within an automated build pipeline. +The purpose of this class is to provide you with the foundational knowledge needed to create data format mappers targeted against the [OASIS Heimdall Data Format (OHDF)](https://saf.mitre.org/framework/normalize). In the following course, you will be taught the art and science of schema translation through a combination of both guided walkthroughs and hands-on demonstrations. -Mappers are frameworks that allow the underlying conversion infrastructure to correlate certain objects or values from one overarching object or file to another overarching object or file. In the case of HDF Converters, these mappers allow for the conversion of some security service formats to HDF (\*-to-HDF) and vice-versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. +### Objectives -The process for creating a mapper for HDF Converters is detailed below. In order to ensure that the created mapper produces a HDF file that is both accurate and detailed, it is important that you provide as much information as possible for prototyping and understand the full (or general) schema of your security export for comprehensive information conversion. +By the end of this class, you should be able to achieve the following objectives: + +- Understand the OHDF schema and its components. +- Be able to identify and break down key components of any given security data export. +- Correlate schema fields of your security data export to schema fields in OHDF. +- Create a *-to-OHDF mapper. +- Create a OHDF-to-* mapper. +- Integrate your mapper with the [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) library. + + +## Mapper Examples + +This course will use examples and code derived from previously developed OHDF mappers which can be [found here](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters). + +You are encouraged to regularly refer back to this GitHub repository to check your understanding of OHDF mappers and see how mappers are actually developed and implemented in a production environment. From cb1b7b5007db4e61e1f3361fc9b6c7e744506b6c Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 10 Jun 2024 11:46:30 -0400 Subject: [PATCH 03/71] Background Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 82c56a423..f2b36ddbd 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -1,7 +1,7 @@ --- order: 2 next: 03.md -title: What Is an OHDF Mapper? +title: OHDF Background author: Charles Hu --- @@ -74,4 +74,8 @@ The important thing to note here is that mappers make translating between two ob ## What Is an OHDF Mapper? +An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security data format to another overarching security data format. In the case of the SAF tool suite, these mappers allow for the conversion of some given security service format to HDF (\*-to-HDF) and vice-versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. +## What is OHDF Converters? + +OHDF Converters is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated into [Heimdall2](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification within an automated build pipeline. From 073271bd0dfe18b53ebdc44bd37f232e473f1295 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 10 Jun 2024 12:46:54 -0400 Subject: [PATCH 04/71] OHDF overview Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 2 +- src/courses/mappers/03.md | 22 ++++++++++++++++++++++ 2 files changed, 23 insertions(+), 1 deletion(-) create mode 100644 src/courses/mappers/03.md diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index f2b36ddbd..7970f5ad5 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -74,7 +74,7 @@ The important thing to note here is that mappers make translating between two ob ## What Is an OHDF Mapper? -An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security data format to another overarching security data format. In the case of the SAF tool suite, these mappers allow for the conversion of some given security service format to HDF (\*-to-HDF) and vice-versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. +An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security data format to another overarching security data format. In the case of the SAF tool suite, these mappers allow for the conversion of some given security service format to HDF (\*-to-HDF) and vice versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. ## What is OHDF Converters? diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md new file mode 100644 index 000000000..0196bb619 --- /dev/null +++ b/src/courses/mappers/03.md @@ -0,0 +1,22 @@ +--- +order: 3 +next: 04.md +title: Understanding the OHDF Schema +author: Charles Hu +--- + +## An Overview of the OHDF Schema + +The OHDF schema is designed to provide a simple, structured, and hierarchal view of security validation results. Any file or object that implements the schema can be broken down into a hierarchy of three structures. These structures are: + +1) **Profiles**: This structure contains metadata on the scan target of the original security service export and on the run performed by the security tool. Profiles provide a high-level overview of the security service scan and the targeted system, which are formated in a manner which is digestible and immediately accessible to the assessor. + +2) **Controls**: Controls are security standards that are used to prevent, mitigate, and address various security risks to sensitive information and infrastructure. In the case of OHDF, the controls structure is a collection of controls tested for by an external security service to ensure that the target complies with vulnerability and weakness prevention standards. Any given profile contains any number of controls which were tested against the target system during the original security service analysis. + +3) **Results**: The results structure contains information on the results of specific tests ran by the security service on the scan target against a security control. These results will always correlate to a certain control and will either report 'passed' or 'failed' to indicate the test status (other statuses exist but are rare) which cumulatively influence the determined compliance level of the scan target for some set of controls. Any given control contains any number of results which reflect the implemented tests to check if the target system is actually compliant with the control. + +## Breaking Down the Formal OHDF Schema + +The following section contains a breakdown of a streamlined version of the OHDF schema. For the full and up-to-date version, see [here](https://saf.mitre.org/framework/normalize/ohdf-schema). + + From 51b7dc5013dbda53923750b6ec6d289a8790b9b6 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 10 Jun 2024 15:36:53 -0400 Subject: [PATCH 05/71] Schema break down Signed-off-by: Charles Hu --- src/courses/mappers/03.md | 179 +++++++++++++++++++++++++++++++++- src/courses/mappers/README.md | 1 - 2 files changed, 178 insertions(+), 2 deletions(-) diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index 0196bb619..fbe2760a1 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -13,10 +13,187 @@ The OHDF schema is designed to provide a simple, structured, and hierarchal view 2) **Controls**: Controls are security standards that are used to prevent, mitigate, and address various security risks to sensitive information and infrastructure. In the case of OHDF, the controls structure is a collection of controls tested for by an external security service to ensure that the target complies with vulnerability and weakness prevention standards. Any given profile contains any number of controls which were tested against the target system during the original security service analysis. -3) **Results**: The results structure contains information on the results of specific tests ran by the security service on the scan target against a security control. These results will always correlate to a certain control and will either report 'passed' or 'failed' to indicate the test status (other statuses exist but are rare) which cumulatively influence the determined compliance level of the scan target for some set of controls. Any given control contains any number of results which reflect the implemented tests to check if the target system is actually compliant with the control. +3) **Results**: The results structure contains information on the results of specific tests ran by the security service on the scan target against a security control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses exist but are rare) which cumulatively influence the determined compliance level of the scan target for some set of controls. Any given control contains any number of results which reflect the implemented tests to check if the target system is actually compliant with the control. ## Breaking Down the Formal OHDF Schema +::: note Full OHDF Schema The following section contains a breakdown of a streamlined version of the OHDF schema. For the full and up-to-date version, see [here](https://saf.mitre.org/framework/normalize/ohdf-schema). +::: +We can break down the formal OHDF schema in the same manner as before by observing each structure in the hierarchy from a top-down view. +1) **Profiles**: +``` +profiles: [ + 0: { + name // Name of profile, usually the original security service tool; should be unique + version // Version of security service tool + sha256 // Checksum of the profile; NOTE: AUTOMATICALLY GENERATED BY HDF CONVERTERS, DO NOT POPULATE + title // Title of security service scan; should be human readable + maintainer // Maintainer + summary // Summary of security service export (e.g., the STIG header) + license // Copyright license + copyright // Copyright holder + copyright_email // Copyright holder's email + supports // Supported platform targets + attributes // Inputs/attributes used in scan + groups // Set of descriptions for the control groups (e.g., control IDs) + controls // Controls substructure (see below) + status // Status of profile (typically 'loaded') + } + ... // More items may exist if the security service produces multiple profiles per export +] +``` + +2) **Controls**: + +``` +controls: [ + 0: { + id // ID of control; used for sorting, should be unique for each unique control + title // Title of control + desc // Description of the control + descriptions // Additional descriptions; usually 'check' and 'fix' text for control + impact // Security severity of control + refs // References to external control documentation + tags // Control tags; typically correlate to existing vulnerability/weakness database (e.g., NIST, CVE, CWE) + code // Control source code for code preservation + source_location // Location of control within source code + results // Results substructure (see below) + } + ... // More items may exist if there are multiple controls reported per profile +] +``` + +3) **Results**: + +``` +results: [ + 0: { + status // Pass/fail status of test (other statuses exist but are rare) + code_desc // Test expectations as defined by control + message // Demonstration of expected and actual result of test to justify test status + run_time // Overall runtime of test + start_time // Starting time of test + } + ... // More items may exist if there are multiple results tested per control +] +``` + +These aforementioned structures cumulatively result in the following generalized structure which primarily defines OHDF: + +``` +// Data fields have been removed for the sake of demonstration +profiles: [ + 0: { + controls: [ + 0: { + results: [ + 0: { + }, + ... + ] + }, + ... + ] + }, + ... +] +``` + +There are additional structures in the OHDF schema which are used for metadata/extraneous information storage. These exist alongside the profiles structure on the top level of the HDF schema. The general structure for the top level of the HDF schema is as follows: + +``` +{ + platform: { // Information on the platform producing the export + name // Name of platform export was run on + release // Platform version + target_id // Platform target ID (i.e., further identifying information on platform) + } + version // Platform version + statistics: { // Statistics relating to target scan run + duration // Duration of run + } + profiles // Profiles structure + passthrough: { // Extraneous information storage + auxiliary_data: [ // Storage for unused data from the sample file + 0: { + name // Name of auxiliary data source + data // Auxiliary data + } + ... // More items may exist if there are multiple auxiliary data sources available + ] + raw // Raw data dump of input security service export + } +} +``` + +## The OHDF Schema + +The streamlined OHDF schema is as follows: + +::: note +::: + +``` +{ + platform: { // required field + name // required field + release // required field + target_id + } + version // required field + statistics: { // required field + duration + } + profiles: [ // required field + 0: { + name // required field + version + sha256 // required field + title + maintainer + summary + license + copyright + copyright_email + supports // required field + attributes // required field + groups // required field + controls: [ // required field + 0: { + id // required field + title + desc + descriptions + impact // required field + refs // required field + tags // required field + code + source_location // required field + results: [ // required field + 0: { + status + code_desc // required field + message + run_time + start_time // required field + } + ] + } + ] + status + } + ] + passthrough: { + auxiliary_data: [ + 0: { + name + data + } + ] + raw + } +} +``` diff --git a/src/courses/mappers/README.md b/src/courses/mappers/README.md index 58f9d6f81..843a4d99e 100644 --- a/src/courses/mappers/README.md +++ b/src/courses/mappers/README.md @@ -17,7 +17,6 @@ By the end of this class, you should be able to achieve the following objectives - Be able to identify and break down key components of any given security data export. - Correlate schema fields of your security data export to schema fields in OHDF. - Create a *-to-OHDF mapper. -- Create a OHDF-to-* mapper. - Integrate your mapper with the [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) library. From 0a829d8b938d4d7c872e394b2bbfe9455ce3840e Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 10 Jun 2024 15:39:49 -0400 Subject: [PATCH 06/71] Minor edit Signed-off-by: Charles Hu --- src/courses/mappers/03.md | 4 ---- 1 file changed, 4 deletions(-) diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index fbe2760a1..eb2977b99 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -132,10 +132,6 @@ There are additional structures in the OHDF schema which are used for metadata/e ## The OHDF Schema The streamlined OHDF schema is as follows: - -::: note -::: - ``` { platform: { // required field From ae998b5d2b86aa4ae5a6f900fb1a2297321c983e Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 10 Jun 2024 16:01:18 -0400 Subject: [PATCH 07/71] Outlining, clean up pages Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 16 +++++++++++++++- src/courses/mappers/03.md | 2 +- src/courses/mappers/04.md | 6 ++++++ src/courses/mappers/05.md | 6 ++++++ src/courses/mappers/06.md | 6 ++++++ src/courses/mappers/07.md | 5 +++++ 6 files changed, 39 insertions(+), 2 deletions(-) create mode 100644 src/courses/mappers/04.md create mode 100644 src/courses/mappers/05.md create mode 100644 src/courses/mappers/06.md create mode 100644 src/courses/mappers/07.md diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 7970f5ad5..a742923b6 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -7,10 +7,24 @@ author: Charles Hu ## What is OHDF? -OASIS Heimdall Data Format (OHDF) is a security data format used to normalize a plethora of generated security data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security validation profiles, controls, and results. +OASIS Heimdall Data Format (OHDF) is a security data format used to normalize generated security data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security validation profiles, controls, and results. You can read more about OHDF [here](https://saf.mitre.org/framework/normalize). +### Why OHDF? + +- Many security tools do not provide context to relevant compliance standards for comparison across security tools.​ +- Security tools typically generate data in unique formats that require multiple dashboards and utilities to process.​ +- OHDF reduces the time it takes to process security assessments, data in disparate locations and inconsistent semantics of a data element between formats.​ + +- OHDF enables: + + - Consistent integration, aggregation, and analysis of security data from all available sources.​ + - Preserving data integrity with original source data. + - Maximizing interoperability and data sharing.​ + - Facilitating the transformation and transport of data between security/management processes or technologies.​ + - Allowing for the mapping and enrichment of security data to relevant compliance standards (GDPR, NIST SP 800-53, PCI-DSS, etc.). + ## What Is a Mapper? A mapper is a design pattern used to correlate (or map) items in two different objects with one another. Mappers are useful in that they allow us to connect items in objects that are nominally different but semantically the same. A result of this is that we can easily transform one object type into another through the use of mappings which define the direct relationship of items in each object type. diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index eb2977b99..3ece5b4b7 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -131,7 +131,7 @@ There are additional structures in the OHDF schema which are used for metadata/e ## The OHDF Schema -The streamlined OHDF schema is as follows: +The OHDF schema is as follows: ``` { platform: { // required field diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md new file mode 100644 index 000000000..85fc6e336 --- /dev/null +++ b/src/courses/mappers/04.md @@ -0,0 +1,6 @@ +--- +order: 4 +next: 05.md +title: Understanding InspecJS +author: Charles Hu +--- diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md new file mode 100644 index 000000000..a79de8a98 --- /dev/null +++ b/src/courses/mappers/05.md @@ -0,0 +1,6 @@ +--- +order: 5 +next: 06.md +title: Understanding OHDF Converters +author: Charles Hu +--- diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md new file mode 100644 index 000000000..f1983cdc5 --- /dev/null +++ b/src/courses/mappers/06.md @@ -0,0 +1,6 @@ +--- +order: 6 +next: 07.md +title: The Art of Mappers +author: Charles Hu +--- \ No newline at end of file diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md new file mode 100644 index 000000000..0e2722780 --- /dev/null +++ b/src/courses/mappers/07.md @@ -0,0 +1,5 @@ +--- +order: 7 +title: Mapper Creation Demonstration +author: Charles Hu +--- From a2530ce8df7764f57c8f28d619352a7da47de672 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Tue, 11 Jun 2024 08:53:29 -0400 Subject: [PATCH 08/71] Minor changes Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 4 ---- src/courses/mappers/05.md | 4 ++++ src/courses/mappers/06.md | 2 +- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index a742923b6..6fc1556a6 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -89,7 +89,3 @@ The important thing to note here is that mappers make translating between two ob ## What Is an OHDF Mapper? An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security data format to another overarching security data format. In the case of the SAF tool suite, these mappers allow for the conversion of some given security service format to HDF (\*-to-HDF) and vice versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. - -## What is OHDF Converters? - -OHDF Converters is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated into [Heimdall2](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification within an automated build pipeline. diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index a79de8a98..e6529b0bf 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -4,3 +4,7 @@ next: 06.md title: Understanding OHDF Converters author: Charles Hu --- + +## What is OHDF Converters? + +OHDF Converters is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated into [Heimdall2](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification within an automated build pipeline. diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index f1983cdc5..11626ef0c 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -1,6 +1,6 @@ --- order: 6 next: 07.md -title: The Art of Mappers +title: The Art of Mapper Making author: Charles Hu --- \ No newline at end of file From ac90ec4026b111d7659d9b684167094e2583c896 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Tue, 11 Jun 2024 12:17:58 -0400 Subject: [PATCH 09/71] OHDF section Signed-off-by: Charles Hu --- src/courses/mappers/03.md | 2 +- src/courses/mappers/04.md | 109 +++++++++++++++++++++++++++++++++++++- src/courses/mappers/05.md | 4 +- src/courses/mappers/06.md | 52 +++++++++++++++++- src/courses/mappers/07.md | 4 +- 5 files changed, 163 insertions(+), 8 deletions(-) diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index 3ece5b4b7..035524526 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -131,7 +131,7 @@ There are additional structures in the OHDF schema which are used for metadata/e ## The OHDF Schema -The OHDF schema is as follows: +The final OHDF schema is as follows: ``` { platform: { // required field diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 85fc6e336..e744d5ab3 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -1,6 +1,113 @@ --- order: 4 next: 05.md -title: Understanding InspecJS +title: Understanding InspecJS & OHDF Converters author: Charles Hu --- + +## What is InspecJS? + + + +## What is OHDF Converters? + +OHDF Converters is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated into [Heimdall2](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification within an automated build pipeline. + +### Features + +- Leverages OHDF mappers to transform security data formats to and from OHDF. +- Special keyword functions provided by the base-converter class. +- Fingerprinting services for automatic data format identification. + +### Keywords + +base-converter is an underlying class which enables \*-to-HDF mapping in OHDF Converters. It defines \*-to-HDF mappers and provides critical tools in the form of keywords which allow for the construction of such mappers. All \*-to-HDF mappers inherit from this class and therefore have access to the keywords that this class provides. You should aim to utilize these keywords to their fullest potential to ease and simplify mapper development. The provided tools are as follows: + +- `path`: Define JSON object path to go to. Paths are found recursively. + - Use: + ``` + path: PATH_AS_STRING + ``` + - Example: + ``` + // Attribute 'id' will be set as whatever JSON object attribute 'vulnerability.id' is + id: {path: 'vulnerability.id'} + ``` + +- `transformer`: Execute given code sequence; operates similar to an anonymous function. + - Use: + ``` + transformer: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} + ``` + - Example: + ``` + // Attribute 'code' will be set as the returned stringified JSON object of input 'vulnerability' + code: { + transformer: (vulnerability: Record): string => { + return JSON.stringify(vulnerability, null, 2); + } + } + ``` + +- `arrayTransformer`: Execute given code sequence on a given array; primarily used when in an attribute that is an array of objects. + - Use: + ``` + arrayTransformer: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} + ``` + - Example: + ``` + // The function 'deduplicateId' will run against all items in the current array that the 'arrayTransformer' was called inside + arrayTransformer: deduplicateId + ``` + +- `pathTransform`: Converts the JSON object path structure. + - Use: + ``` + pathTransform: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} + ``` + - Example: + ``` + // Returns the JSON path if it is an array, otherwise returns an empty array + pathTransform: (value) => (Array.isArray(value) ? value : []), + ``` + +- `key`: Used by base-converter to sort an array of objects by + - Use: + ``` + key: KEY_AS_STRING + ``` + - Example: + ``` + // 'id' is now the key by which this array will be sorted by + key: 'id' + ``` + +### Directory Structure + +The following is a simplified depiction of the directory tree for the HDF Converter. Only noteworthy and potentially useful files and directories are included. It is not imperative to memorize the structure, but it is useful to familiarize yourself with it to better understand what exists where within the HDF Converter for future reference. + +``` +hdf-converters ++-- data +| +-- converters +| | +-- csv2json.ts +| | +-- xml2json.ts ++-- sample_jsons //Sample exports for mapper testing are located here ++-- src //*-to-HDF mappers are located here +| +-- converters-from-hdf //HDF-to-* mappers are located here +| | +-- reverse-any-base-converter.ts +| | +-- reverse-base-converter.ts +| +-- mappings //Non-HDF mappers are located here (e.g., CVE, CCI, NIST) +| +-- utils +| | +-- fingerprinting.ts +| | +-- global.ts +| +-- base-converter.ts ++-- test //Mapper tests are located here +| +-- mappers +| | +-- forward //*-to-HDF tests +| | +-- reverse //HDF-to-* tests +| | +-- utils.ts ++-- types //Explicit data typing for known export schemas ++-- index.ts ++-- package.json +``` diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index e6529b0bf..ed3a78824 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -1,10 +1,8 @@ --- order: 5 next: 06.md -title: Understanding OHDF Converters +title: The Art of Mapper Making author: Charles Hu --- -## What is OHDF Converters? -OHDF Converters is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated into [Heimdall2](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification within an automated build pipeline. diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index 11626ef0c..0dbcef495 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -1,6 +1,54 @@ --- order: 6 next: 07.md -title: The Art of Mapper Making +title: Mapper Creation Demonstration author: Charles Hu ---- \ No newline at end of file +--- + +## Environment Set Up + +Node.js (a runtime environment for Javascript) and Yarn (a package manager for Node.js) are external utilities which are utilized extensively within this guide. The following section details their installation process. + +Linux/Mac OS: + +1. Install [nvm](https://github.com/nvm-sh/nvm#install--update-script). + + - 1a. Use either of the following commands to install nvm: + ``` + curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash + ``` + ``` + wget -qO- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash + ``` + + - 1b. Either restart the terminal or run the following commands to use nvm: + ``` + export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")" + [ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh" # This loads nvm + ``` + +2. Run the following command to install and use Node.js v18: +``` +nvm install 18 +``` + +3. Install [Yarn](https://yarnpkg.com/getting-started/install) + +Windows: + +1. Install [Node.js v18 via the installer](https://nodejs.org/en/download/). + +2. Install [Yarn](https://yarnpkg.com/getting-started/install): + +## Repository Set Up + +1. Fork/branch a development repository from the main [Heimdall2 GitHub repository](https://github.com/mitre/heimdall2). + + - SAF team developers have write access to the main repository and should [create a branch](https://docs.github.com/en/desktop/contributing-and-collaborating-using-github-desktop/making-changes-in-a-branch/managing-branches#creating-a-branch) on the primary development repository. Non-SAF team developers should instead [create a fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo#forking-a-repository) of the main repository and create a development branch there. + +2. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. + +3. Install the necessary dependencies for Heimdall2. Under the heimdall2 directory, enter the following command in the terminal: +``` +yarn install +``` diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md index 0e2722780..61809326c 100644 --- a/src/courses/mappers/07.md +++ b/src/courses/mappers/07.md @@ -1,5 +1,7 @@ --- order: 7 -title: Mapper Creation Demonstration +title: Integrating Your Mapper With OHDF Converters author: Charles Hu --- + + From 0aa3889b923a536d6e1b5f135472357043b94850 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Tue, 11 Jun 2024 13:09:29 -0400 Subject: [PATCH 10/71] InspecJS Signed-off-by: Charles Hu --- src/courses/mappers/04.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index e744d5ab3..3a505c58a 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -7,7 +7,7 @@ author: Charles Hu ## What is InspecJS? - +InspecJS is a library that provides schema definitions, classes, and utilities for OHDF file handling. InspecJS plays a pivotal role in the contextualization process where it converts the individual statuses for each finding into an overall status for the control. ## What is OHDF Converters? From 0e40b1bd00494479c4fa714cf569c630d0f277a2 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 12 Jun 2024 12:29:42 -0400 Subject: [PATCH 11/71] OHDF intro rewrite Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 89 +++----- src/courses/mappers/03.md | 191 ++---------------- src/courses/mappers/04.md | 168 ++++++--------- src/courses/mappers/05.md | 2 +- src/courses/mappers/06.md | 48 +---- src/courses/mappers/07.md | 2 +- src/courses/mappers/README.md | 4 +- .../img/saf_security_validation_lifecycle.png | Bin 0 -> 235750 bytes 8 files changed, 106 insertions(+), 398 deletions(-) create mode 100644 src/courses/mappers/img/saf_security_validation_lifecycle.png diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 6fc1556a6..345b4a509 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -1,91 +1,52 @@ --- order: 2 next: 03.md -title: OHDF Background +title: What Is OHDF? author: Charles Hu --- ## What is OHDF? -OASIS Heimdall Data Format (OHDF) is a security data format used to normalize generated security data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security validation profiles, controls, and results. +OASIS Heimdall Data Format (OHDF) is a security data format used to normalize generated data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security validation profiles, controls, and results. -You can read more about OHDF [here](https://saf.mitre.org/framework/normalize). - -### Why OHDF? +## Why OHDF? - Many security tools do not provide context to relevant compliance standards for comparison across security tools.​ - Security tools typically generate data in unique formats that require multiple dashboards and utilities to process.​ -- OHDF reduces the time it takes to process security assessments, data in disparate locations and inconsistent semantics of a data element between formats.​ - -- OHDF enables: - - - Consistent integration, aggregation, and analysis of security data from all available sources.​ - - Preserving data integrity with original source data. - - Maximizing interoperability and data sharing.​ - - Facilitating the transformation and transport of data between security/management processes or technologies.​ - - Allowing for the mapping and enrichment of security data to relevant compliance standards (GDPR, NIST SP 800-53, PCI-DSS, etc.). - -## What Is a Mapper? +- OHDF reduces the time it takes to process security assessments, data in disparate locations, and inconsistent semantics of a data element between formats.​ -A mapper is a design pattern used to correlate (or map) items in two different objects with one another. Mappers are useful in that they allow us to connect items in objects that are nominally different but semantically the same. A result of this is that we can easily transform one object type into another through the use of mappings which define the direct relationship of items in each object type. +## Features -Here are some scenarios which demonstrate some key aspects of mappers: +### 1. Consistent integration, aggregation, and analysis of security data from all available sources.​ -::: details Transferring IDs -Say we have to transfer the credentials of an employee who is moving from Business A to Business B. The data formats the businesses use for IDs are as follows: -``` -// Business A -{Name, DoB, Age, Title} +- Enforces consistent schema fields through consciously designed data format mappings. +- Supports data format conversion from numerous established security tools such as AWS Security Hub's AWS Security Finding Format (ASFF) and Tenable Nessus' Nessus file format. +- Allows the integration of currently unsupported security tool data formats through the development of OHDF mappers for the OHDF Converters tool. -// Business B -{employee, employeeBirthday, employeeAge, jobTitle} -``` -How do we transfer John's credentials from Business A to Business B? -``` -{Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} -``` +[DEV NOTE: Maybe want to throw a graphic here] -What we can do is create a mapping which correlates the items from Business A's ID scheme to Business B's: -``` -{employee: Name, employeeBirthday: DoB, employeeAge: Age, jobTitle: Title} -``` +### 2. Preserving data integrity with original source data. -With this, we can then develop a mapper which takes John's credentials from Business A and transforms it to Business B's format as so: -``` -{Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} +- Uses mappings which maximize meaningful schema field conversions. +- Leverages schema fields `passthrough` and `raw` to preserve the original data in its entirety. +- Allows for bidirectional format conversions to and from OHDF. - || -\ / - \/ +[DEV NOTE: Maybe want to throw a graphic here] -MAPPER +### 3. Maximizing interoperability and data sharing.​ - || -\ / - \/ +- Provides a consistent and standardized format for communication. +- Provides an easily ingestible data format and tools to improve user readability. -{employee: 'John Doe', employeeBirthday: 10-6-1992, employeeAge: 32, jobTitle: 'Security Technician'} -``` +### 4. Facilitating the transformation and transport of data between security/management processes or technologies.​ -The important thing to note here is that mappers rely on underlying mappings which match semantically similar fields between two objects. These matches allow us to correctly convert each item in one object to the other. -::: +- Provides a clear schema for technologies/processes to support. +- Includes a simple file format that technologies/processes can accept. -::: details Translating a foreign language -Say we are given the job to translate the traditional Chinese sentence '我愛貓' into English. +### 5. Allowing for the mapping and enrichment of security data to relevant compliance standards (GDPR, NIST SP 800-53, PCI-DSS, etc.). -Without knowledge of the language, this is an impossible task. +- Uses mappers which provide and append relevant compliance standards to converted security tool data. -However, say we now also had a mapper which utilized the following mapping: -``` -{'愛': 'love', '我': 'I', '貓': 'cats'} -``` +## What Else? -Now this task becomes much more easier. We can apply this mapper which will translate the sentence from '我愛貓' to 'I love cats' and vice versa. - -The important thing to note here is that mappers make translating between two objects trivial, which means that anyone can do it and we can automate mappers to perform object conversions for us. -::: - - -## What Is an OHDF Mapper? - -An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security data format to another overarching security data format. In the case of the SAF tool suite, these mappers allow for the conversion of some given security service format to HDF (\*-to-HDF) and vice versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. +You can read more about OHDF [here](https://saf.mitre.org/framework/normalize). diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index 035524526..4fdd527bc 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -1,195 +1,28 @@ --- order: 3 next: 04.md -title: Understanding the OHDF Schema +title: Where Is OHDF Used? author: Charles Hu --- -## An Overview of the OHDF Schema +## Where Is OHDF Used? -The OHDF schema is designed to provide a simple, structured, and hierarchal view of security validation results. Any file or object that implements the schema can be broken down into a hierarchy of three structures. These structures are: +OHDF is part of the SAF normalization process (see below) and is officially implemented and used in a plethora of tools and libraries including InspecJS, OHDF Converters, the SAF CLI, and Heimdall2. -1) **Profiles**: This structure contains metadata on the scan target of the original security service export and on the run performed by the security tool. Profiles provide a high-level overview of the security service scan and the targeted system, which are formated in a manner which is digestible and immediately accessible to the assessor. +![](./img/saf_security_validation_lifecycle.png) -2) **Controls**: Controls are security standards that are used to prevent, mitigate, and address various security risks to sensitive information and infrastructure. In the case of OHDF, the controls structure is a collection of controls tested for by an external security service to ensure that the target complies with vulnerability and weakness prevention standards. Any given profile contains any number of controls which were tested against the target system during the original security service analysis. +## What Is InspecJS? -3) **Results**: The results structure contains information on the results of specific tests ran by the security service on the scan target against a security control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses exist but are rare) which cumulatively influence the determined compliance level of the scan target for some set of controls. Any given control contains any number of results which reflect the implemented tests to check if the target system is actually compliant with the control. +[InspecJS](https://github.com/mitre/heimdall2/tree/master/libs/inspecjs) is a library that provides schema definitions, classes, and utilities for OHDF file handling. InspecJS plays a pivotal role in the contextualization process where it converts the individual statuses for each finding into an overall status for the control. -## Breaking Down the Formal OHDF Schema +## What Is OHDF Converters? -::: note Full OHDF Schema -The following section contains a breakdown of a streamlined version of the OHDF schema. For the full and up-to-date version, see [here](https://saf.mitre.org/framework/normalize/ohdf-schema). -::: +[OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated into [Heimdall2](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification within an automated build pipeline. -We can break down the formal OHDF schema in the same manner as before by observing each structure in the hierarchy from a top-down view. +## What Is the SAF CLI? -1) **Profiles**: -``` -profiles: [ - 0: { - name // Name of profile, usually the original security service tool; should be unique - version // Version of security service tool - sha256 // Checksum of the profile; NOTE: AUTOMATICALLY GENERATED BY HDF CONVERTERS, DO NOT POPULATE - title // Title of security service scan; should be human readable - maintainer // Maintainer - summary // Summary of security service export (e.g., the STIG header) - license // Copyright license - copyright // Copyright holder - copyright_email // Copyright holder's email - supports // Supported platform targets - attributes // Inputs/attributes used in scan - groups // Set of descriptions for the control groups (e.g., control IDs) - controls // Controls substructure (see below) - status // Status of profile (typically 'loaded') - } - ... // More items may exist if the security service produces multiple profiles per export -] -``` +The [SAF CLI](https://github.com/mitre/saf) is a tool that provides various automation support functions for CI/CD. One of its main functions is the `saf convert` command, which allows for the conversion of data between OHDF and several supported security tool data formats. -2) **Controls**: +## What Is Heimdall2? -``` -controls: [ - 0: { - id // ID of control; used for sorting, should be unique for each unique control - title // Title of control - desc // Description of the control - descriptions // Additional descriptions; usually 'check' and 'fix' text for control - impact // Security severity of control - refs // References to external control documentation - tags // Control tags; typically correlate to existing vulnerability/weakness database (e.g., NIST, CVE, CWE) - code // Control source code for code preservation - source_location // Location of control within source code - results // Results substructure (see below) - } - ... // More items may exist if there are multiple controls reported per profile -] -``` - -3) **Results**: - -``` -results: [ - 0: { - status // Pass/fail status of test (other statuses exist but are rare) - code_desc // Test expectations as defined by control - message // Demonstration of expected and actual result of test to justify test status - run_time // Overall runtime of test - start_time // Starting time of test - } - ... // More items may exist if there are multiple results tested per control -] -``` - -These aforementioned structures cumulatively result in the following generalized structure which primarily defines OHDF: - -``` -// Data fields have been removed for the sake of demonstration -profiles: [ - 0: { - controls: [ - 0: { - results: [ - 0: { - }, - ... - ] - }, - ... - ] - }, - ... -] -``` - -There are additional structures in the OHDF schema which are used for metadata/extraneous information storage. These exist alongside the profiles structure on the top level of the HDF schema. The general structure for the top level of the HDF schema is as follows: - -``` -{ - platform: { // Information on the platform producing the export - name // Name of platform export was run on - release // Platform version - target_id // Platform target ID (i.e., further identifying information on platform) - } - version // Platform version - statistics: { // Statistics relating to target scan run - duration // Duration of run - } - profiles // Profiles structure - passthrough: { // Extraneous information storage - auxiliary_data: [ // Storage for unused data from the sample file - 0: { - name // Name of auxiliary data source - data // Auxiliary data - } - ... // More items may exist if there are multiple auxiliary data sources available - ] - raw // Raw data dump of input security service export - } -} -``` - -## The OHDF Schema - -The final OHDF schema is as follows: -``` -{ - platform: { // required field - name // required field - release // required field - target_id - } - version // required field - statistics: { // required field - duration - } - profiles: [ // required field - 0: { - name // required field - version - sha256 // required field - title - maintainer - summary - license - copyright - copyright_email - supports // required field - attributes // required field - groups // required field - controls: [ // required field - 0: { - id // required field - title - desc - descriptions - impact // required field - refs // required field - tags // required field - code - source_location // required field - results: [ // required field - 0: { - status - code_desc // required field - message - run_time - start_time // required field - } - ] - } - ] - status - } - ] - passthrough: { - auxiliary_data: [ - 0: { - name - data - } - ] - raw - } -} -``` +[Heimdall2](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. Data that is imported into Heimdall2 is automatically converted to OHDF through OHDF Converters, which serves as the underlying library which services data format conversion requests in Heimdall2. diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 3a505c58a..21a54b1d0 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -1,113 +1,73 @@ --- order: 4 next: 05.md -title: Understanding InspecJS & OHDF Converters +title: What Is an OHDF Mapper? author: Charles Hu --- -## What is InspecJS? - -InspecJS is a library that provides schema definitions, classes, and utilities for OHDF file handling. InspecJS plays a pivotal role in the contextualization process where it converts the individual statuses for each finding into an overall status for the control. - -## What is OHDF Converters? - -OHDF Converters is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated into [Heimdall2](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification within an automated build pipeline. - -### Features - -- Leverages OHDF mappers to transform security data formats to and from OHDF. -- Special keyword functions provided by the base-converter class. -- Fingerprinting services for automatic data format identification. - -### Keywords - -base-converter is an underlying class which enables \*-to-HDF mapping in OHDF Converters. It defines \*-to-HDF mappers and provides critical tools in the form of keywords which allow for the construction of such mappers. All \*-to-HDF mappers inherit from this class and therefore have access to the keywords that this class provides. You should aim to utilize these keywords to their fullest potential to ease and simplify mapper development. The provided tools are as follows: - -- `path`: Define JSON object path to go to. Paths are found recursively. - - Use: - ``` - path: PATH_AS_STRING - ``` - - Example: - ``` - // Attribute 'id' will be set as whatever JSON object attribute 'vulnerability.id' is - id: {path: 'vulnerability.id'} - ``` - -- `transformer`: Execute given code sequence; operates similar to an anonymous function. - - Use: - ``` - transformer: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} - ``` - - Example: - ``` - // Attribute 'code' will be set as the returned stringified JSON object of input 'vulnerability' - code: { - transformer: (vulnerability: Record): string => { - return JSON.stringify(vulnerability, null, 2); - } - } - ``` - -- `arrayTransformer`: Execute given code sequence on a given array; primarily used when in an attribute that is an array of objects. - - Use: - ``` - arrayTransformer: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} - ``` - - Example: - ``` - // The function 'deduplicateId' will run against all items in the current array that the 'arrayTransformer' was called inside - arrayTransformer: deduplicateId - ``` - -- `pathTransform`: Converts the JSON object path structure. - - Use: - ``` - pathTransform: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} - ``` - - Example: - ``` - // Returns the JSON path if it is an array, otherwise returns an empty array - pathTransform: (value) => (Array.isArray(value) ? value : []), - ``` - -- `key`: Used by base-converter to sort an array of objects by - - Use: - ``` - key: KEY_AS_STRING - ``` - - Example: - ``` - // 'id' is now the key by which this array will be sorted by - key: 'id' - ``` - -### Directory Structure - -The following is a simplified depiction of the directory tree for the HDF Converter. Only noteworthy and potentially useful files and directories are included. It is not imperative to memorize the structure, but it is useful to familiarize yourself with it to better understand what exists where within the HDF Converter for future reference. +## What Is a Mapper? +A mapper is a design pattern used to correlate (or map) items in two different objects with one another. Mappers are useful in that they allow us to connect items in objects that are nominally different but semantically the same. A result of this is that we can easily transform one object type into another through the use of mappings which define the direct relationship of items in each object type. + +Here are some scenarios which demonstrate some key aspects of mappers: + +::: details Transferring IDs +Say we have to transfer the credentials of an employee who is moving from Business A to Business B. The data formats the businesses use for IDs are as follows: +``` +// Business A +{Name, DoB, Age, Title} + +// Business B +{employee, employeeBirthday, employeeAge, jobTitle} +``` +How do we transfer John's credentials from Business A to Business B? +``` +{Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} +``` + +What we can do is create a mapping which correlates the items from Business A's ID scheme to Business B's: +``` +{employee: Name, employeeBirthday: DoB, employeeAge: Age, jobTitle: Title} +``` + +With this, we can then develop a mapper which takes John's credentials from Business A and transforms it to Business B's format as so: +``` +{Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} + + || +\ / + \/ + +MAPPER + + || +\ / + \/ + +{employee: 'John Doe', employeeBirthday: 10-6-1992, employeeAge: 32, jobTitle: 'Security Technician'} +``` + +The important thing to note here is that mappers rely on underlying mappings which match semantically similar fields between two objects. These matches allow us to correctly convert each item in one object to the other. +::: + +::: details Translating a foreign language +Say we are given the job to translate the traditional Chinese sentence '我愛貓' into English. + +Without knowledge of the language, this is an impossible task. + +However, say we now also had a mapper which utilized the following mapping: ``` -hdf-converters -+-- data -| +-- converters -| | +-- csv2json.ts -| | +-- xml2json.ts -+-- sample_jsons //Sample exports for mapper testing are located here -+-- src //*-to-HDF mappers are located here -| +-- converters-from-hdf //HDF-to-* mappers are located here -| | +-- reverse-any-base-converter.ts -| | +-- reverse-base-converter.ts -| +-- mappings //Non-HDF mappers are located here (e.g., CVE, CCI, NIST) -| +-- utils -| | +-- fingerprinting.ts -| | +-- global.ts -| +-- base-converter.ts -+-- test //Mapper tests are located here -| +-- mappers -| | +-- forward //*-to-HDF tests -| | +-- reverse //HDF-to-* tests -| | +-- utils.ts -+-- types //Explicit data typing for known export schemas -+-- index.ts -+-- package.json +{'愛': 'love', '我': 'I', '貓': 'cats'} ``` + +Now this task becomes much more easier. We can apply this mapper which will translate the sentence from '我愛貓' to 'I love cats' and vice versa. + +The important thing to note here is that mappers make translating between two objects trivial, which means that anyone can do it and we can automate mappers to perform object conversions for us. +::: + + +## What Is an OHDF Mapper? + +An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security data format to another overarching security data format. In the case of the SAF tool suite, these mappers allow for the conversion of some given security service format to HDF (\*-to-HDF) and vice versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. + +Examples of these \ No newline at end of file diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index ed3a78824..72086fbeb 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -1,7 +1,7 @@ --- order: 5 next: 06.md -title: The Art of Mapper Making +title: e author: Charles Hu --- diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index 0dbcef495..c19410351 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -1,54 +1,8 @@ --- order: 6 next: 07.md -title: Mapper Creation Demonstration +title: e author: Charles Hu --- -## Environment Set Up -Node.js (a runtime environment for Javascript) and Yarn (a package manager for Node.js) are external utilities which are utilized extensively within this guide. The following section details their installation process. - -Linux/Mac OS: - -1. Install [nvm](https://github.com/nvm-sh/nvm#install--update-script). - - - 1a. Use either of the following commands to install nvm: - ``` - curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash - ``` - ``` - wget -qO- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash - ``` - - - 1b. Either restart the terminal or run the following commands to use nvm: - ``` - export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")" - [ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh" # This loads nvm - ``` - -2. Run the following command to install and use Node.js v18: -``` -nvm install 18 -``` - -3. Install [Yarn](https://yarnpkg.com/getting-started/install) - -Windows: - -1. Install [Node.js v18 via the installer](https://nodejs.org/en/download/). - -2. Install [Yarn](https://yarnpkg.com/getting-started/install): - -## Repository Set Up - -1. Fork/branch a development repository from the main [Heimdall2 GitHub repository](https://github.com/mitre/heimdall2). - - - SAF team developers have write access to the main repository and should [create a branch](https://docs.github.com/en/desktop/contributing-and-collaborating-using-github-desktop/making-changes-in-a-branch/managing-branches#creating-a-branch) on the primary development repository. Non-SAF team developers should instead [create a fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo#forking-a-repository) of the main repository and create a development branch there. - -2. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. - -3. Install the necessary dependencies for Heimdall2. Under the heimdall2 directory, enter the following command in the terminal: -``` -yarn install -``` diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md index 61809326c..11e8d266c 100644 --- a/src/courses/mappers/07.md +++ b/src/courses/mappers/07.md @@ -1,6 +1,6 @@ --- order: 7 -title: Integrating Your Mapper With OHDF Converters +title: e author: Charles Hu --- diff --git a/src/courses/mappers/README.md b/src/courses/mappers/README.md index 843a4d99e..3fc6a078f 100644 --- a/src/courses/mappers/README.md +++ b/src/courses/mappers/README.md @@ -7,14 +7,14 @@ author: Charles Hu ## Overview -The purpose of this class is to provide you with the foundational knowledge needed to create data format mappers targeted against the [OASIS Heimdall Data Format (OHDF)](https://saf.mitre.org/framework/normalize). In the following course, you will be taught the art and science of schema translation through a combination of both guided walkthroughs and hands-on demonstrations. +The purpose of this class is to provide you with the foundational knowledge needed to create data format mappers for mapping data to the [OASIS Heimdall Data Format (OHDF)](https://saf.mitre.org/framework/normalize). In the following course, you will be taught the art and science of schema translation through a combination of both guided walkthroughs and hands-on demonstrations. ### Objectives By the end of this class, you should be able to achieve the following objectives: - Understand the OHDF schema and its components. -- Be able to identify and break down key components of any given security data export. +- Be able to identify and break down key components of any given security tool export. - Correlate schema fields of your security data export to schema fields in OHDF. - Create a *-to-OHDF mapper. - Integrate your mapper with the [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) library. diff --git a/src/courses/mappers/img/saf_security_validation_lifecycle.png b/src/courses/mappers/img/saf_security_validation_lifecycle.png new file mode 100644 index 0000000000000000000000000000000000000000..321ce20e0e005a949b00ccd3d526196d9c50b2b6 GIT binary patch literal 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zb!s;0&`?~rmRBP0ki9}%d?YMa8yawdt46=m)VF_|qAx=V;i?lat z*6d%cj1+f#83_AP0xT;f-;KKo_TlBcaljfYIrC5~L4(c2Rfc#2B5ErXAg6PAO3B3t zF&4h7w6oAYgY@?UIfzfG4sTh8z~9rst!fh_X6YQ-9uoGxL@`L2E-%n&@l}gU8g4QH zMJ_#BOR}1G&R7X1u%dRc!=)kKA2Ru5vYb_Y7LW6(G}^jO>8T@+}$nnBVgGvk~n6+d)^e z3P)G-f^$NWY1fgonT!jKE-@jd0HtCc;4!5_3fW!2%(h|IFaDsnubJ#14)Gp4L>s83 z_=GzB-H1GCVap2Ks^)d3PN}#nr`iG}E@Cqw#?A>|Ud4GQ4!-^}?)CP`t(TMdcZP4D zE!A3t+uea0o4eO*2$m$}Y=84cGPNs$fok{DPPLM6FHpW9!uy5}$m#>|2p|Pu^RZiG zp{Z>~NbvGLti93kc>6EyhO6>mhcOI>l(Ax_4E4i#91!c-LDiUm{FGp3bSAkw@ymvT zlIv;a#*I(bleu_L*x!#j?bN_%ZtlC*(Pf0C zM-^Xv!+VDH?;)(h5Ne7q98NjyyJ5FE7DOy%uSkq*bV8Wh^Oon9CUN{J(w4dRV%(6) zkZA?soHGt(0dDFFI-Kb;%MZeqEV(ZIxQ_=F-WE!{LQFZlvd2}^Yp|$8sBtI1F~VOg z4uY15yGi13QVc5YjeQ?()aB@w0zDQ59h;{qqc;QI-CfeUWwG9Y%+JTs$ye*ckOLQV zd(b=;)fA#o|zOo>*Z!8y-l0LjrPhHkc#ATQx43{`7-Ov)<+ixw<_@W zGL8Sgk~<7oA(-u}*N6rHWZ(!)E-+Ur&G7|Jx2J+QKtkLT)iG`0)6L_unU0j{EjBbJ zdxvzx$N%XP#gmsOe9v7r*x|YIG(eder}H%i3j!yB(@B`Q6~MIic@pBMXwT?8A;S6Z zp8i{gHsm@v>=gu2>eEwekuKV*pJvr+1au#DI_SGAVq5qCZ6h7Qul{G`{J2AgjyFP_ zjis%Q=u;uDyUogBzOqzVMwjQqWVxuo*@HN1aqa%1a4Ou5Xfi$7EskUxZ&0NGq$>Y0 zBloqVu9&s(*hWcGK0s00je8Ag$324~1nz(5vj1yHqIZvB0#M=8!$xDfqvFkW;H0d5 z=e&N5@bTA2NH-9ne7)_Dvw~vdFtl5Bx_JUh&%Y2fvxeI@`ORu!LqT`#%Zfr6?f&nrdKvHfWIOLo8cS{d|>& z7seQ2@9pY?03C?Xr&Zhm(%f*Ce}4~ic3PhsP1ySSCqTx)t0I*2O}9cUEs%}1MUWL< zU;Quj{y&NaI%4b20$JCbS?ySPzmR7W3;OOHnEz<@d!Weedf~`*dUyBSHK>iU(lclKbiO5dswv_JA+mrw9f9-`VB=?fc+xpd-lt zeN6w{>nq;`NBaCzc&PHi@b}9pFfR==}e$F5*?>LAJCZXxzdJ2KbSc MRFbF?Gy3xX0H}Jhp#T5? literal 0 HcmV?d00001 From c1089f40db2cbc64af3da55ba54c43a1d9cc3cb4 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 12 Jun 2024 12:42:43 -0400 Subject: [PATCH 12/71] Mapper section Signed-off-by: Charles Hu --- src/courses/mappers/04.md | 4 +++- src/courses/mappers/05.md | 2 +- src/courses/mappers/06.md | 2 +- src/courses/mappers/07.md | 2 +- 4 files changed, 6 insertions(+), 4 deletions(-) diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 21a54b1d0..790b1fa8e 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -70,4 +70,6 @@ The important thing to note here is that mappers make translating between two ob An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security data format to another overarching security data format. In the case of the SAF tool suite, these mappers allow for the conversion of some given security service format to HDF (\*-to-HDF) and vice versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. -Examples of these \ No newline at end of file +The following is an example of + +More examples of actual OHDF mappers used in production can be [found here](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters/src). \ No newline at end of file diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index 72086fbeb..52b69baba 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -1,7 +1,7 @@ --- order: 5 next: 06.md -title: e +title: REWRITING author: Charles Hu --- diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index c19410351..c4a7af329 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -1,7 +1,7 @@ --- order: 6 next: 07.md -title: e +title: REWRITING author: Charles Hu --- diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md index 11e8d266c..ae32a3018 100644 --- a/src/courses/mappers/07.md +++ b/src/courses/mappers/07.md @@ -1,6 +1,6 @@ --- order: 7 -title: e +title: REWRITING author: Charles Hu --- From 7f25daafc2d98b4041bd3cf04e69d42cc2c1be1a Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 12 Jun 2024 14:23:47 -0400 Subject: [PATCH 13/71] OHDF schema definition Signed-off-by: Charles Hu --- src/courses/mappers/04.md | 279 +++++++++++++++++- src/courses/mappers/05.md | 41 ++- src/courses/mappers/06.md | 2 +- .../saf_security_validation_lifecycle.png | Bin 4 files changed, 317 insertions(+), 5 deletions(-) rename src/courses/mappers/{img => }/saf_security_validation_lifecycle.png (100%) diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 790b1fa8e..020958324 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -68,8 +68,281 @@ The important thing to note here is that mappers make translating between two ob ## What Is an OHDF Mapper? -An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security data format to another overarching security data format. In the case of the SAF tool suite, these mappers allow for the conversion of some given security service format to HDF (\*-to-HDF) and vice versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. +An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security data format to another overarching security data format. In the case of the SAF tool suite, these mappers allow for the conversion of any given security service format to HDF (\*-to-HDF) and vice versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. -The following is an example of +OHDF mappers are built upon the schemas that define the involved security data formats, and the mechanics of the mappers revolve around correlating each schema's fields as accurately as possible. -More examples of actual OHDF mappers used in production can be [found here](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters/src). \ No newline at end of file +### Examples + +The following section show some simplified examples of security tool data that has been converted to OHDF using OHDF mappers. + +Here are some key questions to keep note of while reading through these examples: + +- How is the source data structured/organized (e.g., by requirement, by target system, by finding)? +- How is the OHDF file structured? +- Where are data fields in the source data going when converted to OHDF? + +#### GoSec + +::: details Source Data +``` +{ + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + "GosecVersion": "dev" +} +``` +::: + +::: details Converted OHDF File +``` +{ + "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, + "version": "2.10.8", + "statistics": {}, + "profiles": [ + { + "name": "Gosec scanner", + "title": "gosec", + "version": "dev", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "controls": [ + { + "tags": { + "nist": ["SI-10"], + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "nosec": "", + "suppressions": "", + "severity": "MEDIUM", + "confidence": "HIGH" + }, + "refs": [], + "source_location": {}, + "title": "Potential file inclusion via variable", + "id": "G304", + "desc": "", + "impact": 0.5, + "results": [ + { + "status": "failed", + "code_desc": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "message": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go, line:83, column:14", + "start_time": "" + } + ] + } + ], + "sha256": "d0506f4b7715bf8b1cd81a8a87ab8efcce41ebeb2b5ec5fcfb23d3bdd136f48c" + } + ], + "passthrough": { + "auxiliary_data": [{ "name": "Gosec", "data": { "Golang errors": {} } }] + } +} +``` +::: + +#### Twistlock + +::: details Source Data +``` +{ + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "collections": [ + "All", + "TEST-COLLECTION" + ], + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": [ + "MPLv2.0" + ] + } + ], + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceDistribution": { + "critical": 0, + "high": 0, + "medium": 0, + "low": 0, + "total": 0 + }, + "complianceScanPassed": true, + "vulnerabilities": [ + { + "id": "CVE-2021-43529", + "status": "affected", + "cvss": 9.8, + "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "severity": "critical", + "packageName": "nss-util", + "packageVersion": "3.67.0-7.el8_5", + "link": "https://access.redhat.com/security/cve/CVE-2021-43529", + "riskFactors": [ + "Remote execution", + "Attack complexity: low", + "Attack vector: network", + "Critical severity", + "Recent vulnerability" + ], + "impactedVersions": [ + "*" + ], + "publishedDate": "2021-12-01T00:00:00Z", + "discoveredDate": "2022-05-18T12:24:22Z", + "layerTime": "2022-05-16T23:12:25Z" + } + ], + "vulnerabilityDistribution": { + "critical": 5, + "high": 1, + "medium": 86, + "low": 5, + "total": 97 + }, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-03T08:38:31Z" + } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" +} +``` +::: + +::: details Converted OHDF File +``` +{ + "platform": { + "name": "Heimdall Tools", + "release": "2.10.8", + "target_id": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a" + }, + "version": "2.10.8", + "statistics": {}, + "profiles": [ + { + "name": "Twistlock Scan", + "title": "Twistlock Project: All / TEST-COLLECTION", + "summary": "Package Vulnerability Summary: 97 Application Compliance Issue Total: 0", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "controls": [ + { + "tags": { + "nist": ["SI-2", "RA-5"], + "cci": ["CCI-002605", "CCI-001643"], + "cveid": "CVE-2021-43529" + }, + "refs": [], + "source_location": {}, + "title": "CVE-2021-43529", + "id": "CVE-2021-43529", + "desc": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "impact": 0.9, + "code": "{\n \"id\": \"CVE-2021-43529\",\n \"status\": \"affected\",\n \"cvss\": 9.8,\n \"description\": \"DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec\",\n \"severity\": \"critical\",\n \"packageName\": \"nss-util\",\n \"packageVersion\": \"3.67.0-7.el8_5\",\n \"link\": \"https://access.redhat.com/security/cve/CVE-2021-43529\",\n \"riskFactors\": [\n \"Remote execution\",\n \"Attack complexity: low\",\n \"Attack vector: network\",\n \"Critical severity\",\n \"Recent vulnerability\"\n ],\n \"impactedVersions\": [\n \"*\"\n ],\n \"publishedDate\": \"2021-12-01T00:00:00Z\",\n \"discoveredDate\": \"2022-05-18T12:24:22Z\",\n \"layerTime\": \"2022-05-16T23:12:25Z\"\n}", + "results": [ + { + "status": "failed", + "code_desc": "Package \"nss-util\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-util\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-util\"", + "start_time": "2022-05-18T12:24:22Z" + } + ] + } + ], + "sha256": "998180601124e9d2b4f03be239a5bb68d9045ba2dc5a26fa2c8d453500288b2e" + } + ], + "passthrough": { + "auxiliary_data": [ + { + "name": "Twistlock", + "data": { + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } + ], + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceScanPassed": true, + "vulnerabilityScanPassed": true, + "history": [{ "created": "2022-05-03T08:38:31Z" }], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" + } + } + ] + } +} +``` +::: diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index 52b69baba..05cbfa13d 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -1,8 +1,47 @@ --- order: 5 next: 06.md -title: REWRITING +title: OHDF Schema Basics author: Charles Hu --- +## An Overview of the OHDF Schema +In order to make an OHDF mapper, it is important to understand the specifics of how OHDF is actually structured through the OHDF schema. + +The OHDF schema is designed to provide a simple, structured, and hierarchal view of security validation results. Any file or object that implements the schema can be broken down into a hierarchy of three structures. These structures are: + +### 1. **Profiles** + +This structure contains metadata on the scan target of the original security service export and on the run performed by the security tool. Profiles provide a high-level overview of the security service scan and the targeted system, which are formatted in a manner which is digestible and immediately accessible to the assessor. + +### 2. **Controls** + +Controls are security standards that are used to prevent, mitigate, and address various security risks to sensitive information and infrastructure. In the case of OHDF, the controls structure is a collection of controls tested for by an external security service to ensure that the target complies with vulnerability and weakness prevention standards. Any given profile contains any number of controls which were tested against the target system during the original security service analysis. + +### 3. **Results** + +The results structure contains information on the results of specific tests ran by the security service on the scan target against a security control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses exist but are rare) which cumulatively influence the determined compliance level of the scan target for some set of controls. Any given control contains any number of results which reflect the implemented tests to check if the target system is actually compliant with the control. + +## Overall Hierarchy + +These aforementioned structures cumulatively result in the following generalized structure: + +``` +// Data fields have been removed for the sake of demonstration +profiles: [ + 0: { + controls: [ + 0: { + results: [ + 0: { + }, + ... + ] + }, + ... + ] + }, + ... +] +``` diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index c4a7af329..ef20c512c 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -1,7 +1,7 @@ --- order: 6 next: 07.md -title: REWRITING +title: Formal OHDF Schema Definition author: Charles Hu --- diff --git a/src/courses/mappers/img/saf_security_validation_lifecycle.png b/src/courses/mappers/saf_security_validation_lifecycle.png similarity index 100% rename from src/courses/mappers/img/saf_security_validation_lifecycle.png rename to src/courses/mappers/saf_security_validation_lifecycle.png From 129d8da4778100959792996f758c7d378143e762 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 12 Jun 2024 14:27:34 -0400 Subject: [PATCH 14/71] Img locale change Signed-off-by: Charles Hu --- .../{ => img}/saf_security_validation_lifecycle.png | Bin 1 file changed, 0 insertions(+), 0 deletions(-) rename src/courses/mappers/{ => img}/saf_security_validation_lifecycle.png (100%) diff --git a/src/courses/mappers/saf_security_validation_lifecycle.png b/src/courses/mappers/img/saf_security_validation_lifecycle.png similarity index 100% rename from src/courses/mappers/saf_security_validation_lifecycle.png rename to src/courses/mappers/img/saf_security_validation_lifecycle.png From 1dd9ee033427abca43fe4b5cf6e690639e3af2f7 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 12 Jun 2024 15:26:19 -0400 Subject: [PATCH 15/71] Schema definition Signed-off-by: Charles Hu --- src/courses/mappers/04.md | 4 +- src/courses/mappers/05.md | 8 +-- src/courses/mappers/06.md | 148 ++++++++++++++++++++++++++++++++++++++ src/courses/mappers/07.md | 69 +++++++++++++++++- 4 files changed, 222 insertions(+), 7 deletions(-) diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 020958324..47a8fd36c 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -68,9 +68,9 @@ The important thing to note here is that mappers make translating between two ob ## What Is an OHDF Mapper? -An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security data format to another overarching security data format. In the case of the SAF tool suite, these mappers allow for the conversion of any given security service format to HDF (\*-to-HDF) and vice versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. +An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security tool data format to another overarching security tool data format. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to HDF (\*-to-HDF) and vice versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. -OHDF mappers are built upon the schemas that define the involved security data formats, and the mechanics of the mappers revolve around correlating each schema's fields as accurately as possible. +OHDF mappers are built upon the schemas that define the involved data formats, and the mechanics of the mappers revolve around correlating each schema's fields as accurately as possible. ### Examples diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index 05cbfa13d..8b6357809 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -9,19 +9,19 @@ author: Charles Hu In order to make an OHDF mapper, it is important to understand the specifics of how OHDF is actually structured through the OHDF schema. -The OHDF schema is designed to provide a simple, structured, and hierarchal view of security validation results. Any file or object that implements the schema can be broken down into a hierarchy of three structures. These structures are: +The OHDF schema is designed to provide a simple, structured, and hierarchal view of security tool results. Any file or object that implements the schema can be broken down into a hierarchy of three structures. These structures are: ### 1. **Profiles** -This structure contains metadata on the scan target of the original security service export and on the run performed by the security tool. Profiles provide a high-level overview of the security service scan and the targeted system, which are formatted in a manner which is digestible and immediately accessible to the assessor. +This structure contains metadata on the target system of the original security tool export and on the specific run performed by the security tool. Profiles provide a high-level overview of the security tool result and the targeted system, which are formatted in a manner which is digestible and immediately accessible to the assessor. ### 2. **Controls** -Controls are security standards that are used to prevent, mitigate, and address various security risks to sensitive information and infrastructure. In the case of OHDF, the controls structure is a collection of controls tested for by an external security service to ensure that the target complies with vulnerability and weakness prevention standards. Any given profile contains any number of controls which were tested against the target system during the original security service analysis. +Controls are security requirements that are used to prevent, mitigate, and address various security risks to sensitive information and infrastructure. In the case of OHDF, the controls structure is a collection of requirements tested for by an external security tool to ensure that the target complies with vulnerability and weakness prevention standards. Any given profile contains any number of controls which were tested against the target system during the original security tool run. ### 3. **Results** -The results structure contains information on the results of specific tests ran by the security service on the scan target against a security control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses exist but are rare) which cumulatively influence the determined compliance level of the scan target for some set of controls. Any given control contains any number of results which reflect the implemented tests to check if the target system is actually compliant with the control. +The results structure contains information on the results of specific tests ran by the security tool on the target system against a security requirement/control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses exist but are rare) which cumulatively influence the determined compliance level of the target system for some set of requirements/controls. Any given control contains any number of results which reflect the implemented tests to check if the target system is actually compliant. ## Overall Hierarchy diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index ef20c512c..1a8b3b279 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -5,4 +5,152 @@ title: Formal OHDF Schema Definition author: Charles Hu --- +## Breaking Down the Formal OHDF Schema +We can break down the formal OHDF schema in the same manner as before by observing each structure in the hierarchy from a top-down view. + +::: note Full OHDF Schema +The following section contains a breakdown of a streamlined version of the OHDF schema. For the full and up-to-date version, see [here](https://saf.mitre.org/framework/normalize/ohdf-schema). +::: + +### 1. **Profiles** + +::: details Profiles Schema +``` +profiles: [ + 0: { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls, + status + }, + ... // More items may exist if the security service produces multiple profiles per export +] +``` +::: + +- `name`: Name of profile, usually the original security service tool; should be unique. +- `version`: Version of security service tool. +- `sha256`: Checksum of the profile (NOTE: AUTOMATICALLY GENERATED BY HDF CONVERTERS, DO NOT POPULATE). +- `title`: Title of security service scan; should be human readable. +- `maintainer`: Maintainer. +- `summary`: Summary of security service export (e.g., the STIG header). +- `license`: Copyright license. +- `copyright`: Copyright holder. +- `copyright_email`: Copyright holder's email. +- `supports`: Supported platform targets. +- `attributes`: Inputs/attributes used in scan. +- `groups`: Set of descriptions for the control groups (e.g., control IDs). +- `controls`: Controls substructure (see below). +- `status`: Status of profile (typically 'loaded'). + +### 2. **Controls** + +::: details Controls Schema +``` +controls: [ + 0: { + id, + title, + desc, + descriptions, + impact, + refs, + tags, + code, + source_location, + results + }, + ... // More items may exist if there are multiple controls reported per profile +] +``` +::: + +- `id`: ID of control, used for sorting; should be unique for each unique control. +- `title`: Title of control. +- `desc`: Description of the control. +- `descriptions`: Additional descriptions; usually 'check' and 'fix' text for control. +- `impact`: Security severity of control. +- `refs`: References to external control documentation. +- `tags`: Control tags; typically correlate to existing vulnerability/weakness database (e.g., NIST, CVE, CWE). +- `code`: Control source code for code preservation. +- `source_location`: Location of control within source code. +- `results`: Results substructure (see below). + +### 3. **Results** + +::: details Results Schema +``` +results: [ + 0: { + status, + code_desc, + message, + run_time, + start_time + }, + ... // More items may exist if there are multiple results tested per control +] +``` +::: + +- `status`: Pass/fail status of test (other statuses exist but are rare). +- `code_desc`: Test expectations as defined by control. +- `message`: Demonstration of expected and actual result of test to justify test status. +- `run_time`: Overall runtime of test. +- `start_time`: Starting time of test. + +### 4. Additional Structures + +There are additional structures in the OHDF schema which are used for metadata/extraneous information storage. These exist alongside the profiles structure on the top level of the HDF schema. The general structure for the top level of the HDF schema is as follows: + +::: details Additional Schema +``` +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles, + passthrough: { + auxiliary_data: [ + 0: { + name, + data + }, + ... // More items may exist if there are multiple auxiliary data sources available + ], + raw + } +} +``` +::: + +- `platform`: Information on the platform producing the export. + - `name`: Name of platform export was run on. + - `release`: Platform version. + - `target_id`: Platform target ID (i.e., further identifying information on platform). +- `version`: Platform version. +- `statistics`: Statistics relating to target scan run. + - `duration`: Duration of run. +- `profiles`: Profiles structure. +- `passthrough`: Extraneous information storage. + - `auxiliary_data`: Storage for unused data from the sample file. + - `name`: Name of auxiliary data source. + - `data`: Auxiliary data. + - `raw`: Raw data dump of input security service export. diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md index ae32a3018..010995c8a 100644 --- a/src/courses/mappers/07.md +++ b/src/courses/mappers/07.md @@ -1,7 +1,74 @@ --- order: 7 -title: REWRITING +next: 08.md +title: Required OHDF Schema Fields author: Charles Hu --- +## Required OHDF Schema Fields + + +::: details Full Schema +``` +{ + platform: { // required field + name // required field + release // required field + target_id + } + version // required field + statistics: { // required field + duration + } + profiles: [ // required field + 0: { + name // required field + version + sha256 // required field + title + maintainer + summary + license + copyright + copyright_email + supports // required field + attributes // required field + groups // required field + controls: [ // required field + 0: { + id // required field + title + desc + descriptions + impact // required field + refs // required field + tags // required field + code + source_location // required field + results: [ // required field + 0: { + status + code_desc // required field + message + run_time + start_time // required field + } + ] + } + ] + status + } + ] + passthrough: { + auxiliary_data: [ + 0: { + name + data + } + ] + raw + } +} +``` +::: From 7312d3d741028f32a691afb7f82a647f9608e859 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 12 Jun 2024 15:48:17 -0400 Subject: [PATCH 16/71] Required fields Signed-off-by: Charles Hu --- src/courses/mappers/07.md | 119 ++++++++++++++++++++++++++------------ 1 file changed, 82 insertions(+), 37 deletions(-) diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md index 010995c8a..6771008d6 100644 --- a/src/courses/mappers/07.md +++ b/src/courses/mappers/07.md @@ -7,66 +7,111 @@ author: Charles Hu ## Required OHDF Schema Fields +Not all fields in the schema have to be filled or even used in an OHDF mapper. In practice, most implementations either provide a blank field or omit an unused field entirely. +Note that just because you can skip a schema field does not mean that you should. Always aim to maximize the filled fields in your mapper and only skip a field as a last resort if no applicable equivalent exists in your source data. Consider required fields as priority fields that you should aim to fill out first instead of the bare minimum necessary to create a mapper. + +The fields that are specifically required by the schema are as follows: + +::: details Required Fields +``` +{ + platform: { + name, + release + }, + version, + statistics, + profiles: [ + 0: { + name, + sha256, + supports, + attributes, + groups, + controls: [ + 0: { + id, + impact, + refs, + tags, + source_location, + results: [ + 0: { + code_desc, + start_time + }, + ] + }, + ] + }, + ] +} +``` +::: + +## In Context + +The required fields in context of the full schema are shown below: ::: details Full Schema ``` { platform: { // required field - name // required field - release // required field + name, // required field + release, // required field target_id - } - version // required field + }, + version, // required field statistics: { // required field duration - } + }, profiles: [ // required field 0: { - name // required field - version - sha256 // required field - title - maintainer - summary - license - copyright - copyright_email - supports // required field - attributes // required field - groups // required field + name, // required field + version, + sha256, // required field + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, // required field + attributes, // required field + groups, // required field controls: [ // required field 0: { - id // required field - title - desc - descriptions - impact // required field - refs // required field - tags // required field - code - source_location // required field + id, // required field + title, + desc, + descriptions, + impact, // required field + refs, // required field + tags, // required field + code, + source_location, // required field results: [ // required field 0: { - status - code_desc // required field - message - run_time + status, + code_desc, // required field + message, + run_time, start_time // required field } ] - } - ] + }, + ], status - } - ] + }, + ], passthrough: { auxiliary_data: [ 0: { - name + name, data - } - ] + }, + ], raw } } From 24add33dd414339f32f9b0bcdeeec642ae7bd22c Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Thu, 13 Jun 2024 10:57:35 -0400 Subject: [PATCH 17/71] Major syntax/example overhaul Signed-off-by: Charles Hu --- src/courses/mappers/04.md | 222 +++++++++++++++--------------- src/courses/mappers/05.md | 2 +- src/courses/mappers/06.md | 141 ++++++++++++++++++- src/courses/mappers/07.md | 95 ++++++++++++- src/courses/mappers/08.md | 275 ++++++++++++++++++++++++++++++++++++++ 5 files changed, 614 insertions(+), 121 deletions(-) create mode 100644 src/courses/mappers/08.md diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 47a8fd36c..b6269b310 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -13,25 +13,26 @@ Here are some scenarios which demonstrate some key aspects of mappers: ::: details Transferring IDs Say we have to transfer the credentials of an employee who is moving from Business A to Business B. The data formats the businesses use for IDs are as follows: -``` +```json // Business A {Name, DoB, Age, Title} // Business B {employee, employeeBirthday, employeeAge, jobTitle} ``` + How do we transfer John's credentials from Business A to Business B? -``` +```json {Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} ``` What we can do is create a mapping which correlates the items from Business A's ID scheme to Business B's: -``` +```json {employee: Name, employeeBirthday: DoB, employeeAge: Age, jobTitle: Title} ``` With this, we can then develop a mapper which takes John's credentials from Business A and transforms it to Business B's format as so: -``` +```json {Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} || @@ -56,7 +57,7 @@ Say we are given the job to translate the traditional Chinese sentence '我愛 Without knowledge of the language, this is an impossible task. However, say we now also had a mapper which utilized the following mapping: -``` +```json {'愛': 'love', '我': 'I', '貓': 'cats'} ``` @@ -85,40 +86,40 @@ Here are some key questions to keep note of while reading through these examples #### GoSec ::: details Source Data -``` +```json { - "Golang errors": {}, - "Issues": [ - { - "severity": "MEDIUM", - "confidence": "HIGH", - "cwe": { - "id": "22", - "url": "https://cwe.mitre.org/data/definitions/22.html" - }, - "rule_id": "G304", - "details": "Potential file inclusion via variable", - "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", - "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - "line": "83", - "column": "14", - "nosec": false, - "suppressions": null - } - ], - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - }, - "GosecVersion": "dev" + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + "GosecVersion": "dev" } ``` ::: ::: details Converted OHDF File -``` +```json { "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, "version": "2.10.8", @@ -174,93 +175,86 @@ Here are some key questions to keep note of while reading through these examples #### Twistlock ::: details Source Data -``` +```json { - "results": [ - { - "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", - "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", - "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", - "distroRelease": "RHEL8", - "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", - "collections": [ - "All", - "TEST-COLLECTION" - ], - "packages": [ - { - "type": "os", - "name": "nss-util", - "version": "3.67.0-7.el8_5", - "licenses": [ - "MPLv2.0" - ] - } - ], - "applications": [ - { - "name": ".net-core", - "version": "5.0.17", - "path": "/usr/lib64/dotnet/dotnet" - } - ], - "complianceDistribution": { - "critical": 0, - "high": 0, - "medium": 0, - "low": 0, - "total": 0 - }, - "complianceScanPassed": true, - "vulnerabilities": [ - { - "id": "CVE-2021-43529", - "status": "affected", - "cvss": 9.8, - "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", - "severity": "critical", - "packageName": "nss-util", - "packageVersion": "3.67.0-7.el8_5", - "link": "https://access.redhat.com/security/cve/CVE-2021-43529", - "riskFactors": [ - "Remote execution", - "Attack complexity: low", - "Attack vector: network", - "Critical severity", - "Recent vulnerability" - ], - "impactedVersions": [ - "*" - ], - "publishedDate": "2021-12-01T00:00:00Z", - "discoveredDate": "2022-05-18T12:24:22Z", - "layerTime": "2022-05-16T23:12:25Z" - } - ], - "vulnerabilityDistribution": { - "critical": 5, - "high": 1, - "medium": 86, - "low": 5, - "total": 97 - }, - "vulnerabilityScanPassed": true, - "history": [ - { - "created": "2022-05-03T08:38:31Z" - } - ], - "scanTime": "2022-05-18T12:24:32.855444532Z", - "scanID": "6284e580d9600f8d0db159e2" - } - ], - "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "collections": ["All", "TEST-COLLECTION"], + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } + ], + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceDistribution": { + "critical": 0, + "high": 0, + "medium": 0, + "low": 0, + "total": 0 + }, + "complianceScanPassed": true, + "vulnerabilities": [ + { + "id": "CVE-2021-43529", + "status": "affected", + "cvss": 9.8, + "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "severity": "critical", + "packageName": "nss-util", + "packageVersion": "3.67.0-7.el8_5", + "link": "https://access.redhat.com/security/cve/CVE-2021-43529", + "riskFactors": [ + "Remote execution", + "Attack complexity: low", + "Attack vector: network", + "Critical severity", + "Recent vulnerability" + ], + "impactedVersions": ["*"], + "publishedDate": "2021-12-01T00:00:00Z", + "discoveredDate": "2022-05-18T12:24:22Z", + "layerTime": "2022-05-16T23:12:25Z" + } + ], + "vulnerabilityDistribution": { + "critical": 5, + "high": 1, + "medium": 86, + "low": 5, + "total": 97 + }, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-03T08:38:31Z" + } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" } ``` ::: ::: details Converted OHDF File -``` +```json { "platform": { "name": "Heimdall Tools", diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index 8b6357809..6376cb3f3 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -27,7 +27,7 @@ The results structure contains information on the results of specific tes These aforementioned structures cumulatively result in the following generalized structure: -``` +```json // Data fields have been removed for the sake of demonstration profiles: [ 0: { diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index 1a8b3b279..bc7734992 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -16,7 +16,7 @@ The following section contains a breakdown of a streamlined version of the OHDF ### 1. **Profiles** ::: details Profiles Schema -``` +```json profiles: [ 0: { name, @@ -54,10 +54,34 @@ profiles: [ - `controls`: Controls substructure (see below). - `status`: Status of profile (typically 'loaded'). +#### Example + +Here's an example of a profiles section from a converted GoSec data file: + +::: details OHDF Converted GoSec Data +```json +"profiles": [ + { + "name": "Gosec scanner", + "title": "gosec", + "version": "dev", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "controls": [ + ... + ], + "sha256": "d0506f4b7715bf8b1cd81a8a87ab8efcce41ebeb2b5ec5fcfb23d3bdd136f48c" + } +] +``` +::: + ### 2. **Controls** ::: details Controls Schema -``` +```json controls: [ 0: { id, @@ -87,10 +111,43 @@ controls: [ - `source_location`: Location of control within source code. - `results`: Results substructure (see below). +#### Example + +Here's an example of a controls section from a converted GoSec data file: + +::: details OHDF Converted GoSec Data +```json +"controls": [ + { + "tags": { + "nist": ["SI-10"], + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "nosec": "", + "suppressions": "", + "severity": "MEDIUM", + "confidence": "HIGH" + }, + "refs": [], + "source_location": {}, + "title": "Potential file inclusion via variable", + "id": "G304", + "desc": "", + "impact": 0.5, + "results": [ + ... + ] + } +], +``` +::: + ### 3. **Results** ::: details Results Schema -``` +```json results: [ 0: { status, @@ -110,12 +167,29 @@ results: [ - `run_time`: Overall runtime of test. - `start_time`: Starting time of test. +#### Example + +Here's an example of a results section from a converted Twistlock data file: + +::: details OHDF Converted Twistlock Data +```json +"results": [ + { + "status": "failed", + "code_desc": "Package \"nss-util\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-util\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-util\"", + "start_time": "2022-05-18T12:24:22Z" + } +] +``` +::: + ### 4. Additional Structures There are additional structures in the OHDF schema which are used for metadata/extraneous information storage. These exist alongside the profiles structure on the top level of the HDF schema. The general structure for the top level of the HDF schema is as follows: ::: details Additional Schema -``` +```json { platform: { name, @@ -154,3 +228,62 @@ There are additional structures in the OHDF schema which are used for metadata/e - `name`: Name of auxiliary data source. - `data`: Auxiliary data. - `raw`: Raw data dump of input security service export. + +#### Example + +Here's an example of the additional structures from a converted Twistlock data file: + +::: details OHDF Converted Twistlock Data +```json +{ + "platform": { + "name": "Heimdall Tools", + "release": "2.10.8", + "target_id": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a" + }, + "version": "2.10.8", + "statistics": {}, + "profiles": [ + ... + ], + "passthrough": { + "auxiliary_data": [ + { + "name": "Twistlock", + "data": { + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } + ], + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceScanPassed": true, + "vulnerabilityScanPassed": true, + "history": [{ "created": "2022-05-03T08:38:31Z" }], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" + } + } + ] + } +} +``` +::: diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md index 6771008d6..b955b1f01 100644 --- a/src/courses/mappers/07.md +++ b/src/courses/mappers/07.md @@ -14,7 +14,7 @@ Note that just because you can skip a schema field does not mean that you should The fields that are specifically required by the schema are as follows: ::: details Required Fields -``` +```json { platform: { name, @@ -55,7 +55,7 @@ The fields that are specifically required by the schema are as follows: The required fields in context of the full schema are shown below: ::: details Full Schema -``` +```json { platform: { // required field name, // required field @@ -117,3 +117,94 @@ The required fields in context of the full schema are shown below: } ``` ::: + +## Example + +Here's an example of GoSec source data and the converted OHDF file that has been annotated to show the required fields. + +::: details Source Data +```json +{ + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + "GosecVersion": "dev" +} +``` +::: + +::: details Converted OHDF File +```json +{ + "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, + "version": "2.10.8", + "statistics": {}, + "profiles": [ + { + "name": "Gosec scanner", + "title": "gosec", + "version": "dev", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "controls": [ + { + "tags": { + "nist": ["SI-10"], + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "nosec": "", + "suppressions": "", + "severity": "MEDIUM", + "confidence": "HIGH" + }, + "refs": [], + "source_location": {}, + "title": "Potential file inclusion via variable", + "id": "G304", + "desc": "", + "impact": 0.5, + "results": [ + { + "status": "failed", + "code_desc": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "message": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go, line:83, column:14", + "start_time": "" + } + ] + } + ], + "sha256": "d0506f4b7715bf8b1cd81a8a87ab8efcce41ebeb2b5ec5fcfb23d3bdd136f48c" + } + ], + "passthrough": { + "auxiliary_data": [{ "name": "Gosec", "data": { "Golang errors": {} } }] + } +} +``` +::: diff --git a/src/courses/mappers/08.md b/src/courses/mappers/08.md new file mode 100644 index 000000000..6c944e023 --- /dev/null +++ b/src/courses/mappers/08.md @@ -0,0 +1,275 @@ +--- +order: 8 +next: 09.md +title: OHDF Schema Review +author: Charles Hu +--- + +## OHDF Schema Review + + + +### GoSec + +::: details Source Data +``` +{ + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + "GosecVersion": "dev" +} +``` +::: + +::: details Converted OHDF File +``` +{ + "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, + "version": "2.10.8", + "statistics": {}, + "profiles": [ + { + "name": "Gosec scanner", + "title": "gosec", + "version": "dev", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "controls": [ + { + "tags": { + "nist": ["SI-10"], + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "nosec": "", + "suppressions": "", + "severity": "MEDIUM", + "confidence": "HIGH" + }, + "refs": [], + "source_location": {}, + "title": "Potential file inclusion via variable", + "id": "G304", + "desc": "", + "impact": 0.5, + "results": [ + { + "status": "failed", + "code_desc": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "message": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go, line:83, column:14", + "start_time": "" + } + ] + } + ], + "sha256": "d0506f4b7715bf8b1cd81a8a87ab8efcce41ebeb2b5ec5fcfb23d3bdd136f48c" + } + ], + "passthrough": { + "auxiliary_data": [{ "name": "Gosec", "data": { "Golang errors": {} } }] + } +} +``` +::: + +### Twistlock + +::: details Source Data +``` +{ + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "collections": [ + "All", + "TEST-COLLECTION" + ], + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": [ + "MPLv2.0" + ] + } + ], + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceDistribution": { + "critical": 0, + "high": 0, + "medium": 0, + "low": 0, + "total": 0 + }, + "complianceScanPassed": true, + "vulnerabilities": [ + { + "id": "CVE-2021-43529", + "status": "affected", + "cvss": 9.8, + "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "severity": "critical", + "packageName": "nss-util", + "packageVersion": "3.67.0-7.el8_5", + "link": "https://access.redhat.com/security/cve/CVE-2021-43529", + "riskFactors": [ + "Remote execution", + "Attack complexity: low", + "Attack vector: network", + "Critical severity", + "Recent vulnerability" + ], + "impactedVersions": [ + "*" + ], + "publishedDate": "2021-12-01T00:00:00Z", + "discoveredDate": "2022-05-18T12:24:22Z", + "layerTime": "2022-05-16T23:12:25Z" + } + ], + "vulnerabilityDistribution": { + "critical": 5, + "high": 1, + "medium": 86, + "low": 5, + "total": 97 + }, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-03T08:38:31Z" + } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" +} +``` +::: + +::: details Converted OHDF File +``` +{ + "platform": { + "name": "Heimdall Tools", + "release": "2.10.8", + "target_id": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a" + }, + "version": "2.10.8", + "statistics": {}, + "profiles": [ + { + "name": "Twistlock Scan", + "title": "Twistlock Project: All / TEST-COLLECTION", + "summary": "Package Vulnerability Summary: 97 Application Compliance Issue Total: 0", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "controls": [ + { + "tags": { + "nist": ["SI-2", "RA-5"], + "cci": ["CCI-002605", "CCI-001643"], + "cveid": "CVE-2021-43529" + }, + "refs": [], + "source_location": {}, + "title": "CVE-2021-43529", + "id": "CVE-2021-43529", + "desc": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "impact": 0.9, + "code": "{\n \"id\": \"CVE-2021-43529\",\n \"status\": \"affected\",\n \"cvss\": 9.8,\n \"description\": \"DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec\",\n \"severity\": \"critical\",\n \"packageName\": \"nss-util\",\n \"packageVersion\": \"3.67.0-7.el8_5\",\n \"link\": \"https://access.redhat.com/security/cve/CVE-2021-43529\",\n \"riskFactors\": [\n \"Remote execution\",\n \"Attack complexity: low\",\n \"Attack vector: network\",\n \"Critical severity\",\n \"Recent vulnerability\"\n ],\n \"impactedVersions\": [\n \"*\"\n ],\n \"publishedDate\": \"2021-12-01T00:00:00Z\",\n \"discoveredDate\": \"2022-05-18T12:24:22Z\",\n \"layerTime\": \"2022-05-16T23:12:25Z\"\n}", + "results": [ + { + "status": "failed", + "code_desc": "Package \"nss-util\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-util\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-util\"", + "start_time": "2022-05-18T12:24:22Z" + } + ] + } + ], + "sha256": "998180601124e9d2b4f03be239a5bb68d9045ba2dc5a26fa2c8d453500288b2e" + } + ], + "passthrough": { + "auxiliary_data": [ + { + "name": "Twistlock", + "data": { + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } + ], + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceScanPassed": true, + "vulnerabilityScanPassed": true, + "history": [{ "created": "2022-05-03T08:38:31Z" }], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" + } + } + ] + } +} +``` +::: From c712fe543a33cab82d0b00bc3e1c81ff231eca1b Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Thu, 13 Jun 2024 12:20:33 -0400 Subject: [PATCH 18/71] Frameworking Signed-off-by: Charles Hu --- src/courses/mappers/07.md | 65 +++++++----- src/courses/mappers/08.md | 211 ++++++++++++++++++-------------------- src/courses/mappers/09.md | 8 ++ src/courses/mappers/10.md | 8 ++ src/courses/mappers/11.md | 8 ++ 5 files changed, 163 insertions(+), 137 deletions(-) create mode 100644 src/courses/mappers/09.md create mode 100644 src/courses/mappers/10.md create mode 100644 src/courses/mappers/11.md diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md index b955b1f01..7e6bdd197 100644 --- a/src/courses/mappers/07.md +++ b/src/courses/mappers/07.md @@ -120,7 +120,13 @@ The required fields in context of the full schema are shown below: ## Example -Here's an example of GoSec source data and the converted OHDF file that has been annotated to show the required fields. +Here's an example of GoSec source data and the converted OHDF file that has been annotated to show the required/not required fields. + +Here are some key questions to keep note of while reading through the example: + +- Why is a required field filled/unfilled? +- Why is an unrequired field filled/unfilled? +- Is there an appropriate field from the source data to fill in an unfilled field in the OHDF file? ::: details Source Data ```json @@ -158,21 +164,24 @@ Here's an example of GoSec source data and the converted OHDF file that has been ::: details Converted OHDF File ```json { - "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, - "version": "2.10.8", - "statistics": {}, - "profiles": [ + "platform": { // required + "name": "Heimdall Tools", // required + "release": "2.10.8" // required + }, + "version": "2.10.8", // required + "statistics": {}, // required + "profiles": [ // required { - "name": "Gosec scanner", - "title": "gosec", - "version": "dev", - "supports": [], - "attributes": [], - "groups": [], - "status": "loaded", - "controls": [ + "name": "Gosec scanner", // required + "title": "gosec", // not required + "version": "dev", // not required + "supports": [], // required + "attributes": [], // required + "groups": [], // required + "status": "loaded", // not required + "controls": [ // required { - "tags": { + "tags": { // required "nist": ["SI-10"], "cwe": { "id": "22", @@ -183,27 +192,27 @@ Here's an example of GoSec source data and the converted OHDF file that has been "severity": "MEDIUM", "confidence": "HIGH" }, - "refs": [], - "source_location": {}, - "title": "Potential file inclusion via variable", - "id": "G304", - "desc": "", - "impact": 0.5, - "results": [ + "refs": [], // required + "source_location": {}, // required + "title": "Potential file inclusion via variable", // not required + "id": "G304", // required + "desc": "", // not required + "impact": 0.5, // required + "results": [ // required { - "status": "failed", - "code_desc": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - "message": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go, line:83, column:14", - "start_time": "" + "status": "failed", // not required + "code_desc": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", // required + "message": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go, line:83, column:14", // not required + "start_time": "" // required } ] } ], - "sha256": "d0506f4b7715bf8b1cd81a8a87ab8efcce41ebeb2b5ec5fcfb23d3bdd136f48c" + "sha256": "d0506f4b7715bf8b1cd81a8a87ab8efcce41ebeb2b5ec5fcfb23d3bdd136f48c" // required } ], - "passthrough": { - "auxiliary_data": [{ "name": "Gosec", "data": { "Golang errors": {} } }] + "passthrough": { // not required + "auxiliary_data": [{ "name": "Gosec", "data": { "Golang errors": {} } }] // not required } } ``` diff --git a/src/courses/mappers/08.md b/src/courses/mappers/08.md index 6c944e023..14b2888f3 100644 --- a/src/courses/mappers/08.md +++ b/src/courses/mappers/08.md @@ -12,40 +12,40 @@ author: Charles Hu ### GoSec ::: details Source Data -``` +```json { - "Golang errors": {}, - "Issues": [ - { - "severity": "MEDIUM", - "confidence": "HIGH", - "cwe": { - "id": "22", - "url": "https://cwe.mitre.org/data/definitions/22.html" - }, - "rule_id": "G304", - "details": "Potential file inclusion via variable", - "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", - "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - "line": "83", - "column": "14", - "nosec": false, - "suppressions": null - } - ], - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - }, - "GosecVersion": "dev" + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + "GosecVersion": "dev" } ``` ::: ::: details Converted OHDF File -``` +```json { "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, "version": "2.10.8", @@ -101,93 +101,86 @@ author: Charles Hu ### Twistlock ::: details Source Data -``` +```json { - "results": [ - { - "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", - "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", - "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", - "distroRelease": "RHEL8", - "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", - "collections": [ - "All", - "TEST-COLLECTION" - ], - "packages": [ - { - "type": "os", - "name": "nss-util", - "version": "3.67.0-7.el8_5", - "licenses": [ - "MPLv2.0" - ] - } - ], - "applications": [ - { - "name": ".net-core", - "version": "5.0.17", - "path": "/usr/lib64/dotnet/dotnet" - } - ], - "complianceDistribution": { - "critical": 0, - "high": 0, - "medium": 0, - "low": 0, - "total": 0 - }, - "complianceScanPassed": true, - "vulnerabilities": [ - { - "id": "CVE-2021-43529", - "status": "affected", - "cvss": 9.8, - "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", - "severity": "critical", - "packageName": "nss-util", - "packageVersion": "3.67.0-7.el8_5", - "link": "https://access.redhat.com/security/cve/CVE-2021-43529", - "riskFactors": [ - "Remote execution", - "Attack complexity: low", - "Attack vector: network", - "Critical severity", - "Recent vulnerability" - ], - "impactedVersions": [ - "*" - ], - "publishedDate": "2021-12-01T00:00:00Z", - "discoveredDate": "2022-05-18T12:24:22Z", - "layerTime": "2022-05-16T23:12:25Z" - } - ], - "vulnerabilityDistribution": { - "critical": 5, - "high": 1, - "medium": 86, - "low": 5, - "total": 97 - }, - "vulnerabilityScanPassed": true, - "history": [ - { - "created": "2022-05-03T08:38:31Z" - } - ], - "scanTime": "2022-05-18T12:24:32.855444532Z", - "scanID": "6284e580d9600f8d0db159e2" - } - ], - "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "collections": ["All", "TEST-COLLECTION"], + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } + ], + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceDistribution": { + "critical": 0, + "high": 0, + "medium": 0, + "low": 0, + "total": 0 + }, + "complianceScanPassed": true, + "vulnerabilities": [ + { + "id": "CVE-2021-43529", + "status": "affected", + "cvss": 9.8, + "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "severity": "critical", + "packageName": "nss-util", + "packageVersion": "3.67.0-7.el8_5", + "link": "https://access.redhat.com/security/cve/CVE-2021-43529", + "riskFactors": [ + "Remote execution", + "Attack complexity: low", + "Attack vector: network", + "Critical severity", + "Recent vulnerability" + ], + "impactedVersions": ["*"], + "publishedDate": "2021-12-01T00:00:00Z", + "discoveredDate": "2022-05-18T12:24:22Z", + "layerTime": "2022-05-16T23:12:25Z" + } + ], + "vulnerabilityDistribution": { + "critical": 5, + "high": 1, + "medium": 86, + "low": 5, + "total": 97 + }, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-03T08:38:31Z" + } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" } ``` ::: ::: details Converted OHDF File -``` +```json { "platform": { "name": "Heimdall Tools", diff --git a/src/courses/mappers/09.md b/src/courses/mappers/09.md new file mode 100644 index 000000000..587980355 --- /dev/null +++ b/src/courses/mappers/09.md @@ -0,0 +1,8 @@ +--- +order: 9 +next: 10.md +title: Getting Started - OHDF Converters +author: Charles Hu +--- + + diff --git a/src/courses/mappers/10.md b/src/courses/mappers/10.md new file mode 100644 index 000000000..ff874681b --- /dev/null +++ b/src/courses/mappers/10.md @@ -0,0 +1,8 @@ +--- +order: 10 +next: 11.md +title: Getting Started - The Art of Mapper Making +author: Charles Hu +--- + + diff --git a/src/courses/mappers/11.md b/src/courses/mappers/11.md new file mode 100644 index 000000000..0a3131870 --- /dev/null +++ b/src/courses/mappers/11.md @@ -0,0 +1,8 @@ +--- +order: 11 +next: 12.md +title: Getting Started - Setting Up +author: Charles Hu +--- + + From 199f5e22c74c666fc565b54016590a37c6cd8e77 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Thu, 13 Jun 2024 15:10:01 -0400 Subject: [PATCH 19/71] Part of getting started section Signed-off-by: Charles Hu --- src/courses/mappers/08.md | 15 ++++++ src/courses/mappers/09.md | 100 ++++++++++++++++++++++++++++++++++++++ src/courses/mappers/11.md | 48 ++++++++++++++++++ 3 files changed, 163 insertions(+) diff --git a/src/courses/mappers/08.md b/src/courses/mappers/08.md index 14b2888f3..5dd1a2d31 100644 --- a/src/courses/mappers/08.md +++ b/src/courses/mappers/08.md @@ -7,7 +7,20 @@ author: Charles Hu ## OHDF Schema Review +Now that you've familiarized yourself with the formal OHDF schema, let's revisit the GoSec and Twistlock examples and apply some of that knowledge. +Here are some key questions to keep note of while reading through these examples: + +- How is the structure of the source data interpreted to fit the OHDF hierarchy? + - What groups of fields in the source data correlate to our profiles, controls, and results structures? +- Which fields in the source data are used to fill each OHDF field? Is that mapping accurate? + - Can you think of a reason for why that field is used to generate the OHDF field? + - Are there any fields in the source data that you believe are more applicable? Why? +- Which fields are unfilled/omitted? + - Can you think of a reason for why that field is unfilled/omitted? + - Are there any fields in the source data that you believe are applicable? Why? + +These questions will help you understand the conversion process for when you create your own OHDF mappers later. ### GoSec @@ -266,3 +279,5 @@ author: Charles Hu } ``` ::: + +More examples of actual OHDF samples used in production can be [found here](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters/sample_jsons). diff --git a/src/courses/mappers/09.md b/src/courses/mappers/09.md index 587980355..6b8db59d9 100644 --- a/src/courses/mappers/09.md +++ b/src/courses/mappers/09.md @@ -5,4 +5,104 @@ title: Getting Started - OHDF Converters author: Charles Hu --- +## An Overview of OHDF Converters +OHDF Converters is the library that hosts and provides OHDF mappers to other applications in the SAF tool suite. It is important to have a general understanding of a few key features of OHDF Converters as the mappers you develop will be integrated here and leverage the library's utilities. + +### Features + +- Implements OHDF mappers to transform security data formats to and from OHDF. +- Special keyword functions provided by the base-converter class. +- Fingerprinting services for automatic data format identification. + +### Keywords + +base-converter is an underlying class which enables \*-to-HDF mapping in OHDF Converters. It defines \*-to-HDF mappers and provides critical tools in the form of keywords which allow for the construction of such mappers. All \*-to-HDF mappers inherit from this class and therefore have access to the keywords that this class provides. You should aim to utilize these keywords to their fullest potential to ease and simplify mapper development. The provided tools are as follows: + +- `path`: Define JSON object path to go to. Paths are found recursively. + - Use: + ```typescript + path: PATH_AS_STRING + ``` + - Example: + ```typescript + // Attribute 'id' will be set as whatever JSON object attribute 'vulnerability.id' is + id: {path: 'vulnerability.id'} + ``` + +- `transformer`: Execute given code sequence; operates similar to an anonymous function. + - Use: + ```typescript + transformer: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} + ``` + - Example: + ```typescript + // Attribute 'cci' will be set as the returned CCI tag from the ingested 'data' argument + cci: { + path: 'vulnerabilityClassifications', + transformer: (data: string) => getCCIsForNISTTags(nistTag(data)) + } + ``` + +- `arrayTransformer`: Execute given code sequence on a given array; primarily used when in an attribute that is an array of objects. + - Use: + ```typescript + arrayTransformer: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} + ``` + - Example: + ```typescript + // The function 'deduplicateId' will run against all items in the current array that the 'arrayTransformer' was called inside + arrayTransformer: deduplicateId + ``` + +- `pathTransform`: Converts the JSON object path structure. + - Use: + ```typescript + pathTransform: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} + ``` + - Example: + ```typescript + // Returns the JSON path if it is an array, otherwise returns an empty array + pathTransform: (value) => (Array.isArray(value) ? value : []), + ``` + +- `key`: Used by base-converter to sort an array of objects by + - Use: + ```typescript + key: KEY_AS_STRING + ``` + - Example: + ```typescript + // 'id' is now the key by which this array will be sorted by + key: 'id' + ``` + +### Directory Structure + +The following is a simplified depiction of the directory tree for the HDF Converter. Only noteworthy and potentially useful files and directories are included. It is not imperative to memorize the structure, but it is useful to familiarize yourself with it to better understand what exists where within the HDF Converter for future reference. + +``` +hdf-converters ++-- data +| +-- converters +| | +-- csv2json.ts +| | +-- xml2json.ts ++-- sample_jsons // Sample exports for mapper testing are located here ++-- src // *-to-HDF mappers are located here +| +-- converters-from-hdf // HDF-to-* mappers are located here +| | +-- reverse-any-base-converter.ts +| | +-- reverse-base-converter.ts +| +-- mappings // Non-HDF mappers are located here (e.g., CVE, CCI, NIST) +| +-- utils +| | +-- fingerprinting.ts +| | +-- global.ts +| +-- base-converter.ts ++-- test // Mapper tests are located here +| +-- mappers +| | +-- forward // *-to-HDF tests +| | +-- reverse // HDF-to-* tests +| | +-- utils.ts ++-- types // Explicit data typing for known export schemas ++-- index.ts ++-- package.json +``` diff --git a/src/courses/mappers/11.md b/src/courses/mappers/11.md index 0a3131870..a427a8749 100644 --- a/src/courses/mappers/11.md +++ b/src/courses/mappers/11.md @@ -5,4 +5,52 @@ title: Getting Started - Setting Up author: Charles Hu --- +## Environment Set Up + +Node.js (a runtime environment for Javascript) and Yarn (a package manager for Node.js) are external utilities which are utilized extensively within this guide. The following section details their installation process. + +Linux/Mac OS: + +1. Install [nvm](https://github.com/nvm-sh/nvm#install--update-script). + + - 1a. Use either of the following commands to install nvm: + ```shell + curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash + ``` + ```shell + wget -qO- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash + ``` + + - 1b. Either restart the terminal or run the following commands to use nvm: + ```shell + export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")" + [ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh" # This loads nvm + ``` + +2. Run the following command to install and use Node.js v18: +```shell +nvm install 18 +``` + +3. Install [Yarn](https://yarnpkg.com/getting-started/install) + +Windows: + +1. Install [Node.js v18 via the installer](https://nodejs.org/en/download/). + +2. Install [Yarn](https://yarnpkg.com/getting-started/install): + +## Repository Set Up + +1. Fork/branch a development repository from the main [Heimdall2 GitHub repository](https://github.com/mitre/heimdall2). + + - SAF team developers have write access to the main repository and should [create a branch](https://docs.github.com/en/desktop/contributing-and-collaborating-using-github-desktop/making-changes-in-a-branch/managing-branches#creating-a-branch) on the primary development repository. Non-SAF team developers should instead [create a fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo#forking-a-repository) of the main repository and create a development branch there. + +2. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. + +3. Install the necessary dependencies for Heimdall2. Under the heimdall2 directory, enter the following command in the terminal: +``` shell +yarn install +``` + From dfabf771deb98c52359222a3843e2305d5685e8a Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 17 Jun 2024 10:25:22 -0400 Subject: [PATCH 20/71] Mapper development progress/wip reworks Signed-off-by: Charles Hu --- src/courses/mappers/10.md | 36 +++++ src/courses/mappers/11.md | 6 +- src/courses/mappers/12.md | 26 ++++ src/courses/mappers/13.md | 318 ++++++++++++++++++++++++++++++++++++++ src/courses/mappers/14.md | 105 +++++++++++++ src/courses/mappers/15.md | 127 +++++++++++++++ src/courses/mappers/16.md | 7 + src/courses/mappers/17.md | 19 +++ 8 files changed, 640 insertions(+), 4 deletions(-) create mode 100644 src/courses/mappers/12.md create mode 100644 src/courses/mappers/13.md create mode 100644 src/courses/mappers/14.md create mode 100644 src/courses/mappers/15.md create mode 100644 src/courses/mappers/16.md create mode 100644 src/courses/mappers/17.md diff --git a/src/courses/mappers/10.md b/src/courses/mappers/10.md index ff874681b..ac557b5a7 100644 --- a/src/courses/mappers/10.md +++ b/src/courses/mappers/10.md @@ -5,4 +5,40 @@ title: Getting Started - The Art of Mapper Making author: Charles Hu --- +## The Art of Mapper Making +Mapper creation is an inherently tricky process as every situation demands a unique and tailored solution. As a result, there is no one objective best template or process to follow as schema translations will always be designed on a case-by-case basis. + +But don't fret! Mapper making, like many forms of development, is a skill you have to cultivate and improve at. So while there is no one-size-fits-all solution, you can still train yourself to produce mappers that are the best for your needs and uses. + +To help in improving your mapper making skills, the following section details a number of tips and best practices for mapper development that you should keep in mind while creating your mapper. + +## Mapper Making Best Practices + +### 1. Reach Out + +Don't be afraid to reach out to the SAF team for assistance with mapper development. Our developers can help you with everything from schema mapping decisions to mapper integration with OHDF Converters. + +You can contact us through email (saf@groups.mitre.org) for inquiries and by creating a [GitHub issue on the Heimdall2 repository](https://github.com/mitre/heimdall2/issues/new/choose) for technical implementation issues. + +### 2. Reference Existing Solutions + +Try to browse and reference existing solutions in [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) to glean some insight to how previous schema mappers were implemented. Through this, you might be able to find potential solutions to issues you encounter while making your mapper. + +### 3. Understand Your Security Tool and Data + +Understand how your security data is meant to be consumed in the original security tool's use case (i.e., don't just start development with the raw security data). Ask yourself the following questions: + +- How does the original security tool vendor group security data? Is it by type of concern? Where/what component was affected? +- What associations does the tool make to common security references (e.g., NIST SP 800-53, CVE, CWE, CCE, OWASP, STIG IDs)? +- What is the purpose of the security tool (vulnerability scanning, information visualization, etc.)? + +These answers will help ensure that the intent of the data isn't skewed by the mapping process. It is important to try and "seek parity" with the original display style in the vendor's own tool. In other words, users must be able to recognize and navigate the security data in Heimdall just as easily as they can in the original native format. + +### 4. Use a Detailed Sample + +::: note APIs +If your security tool provides an API instead of a security data export, contact the SAF team for further guidance in creating a specialized mapper that works with that API. +::: + +Build your mapper around a sample output that is the most detailed the tool can provide, and try to obtain the data in any machine-readable format (e.g., JSON, XML, CSV) that is natively available. Also try to sanitize your data sample so that it is safe for public release in the OHDF Converters GitHub repository. diff --git a/src/courses/mappers/11.md b/src/courses/mappers/11.md index a427a8749..f881ff143 100644 --- a/src/courses/mappers/11.md +++ b/src/courses/mappers/11.md @@ -7,7 +7,7 @@ author: Charles Hu ## Environment Set Up -Node.js (a runtime environment for Javascript) and Yarn (a package manager for Node.js) are external utilities which are utilized extensively within this guide. The following section details their installation process. +Node.js (a runtime environment for JavaScript/TypeScript) and Yarn (a package manager for JavaScript/TypeScript) are external utilities which are utilized extensively within this guide. The following section details their installation process. Linux/Mac OS: @@ -48,9 +48,7 @@ Windows: 2. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. -3. Install the necessary dependencies for Heimdall2. Under the heimdall2 directory, enter the following command in the terminal: +3. Install the necessary dependencies for Heimdall2. Under the `heimdall2` directory, enter the following command in the terminal: ``` shell yarn install ``` - - diff --git a/src/courses/mappers/12.md b/src/courses/mappers/12.md new file mode 100644 index 000000000..b6181e24d --- /dev/null +++ b/src/courses/mappers/12.md @@ -0,0 +1,26 @@ +--- +order: 12 +next: 13.md +title: Demo - Introduction +author: Charles Hu +--- + +## Demo Introduction + +Now that you've finished learning about OHDF and setting up your environment, we can start creating some OHDF mappers. + +The rest of this course will consist of practice examples demonstrating and explaining the what's, how's and why's of OHDF mapper creation with a focus on practical examples derived from mappers used in a production setting. You are encouraged to actively follow along with the examples and recreate them in your own environment. + +The following is an index of the remaining walkthrough portion of the course: + +1. Mapping a Schema + - Material type: Conceptual + - Requirement(s): OHDF schema knowledge, security tool schema knowledge +2. Implementing a Mapper + - Material type: Practical + - Requirement(s): TypeScript, OHDF schema knowledge +3. Finalizing the Mapper + - Material type: Practical + - Requirement(s): TypeScript, file format (e.g., JSON, XML, CSV) knowledge +4. More Practice +5. Next Steps diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md new file mode 100644 index 000000000..dc3c68b68 --- /dev/null +++ b/src/courses/mappers/13.md @@ -0,0 +1,318 @@ +--- +order: 13 +next: 14.md +title: Demo - Mapping a Schema +author: Charles Hu +--- + +## Mapping Introduction + +::: note Security Tool Type +This walkthrough is targeted at converting security scans to OHDF. If your security tool provides exports that are not security scans or are APIs, contact the SAF team for further instruction on how to develop those services into a OHDF mapper. +::: + +We begin the creation of every OHDF mapper by first planning out how we want correlate the fields in the OHDF and security tool's schemas. This mapping is important for the following reasons: + +1. It gives us a good framework for guiding how we actually implement the *-to-OHDF mapper. +2. It notifies us of potential knowledge gaps we may have of a security tool's schema. We need to close these gaps as best as we can in order to ensure that we can create schema field correlations that are as accurate/applicable as possible. +3. + +## + + +WORKING TO REFACTOR FOLLOWING SECTION + +[placeholder] +The following is an example of a high-level mapping from the Twistlock file format to the HDF. The purpose of this demonstration is to give an easy, non-technical approach to generating a prototype for \*-to-HDF mappers that can be used as a guideline for the development of actual technical mappers for the HDF Converter. This process is generally recommended as the first step for the development of any mapper for the HDF Converter. + +(NOTE: The format used by your export may not match the one being used in this demonstration. The mappings used in this example are for demonstration purposes and should not be taken as a definitive resource; creative interpretation is necessary for the most accurate mapping according to the specifics of your security service export.) + +Given a sample Twistlock scan export (as seen below), our goal is to roughly identify and group data fields according to our 3 primary structures in HDF (profiles, controls, and results) and the non-applicable structure (passthrough). For profiles, we want to find metadata; for controls, we want to find general security control information; for results, we want to find specific security control testing information; and we can place everything else into passthrough. + +``` +//Sample Twistlock scan export +{ + "results": [ + { + "id": "sha256:111", + "name": "registry.io/test", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:222", + "collections": [ + "All", + "TEST-COLLECTION" + ], + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": [ + "MPLv2.0" + ] + } + ], + "vulnerabilities": [ + { + "id": "CVE-2021-43529", + "status": "affected", + "cvss": 9.8, + "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "severity": "critical", + "packageName": "nss-util", + "packageVersion": "3.67.0-7.el8_5", + "link": "https://access.redhat.com/security/cve/CVE-2021-43529", + "riskFactors": [ + "Remote execution", + "Attack complexity: low", + "Attack vector: network", + "Critical severity", + "Recent vulnerability" + ], + "impactedVersions": [ + "*" + ], + "publishedDate": "2021-12-01T00:00:00Z", + "discoveredDate": "2022-05-18T12:24:22Z", + "layerTime": "2022-05-16T23:12:25Z" + } + ], + "vulnerabilityDistribution": { + "critical": 1, + "high": 0, + "medium": 0, + "low": 0, + "total": 1 + }, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-03T08:38:31Z" + }, + { + "created": "2022-05-03T08:39:27Z" + } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "asdfghjkl" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%333" +} +``` + +Thus, upon successive passes we can roughly outline what we expect each data field in the Twistlock scan export to correlate to in the HDF. We first want to identify metadata which will most likely belong in the profiles structure. Such data fields will primarily be related to the general security scan itself or be related to the target system that is being scanned, as seen below: + +``` +//Data values are removed for visual clarity +{ + "results": [ + { + "id", //Scan target metadata -> profiles + "name", // + "distro", // + "distroRelease", // + "digest", // + "collections", // + "packages": [], // + "vulnerabilities": [ + { + "id", + "status", + "cvss", + "description", + "severity", + "packageName", + "packageVersion", + "link", + "riskFactors": [], + "impactedVersions": [], + "publishedDate", + "discoveredDate", + "layerTime" + } + ], + "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles + "vulnerabilityScanPassed", // + "history": [], //Scan target package install history -> profiles + "scanTime", //Twistlock scan metadata -> profiles + "scanID" // + } + ], + "consoleURL" //Twistlock scan metadata -> profiles +} +``` + +Next, we want to roughly outline general security control information that correlates to our controls structure. For this, we want to look for information that provides a background for the tests performed by the security service. Usually, this strongly correlates to information that gives us a why, what, and how for the tests that are performed, as seen with the fields that are highlighted below: + +``` +//Data values are removed for visual clarity +{ + "results": [ + { + "id", //Scan target metadata -> profiles + "name", // + "distro", // + "distroRelease", // + "digest", // + "collections", // + "packages": [], // + "vulnerabilities": [ + { + "id", //ID of control tested against -> controls + "status", + "cvss", //CVSS severity score of control -> controls + "description", //Description of control -> controls + "severity", //Severity of control failure -> controls + "packageName", + "packageVersion", + "link", //Link to control documentation -> controls + "riskFactors": [], + "impactedVersions": [], + "publishedDate", //Control discovery date -> controls + "discoveredDate", + "layerTime" + } + ], + "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles + "vulnerabilityScanPassed", // + "history": [], //Scan target package install history -> profiles + "scanTime", //Twistlock scan metadata -> profiles + "scanID" // + } + ], + "consoleURL" //Twistlock scan metadata -> profiles +} +``` + +After that, we want to outline items that relate to specific instances of control tests ran against the scan target as part of the results structure. Usually, this strongly correlates to information that gives us a who, what, and when for the specific tests that are performed, as seen with the fields that are highlighted below: + +``` +//Data values are removed for visual clarity +{ + "results": [ + { + "id", //Scan target metadata -> profiles + "name", // + "distro", // + "distroRelease", // + "digest", // + "collections", // + "packages": [], // + "vulnerabilities": [ + { + "id", //ID of control tested against -> controls + "status", //Pass/fail result of the control test -> results + "cvss", //CVSS severity score of control -> controls + "description", //Description of control -> controls + "severity", //Severity of control failure -> controls + "packageName", //Package ran against control test -> results + "packageVersion", //Version of package ran against control test -> results + "link", //Link to control documentation -> controls + "riskFactors": [], //Risk factors associated with failing this specific control test -> results + "impactedVersions": [], //Vulnerable versions of package ran against control test -> results + "publishedDate", //Control discovery date -> controls + "discoveredDate", //Date this control result was discovered -> results + "layerTime" + } + ], + "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles + "vulnerabilityScanPassed", // + "history": [], //Scan target package install history -> profiles + "scanTime", //Twistlock scan metadata -> profiles + "scanID" // + } + ], + "consoleURL" //Twistlock scan metadata -> profiles +} +``` + +For fields that we cannot reasonably categorize or have no information about, we can instead just place them into the passthrough structure, as seen below: + +``` +//Data values are removed for visual clarity +{ + "results": [ + { + "id", //Scan target metadata -> profiles + "name", // + "distro", // + "distroRelease", // + "digest", // + "collections", // + "packages": [], // + "vulnerabilities": [ + { + "id", //ID of control tested against -> controls + "status", //Pass/fail result of the control test -> results + "cvss", //CVSS severity score of control -> controls + "description", //Description of control -> controls + "severity", //Severity of control failure -> controls + "packageName", //Package ran against control test -> results + "packageVersion", //Version of package ran against control test -> results + "link", //Link to control documentation -> controls + "riskFactors": [], //Risk factors associated with failing this specific control test -> results + "impactedVersions": [], //Vulnerable versions of package ran against control test -> results + "publishedDate", //Control discovery date -> controls + "discoveredDate", //Date this control result was discovered -> results + "layerTime" //Information on package install time; extraneous -> passthrough + } + ], + "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles + "vulnerabilityScanPassed", // + "history": [], //Scan target package install history -> profiles + "scanTime", //Twistlock scan metadata -> profiles + "scanID" // + } + ], + "consoleURL" //Twistlock scan metadata -> profiles +} +``` + +With this, we now have a general outline which roughly connects each data field in the Twistlock sample export to one of our structures in the HDF. In order to improve the accuracy of this mapping, we can now begin connecting [specific fields in the HDF schema](#fullschema) with the data fields in the sample export using our rough draft as a guide. + +If we cannot find a field in the HDF schema that fits with a certain field in the sample export per our original groupings, we can instead look to the other structures to see if they have applicable fields or place the field into the passthrough structure as a last resort. + +``` +//Data values are removed for visual clarity +{ + "results": [ + { + "id", //profiles -> passthrough.auxiliary_data.data + "name", //profiles -> profiles.name + "distro", //profiles -> passthrough.auxiliary_data.data + "distroRelease", //profiles -> passthrough.auxiliary_data.data + "digest", //profiles -> passthrough.auxiliary_data.data + "collections", //profiles -> profiles.title + "packages": [], //profiles -> passthrough.auxiliary_data.data + "vulnerabilities": [ + { + "id", //controls -> profiles.controls.id + "status", //results -> profiles.controls.results.status + "cvss", //controls -> profiles.controls.code + "description", //controls -> profiles.controls.desc + "severity", //controls -> profiles.controls.impact + "packageName", //results -> profiles.controls.results.code_desc + "packageVersion", //results -> profiles.controls.results.code_desc + "link", //controls -> profiles.controls.code + "riskFactors": [], //results -> profiles.controls.code + "impactedVersions": [], //results -> profiles.controls.results.code_desc + "publishedDate", //controls -> profiles.controls.code + "discoveredDate", //results -> profiles.controls.results.start_time + "layerTime" //passthrough -> profiles.controls.code + } + ], + "vulnerabilityDistribution": {}, //profiles -> profiles.summary + "vulnerabilityScanPassed", //profiles -> passthrough.auxiliary_data.data + "history": [], //profiles -> passthrough.auxiliary_data.data + "scanTime", //profiles -> passthrough.auxiliary_data.data + "scanID" //profiles -> passthrough.auxiliary_data.data + } + ], + "consoleURL" //profiles -> passthrough.auxiliary_data.data +} +``` + +With this, we now have a detailed high-level mapping for the conversion from an external file format to the HDF, which we can use for the [technical implementation of a \*-to-HDF mapper](#create). +[placeholder] diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md new file mode 100644 index 000000000..39dfd0e00 --- /dev/null +++ b/src/courses/mappers/14.md @@ -0,0 +1,105 @@ +--- +order: 14 +next: 15.md +title: Demo - Implementing a Mapper +author: Charles Hu +--- + + +WORKING TO REFACTOR FOLLOWING SECTION + +[placeholder] + +## Mapper Creation + +### \*-to-HDF Creation Guide + + +4. Set up for \*-to-HDF mapper development. + + - 4a. + + - 4b. Create a blank TypeScript file under the src directory in hdf-converters. It should be named: + + ``` + {YOUR-EXPORT-NAME-HERE}-mapper.ts + ``` + + - 4c. Select the appropriate [mapper skeleton](#skeleton) for your export type. Place them in the file created in step 4b. Replace names (skeleton by default) as necessary. + + - 4d. Export your mapper class created in the previous steps by specifying its export in the index.ts file. Add the following line: + + ``` + export * from './src/{YOUR-EXPORT-NAME-HERE}-mapper'; + ``` + + - 4e. Create a new directory named {YOUR-EXPORT-NAME-HERE}_mapper under the sample_jsons directory in hdf-converters. Create another directory named sample_input_report in the directory you just made. The file structure should look like this: + + ``` + +-- sample_jsons + | +-- {YOUR-EXPORT-NAME-HERE}-mapper + | | +-- sample_input_report + ``` + + - 4f. Place your sample export under the sample_input_report directory. Your sample export should be genericized to avoid any leaking of sensitive information. The file structure should now look like this: + + ``` + +-- sample_jsons + | +-- {YOUR-EXPORT-NAME-HERE}-mapper + | | +-- sample_input_report + | | | +-- {YOUR-SAMPLE-EXPORT} + ``` + + - 4g. Create a blank TypeScript file under the test/mappers/forward directory in hdf-converters. It should be named: + + ``` + {YOUR-EXPORT-NAME-HERE}_mapper.spec.ts + ``` + + - 4h. Select the appropriate [mapper testing skeleton](#skeleton) for your export type. Place it in the file created in step 4g. Replace names (skeleton by default) as necessary. + +5. Add fingerprinting to identify your security service scan export. + + - 5a. Go to the file report_intake.ts under the heimdall2/apps/frontend/src/store directory. + + - 5b. Import your mapper file. You should be able to add the name of your mapper class to a pre-existing import statement pointing at hdf-converters as follows: + + ``` + import { + ASFFResults as ASFFResultsMapper, + BurpSuiteMapper, + ... + {YOUR-MAPPER-CLASS-HERE} + } from '@mitre/hdf-converters'; + ``` + + - 5c. Instantiate your mapper class in the convertToHdf switch block. Add the following lines: + + ``` + case '{YOUR-EXPORT-SERVICE-NAME-HERE}': + return new {YOUR-MAPPER-CLASS-HERE}(convertOptions.data).toHdf(); + ``` + + - 5d. Navigate to the file fingerprinting.ts in the src/utils directory in hdf-converters. Add keywords that are unique to your sample export to the fileTypeFingerprints variable. It should be formatted as follows: + + ``` + export const fileTypeFingerprints = { + asff: ['Findings', 'AwsAccountId', 'ProductArn'], + ... + {YOUR-EXPORT-SERVICE-NAME-HERE}: [{UNIQUE KEYWORDS AS STRINGS}] + }; + ``` + +6. Create the \*-to-HDF mapper. + + - 6a. Return to the {YOUR-EXPORT-NAME-HERE}-mapper.ts file. In the file, you should have a generic skeleton mapper picked according to your export type. + + - 6b. Certain security services produce exports which are not immediately usable by the skeleton mapper. In this case, pre-processing on the export and post-processing on the generated HDF file is necessary in order to ensure compatibility. + + - 6c. The skeleton mapper and [base-converter](#base) have been designed to provide the base functionality needed for \*-to-HDF mapper generation. For most developers, mapper creation will be limited to assigning objects from the export structure to correlating attributes in the mapper according to the HDF schema. + + - An example of this process is provided in the [\*-to-HDF Mapper Construction Example](#example2) section. + + - 6d. [Commit your changes](https://github.com/git-guides/git-commit) with the [signoff option](https://git-scm.com/docs/git-commit) and [push the changes](https://github.com/git-guides/git-push) to your development branch. This should queue up the Github Actions pipeline which includes a Netlify instance of Heimdall2 which you can use to test if your mapper is generating a HDF file correctly. + +[placeholder] diff --git a/src/courses/mappers/15.md b/src/courses/mappers/15.md new file mode 100644 index 000000000..4558ba66d --- /dev/null +++ b/src/courses/mappers/15.md @@ -0,0 +1,127 @@ +--- +order: 15 +next: 16.md +title: Demo - Finalizing the Mapper +author: Charles Hu +--- + +WORKING TO REFACTOR FOLLOWING SECTION + +[placeholder] + +7. Set up and use regression testing on your mapper. + + - 7a. Uncomment out the commented out lines in the {YOUR-SAMPLE-EXPORT}-hdf.json file created in step 4f. This will allow the regression tests to automatically generate a HDF output file whenever you run the tests. The commented out lines should look similar to the following: + + ``` + // fs.writeFileSync( + // 'sample_jsons/skeleton_mapper/skeleton-hdf.json', + // JSON.stringify(mapper.toHdf(), null, 2) + // ); + ``` + + - 7b. Using the terminal, cd into the hdf-converters directory and run the following command. This command will run your mapper against the sample export file in sample_jsons and test to see if the output is generated as expected. + + ``` + yarn run test --verbose --silent=false ./test/mappers/forward/{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts + ``` + + - 7c. Your tests should generate HDF output files for when --with-raw is not flagged (default behavior) and when it is flagged (denoted by -withraw in the filename). It will also compare the contents of these generated files with a temporary mapper instance created in the test itself. Review the test output to ensure that the tests are all passing and review the HDF output files to ensure that the contents of the mapping are being generated correctly. + + - 7d. Recomment out the lines from step 7b. + +8. Document your new mapper in the README for hdf-converters under the Supported Formats section. It should be formatted as follows: + +``` +{#}. [{YOUR-EXPORT-NAME-HERE}] - {MAPPER INPUT DESCRIPTION} +``` + +9. Commit your final changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, your mapper will be merged into the main development branch and [scheduled for release](https://github.com/mitre/heimdall2/wiki/How-to-create-a-Heimdall2-release) as an officially supported conversion format for the HDF Converters. + +10. Create a development branch against the [SAF CLI repository](https://github.com/mitre/saf) and create a draft pull request for your new branch. + +11. Set up for SAF CLI mapper integration. + + - 11a. In the package.json file, update the versions of @mitre/hdf-converters and @mitre/heimdall-lite to the [latest release of Heimdall2](https://github.com/mitre/heimdall2/releases). + + - 11b. In the src/commands/convert directory, create a blank TypeScript file. It should be named: + + ``` + {YOUR-EXPORT-NAME-HERE}2hdf.ts + ``` + + - 11c. In the test/sample_data directory, create a directory named {YOUR-EXPORT-NAME-HERE}. Underneath it, create a directory named sample_input_report. The file structure should now look like this: + + ``` + +-- sample_data + | +-- {YOUR-EXPORT-NAME-HERE} + | | +-- sample_input_report + ``` + + - 11d. Place your sample export under the sample_input_report directory. Your sample export should be genericized to avoid any leaking of sensitive information. Under the {YOUR-EXPORT-NAME-HERE} directory, place your output HDF files generated during the testing phase of step 7c. The file structure should now look like this: + + ``` + +-- sample_data + | +-- {YOUR-EXPORT-NAME-HERE} + | | +-- sample_input_report + | | | +-- {YOUR-SAMPLE-EXPORT} + | | +-- {YOUR-EXPORT-NAME-HERE}-hdf.json + | | +-- {YOUR-EXPORT-NAME-HERE}-hdf-withraw.json + ``` + + - 11e. In the test/commands/convert directory, create a blank TypeScript file. It should be named: + + ``` + {YOUR-EXPORT-NAME-HERE}2hdf.test.ts + ``` + +12. Integrate your mapper with the SAF CLI. + + - 12a. Insert the [skeleton](#skeleton) for integrating a HDF mapper with the SAF CLI. Replace names (skeleton by default) as necessary. + + - 12b. Insert the [skeleton](#skeleton) for a convert command test for the SAF CLI. Replace names (skeleton by default) as necessary. + + - 12c. Navigate to the index.ts file under the src/commands/convert directory. Import your mapper using the existing import block as follows: + + ``` + import { + ASFFResults, + ... + {YOUR-MAPPER-CLASS-HERE} + } from '@mitre/hdf-converters' + ``` + + - 12d. Under the switch block in the getFlagsForInputFile function, add your mapper class as it is defined in step 5d for fingerprinting for the generic convert command. If the convert command for your mapper has any additional flags beyond the standard --input and --output flags, return the entire flag block in the switch case. This is demonstrated as follows: + + ``` + switch (Convert.detectedType) { + ... + case {YOUR-EXPORT-SERVICE-NAME-HERE}: + return {YOUR-CLI-CONVERT-CLASS}.flags //Only add if special flags exist + ... + return {} + } + ``` + +13. Edit the README file to reflect your newly added conversion command under the To HDF section. It should be formatted as follows: + +``` +##### {YOUR-EXPORT-NAME-HERE} to HDF + +\``` +convert {YOUR-EXPORT-NAME-HERE}2hdf Translate a {YOUR-EXPORT-NAME-HERE} results {EXPORT-TYPE} into + a Heimdall Data Format JSON file + +OPTIONS + -i, --input=input Input {EXPORT-TYPE} File + -o, --output=output Output HDF JSON File + -w, --with-raw Include raw input file in HDF JSON file + +EXAMPLES + saf convert {YOUR-EXPORT-NAME-HERE}2hdf -i {INPUT-NAME} -o output-hdf-name.json +\``` +``` + +14. Commit your changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, merged, and [released](https://github.com/mitre/saf/wiki/Creating-a-Release-of-the-SAF-CLI), your mapper will be callable using the SAF CLI. + +[placeholder] diff --git a/src/courses/mappers/16.md b/src/courses/mappers/16.md new file mode 100644 index 000000000..22ff5ba2b --- /dev/null +++ b/src/courses/mappers/16.md @@ -0,0 +1,7 @@ +--- +order: 16 +title: Demo - More Practice +author: Charles Hu +--- + + diff --git a/src/courses/mappers/17.md b/src/courses/mappers/17.md new file mode 100644 index 000000000..dec53a97c --- /dev/null +++ b/src/courses/mappers/17.md @@ -0,0 +1,19 @@ +--- +order: 16 +title: Next Steps +author: Charles Hu +--- + +## Next Steps + +### Take Our Other Security Automation Framework Classes + +This class is part of a series of security automation content classes offered by the MITRE SAF team. If you found this content interesting and want to learn about more topics, like writing InSpec resources, we encourage you to check out the other classes provided (shown in the side bar on the left). + +### Check Out the Rest of MITRE SAF's Content + +MITRE SAF is a large collection of tools and techniques for security automation in addition to those discussed in this class. You can find utilities and libraries to support any step of the software development lifecycle by browsing our offerings at [saf.mitre.org](https://saf.mitre.org). Note that everything offered by MITRE SAF is open-source and available to use free of charge. You can also reference all of the resources listed from this class in the [Resources page](../../resources/README.md). + +### Contact Us + +The MITRE SAF team supports U.S. government sponsors in developing new tools for the Framework and implementing existing ones in DevSecOps pipelines. If you have a question about how you can use any of the content you saw in this class in your own environment, contact us at [saf@groups.mitre.org](mailto:saf@groups.mitre.org). From d116569a4a8f433ef4b4829c289106524bc3e191 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Tue, 18 Jun 2024 12:20:10 -0400 Subject: [PATCH 21/71] Schema mapping Signed-off-by: Charles Hu --- src/courses/mappers/12.md | 10 +- src/courses/mappers/13.md | 837 +++++++++++++++++++++++++++----------- src/courses/mappers/14.md | 97 ----- 3 files changed, 607 insertions(+), 337 deletions(-) diff --git a/src/courses/mappers/12.md b/src/courses/mappers/12.md index b6181e24d..d2f3a42e6 100644 --- a/src/courses/mappers/12.md +++ b/src/courses/mappers/12.md @@ -13,14 +13,14 @@ The rest of this course will consist of practice examples demonstrating and expl The following is an index of the remaining walkthrough portion of the course: -1. Mapping a Schema +1. [Mapping a Schema](./13.md) - Material type: Conceptual - Requirement(s): OHDF schema knowledge, security tool schema knowledge -2. Implementing a Mapper +2. [Implementing a Mapper](./14.md) - Material type: Practical - Requirement(s): TypeScript, OHDF schema knowledge -3. Finalizing the Mapper +3. [Finalizing the Mapper](./15.md) - Material type: Practical - Requirement(s): TypeScript, file format (e.g., JSON, XML, CSV) knowledge -4. More Practice -5. Next Steps +4. [More Practice](./16.md) +5. [Next Steps](./17.md) diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index dc3c68b68..d87436162 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -15,304 +15,671 @@ We begin the creation of every OHDF mapper by first planning out how we want cor 1. It gives us a good framework for guiding how we actually implement the *-to-OHDF mapper. 2. It notifies us of potential knowledge gaps we may have of a security tool's schema. We need to close these gaps as best as we can in order to ensure that we can create schema field correlations that are as accurate/applicable as possible. -3. +3. It gives us a chance to review our mapping of the schemas in a format that is still human readable. +4. It helps us reduce the amount of corrections and rewrites we have to perform on the actual mapper implementation due to schema mapping errors. -## +As we develop the mappings in the following examples, note that we will break down and analyze the schemas according to the OHDF schema structures we previously learned about (profiles, controls, and results). This is not necessarily the only or the best way to do this and you are encouraged to develop your own methods for correlating schemas that work best for you. +::: note Use of Exported Security Tool Data +The following examples will use generated instances of exported security tool data that do not reflect the entirety of the schemas they are based on. Ideally, you will want to use the full schema when creating a mapping; however, the full schema is typically not readily available. To reflect this, we will be using generated export data and will fill in missing schema data when possible. +::: + +## Mapping Demo - GoSec + +### 1. Breaking Down the Data -WORKING TO REFACTOR FOLLOWING SECTION +Let's first start with our GoSec sample, which you should be already familiar with: + +::: details GoSec Source Data +```json +{ + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + "GosecVersion": "dev" +} +``` +::: -[placeholder] -The following is an example of a high-level mapping from the Twistlock file format to the HDF. The purpose of this demonstration is to give an easy, non-technical approach to generating a prototype for \*-to-HDF mappers that can be used as a guideline for the development of actual technical mappers for the HDF Converter. This process is generally recommended as the first step for the development of any mapper for the HDF Converter. +We can begin our mapping process by identifying the purpose of each field in the source data according to the [schema for GoSec](https://github.com/securego/gosec/blob/master/issue/issue.go). While we do this, it's also important that we try to tie back each identified purpose to the three general OHDF schema structures that we learned about earlier; that is, in addition to finding the purpose of each field, we should also ask ourselves the following: -(NOTE: The format used by your export may not match the one being used in this demonstration. The mappings used in this example are for demonstration purposes and should not be taken as a definitive resource; creative interpretation is necessary for the most accurate mapping according to the specifics of your security service export.) +- Is this field recording meta data? +- Is this field recording requirements? +- Is this field recording requirement testing? -Given a sample Twistlock scan export (as seen below), our goal is to roughly identify and group data fields according to our 3 primary structures in HDF (profiles, controls, and results) and the non-applicable structure (passthrough). For profiles, we want to find metadata; for controls, we want to find general security control information; for results, we want to find specific security control testing information; and we can place everything else into passthrough. +To summarize, we should be asking ourselves the following two questions for each field in the source data: +- What is the purpose of this field? +- What is this field recording (meta data, requirements, requirement testing)? + +Let's apply this to our GoSec source data. Try to find the answers to these two questions for each field yourself and then refer back to our annotated solution to check your work. + +::: details GoSec Annotated Source Data +```json +{ + // Purpose: Go compilation errors + // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: Container for identified security issues + // Recording: Requirements - This entity records all identified security issues in a Go source code + "Issues": [ + { + // Purpose: The severity of the identified issue + // Recording: Requirements - This is specifically related to the severity level of the requirement + "severity": "MEDIUM", + // Purpose: How sure that the identified issue if applicable to this source code + // Recording: Requirements testing - This field gives the applicability of the issue after source code testing + "confidence": "HIGH", + // Purpose: The associated CWE for the security issue + // Recording: Requirements - This gives the associated CWE for the security issue + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + // Purpose: The internal GoSec ID for the security issue + // Recording: Requirements - This gives an ID for the security issue + "rule_id": "G304", + // Purpose: Explanation of the security issue + // Recording: Requirements - This explains the security issue + "details": "Potential file inclusion via variable", + // Purpose: The offending file + // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The offending code + // Recording: Requirement testing - This specifies the code that fails the requirement after source code testing + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + // Purpose: The line number of the offending code + // Recording: Requirement testing - This field specifies the location of the failling code + "line": "83", + // Purpose: The column number of the offending code + // Recording: Requirement testing - This field specifies the location of the failling code + "column": "14", + // Purpose: Whether this security issue should be ignored + // Recording: Requirements - Specifies whether this security issue should be ignored + "nosec": false, + // Purpose: The supression level for info on the security issue + // Recording: Requirements - Specifies the info suppression level of the security issue + "suppressions": null + } + ], + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Meta data - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + // Purpose: The version of the GoSec instance currently running + // Recording: Meta data - Info on the scan itself + "GosecVersion": "dev" +} ``` -//Sample Twistlock scan export +::: + +Note that this process is subjective and your answers may vary from ours. Don't be so quick to backtrack on your own answers, as your solutions may be as equally valid as ours. There is no objective answer to this process and what's important is that you can identify and break down the source data into useful pieces that we can correlate back to the OHDF schema. + +### 2. Correlating the Schemas + +Now that we're familiar with the specifics of the GoSec schema, we can begin to map these fields to the OHDF schema. + +Note that since we used an export from GoSec and are not basing our mapping off the full schema, we will inevitably miss some fields. We can rectify this by adding them into our mapping post hoc whenever needed; however, we can still capture these missed fields without manual intervention by using our `passthrough` field to capture unmapped data. + +Let's first start with an empty OHDF schema as follows: + +::: details Empty OHDF Schema +```typescript { - "results": [ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ { - "id": "sha256:111", - "name": "registry.io/test", - "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", - "distroRelease": "RHEL8", - "digest": "sha256:222", - "collections": [ - "All", - "TEST-COLLECTION" - ], - "packages": [ + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ { - "type": "os", - "name": "nss-util", - "version": "3.67.0-7.el8_5", - "licenses": [ - "MPLv2.0" + id, + title, + desc, + descriptions, + impact, + refs, + tags, + code, + source_location, + results: [ + { + status, + code_desc, + message, + run_time, + start_time + } ] - } - ], - "vulnerabilities": [ - { - "id": "CVE-2021-43529", - "status": "affected", - "cvss": 9.8, - "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", - "severity": "critical", - "packageName": "nss-util", - "packageVersion": "3.67.0-7.el8_5", - "link": "https://access.redhat.com/security/cve/CVE-2021-43529", - "riskFactors": [ - "Remote execution", - "Attack complexity: low", - "Attack vector: network", - "Critical severity", - "Recent vulnerability" - ], - "impactedVersions": [ - "*" - ], - "publishedDate": "2021-12-01T00:00:00Z", - "discoveredDate": "2022-05-18T12:24:22Z", - "layerTime": "2022-05-16T23:12:25Z" - } - ], - "vulnerabilityDistribution": { - "critical": 1, - "high": 0, - "medium": 0, - "low": 0, - "total": 1 - }, - "vulnerabilityScanPassed": true, - "history": [ - { - "created": "2022-05-03T08:38:31Z" }, - { - "created": "2022-05-03T08:39:27Z" - } ], - "scanTime": "2022-05-18T12:24:32.855444532Z", - "scanID": "asdfghjkl" - } + status + }, ], - "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%333" + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } } ``` +::: -Thus, upon successive passes we can roughly outline what we expect each data field in the Twistlock scan export to correlate to in the HDF. We first want to identify metadata which will most likely belong in the profiles structure. Such data fields will primarily be related to the general security scan itself or be related to the target system that is being scanned, as seen below: +We can begin our schema correlation by directly porting over fields from the GoSec source data that are obvious: `GosecVersion`, `Issues.rule_id`, `Issues.details`, `Issues.cwe`, and `Issues.code`. Try to map these fields youself as you follow along and refer to our solution to check your work. -``` -//Data values are removed for visual clarity +::: details OHDF Schema Mapping Ver. 1 +```typescript { - "results": [ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ { - "id", //Scan target metadata -> profiles - "name", // - "distro", // - "distroRelease", // - "digest", // - "collections", // - "packages": [], // - "vulnerabilities": [ + name, + version: GosecVersion, // Version of GoSec instance + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ { - "id", - "status", - "cvss", - "description", - "severity", - "packageName", - "packageVersion", - "link", - "riskFactors": [], - "impactedVersions": [], - "publishedDate", - "discoveredDate", - "layerTime" - } + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc, + descriptions, + impact, + refs, + tags: { + Issues.cwe // Associated CWE for the requirement + }, + code, + source_location, + results: [ + { + status, + code_desc: Issues.code, // The code for the requirement test + message, + run_time, + start_time + } + ] + }, ], - "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles - "vulnerabilityScanPassed", // - "history": [], //Scan target package install history -> profiles - "scanTime", //Twistlock scan metadata -> profiles - "scanID" // + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +::: details Remaining GoSec Source Data +```json +{ + // Purpose: Go compilation errors + // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: Container for identified security issues + // Recording: Requirements - This entity records all identified security issues in a Go source code + "Issues": [ + { + // Purpose: The severity of the identified issue + // Recording: Requirements - This is specifically related to the severity level of the requirement + "severity": "MEDIUM", + // Purpose: How sure that the identified issue if applicable to this source code + // Recording: Requirements testing - This field gives the applicability of the issue after source code testing + "confidence": "HIGH", + // Purpose: The offending file + // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The line number of the offending code + // Recording: Requirement testing - This field specifies the location of the failling code + "line": "83", + // Purpose: The column number of the offending code + // Recording: Requirement testing - This field specifies the location of the failling code + "column": "14", + // Purpose: Whether this security issue should be ignored + // Recording: Requirements - Specifies whether this security issue should be ignored + "nosec": false, + // Purpose: The supression level for info on the security issue + // Recording: Requirements - Specifies the info suppression level of the security issue + "suppressions": null } ], - "consoleURL" //Twistlock scan metadata -> profiles + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Meta data - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + } } ``` +::: -Next, we want to roughly outline general security control information that correlates to our controls structure. For this, we want to look for information that provides a background for the tests performed by the security service. Usually, this strongly correlates to information that gives us a why, what, and how for the tests that are performed, as seen with the fields that are highlighted below: +Note that these mapping are informal and do not need to adhere to any programming syntax. Proper implementation of these mappings will be done later in the course. -``` -//Data values are removed for visual clarity +Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.nosec`, and `Issues.suppressions`. + +::: details OHDF Schema Mapping Ver. 2 +```typescript { - "results": [ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ { - "id", //Scan target metadata -> profiles - "name", // - "distro", // - "distroRelease", // - "digest", // - "collections", // - "packages": [], // - "vulnerabilities": [ + name, + version: GosecVersion, // Version of GoSec instance + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ { - "id", //ID of control tested against -> controls - "status", - "cvss", //CVSS severity score of control -> controls - "description", //Description of control -> controls - "severity", //Severity of control failure -> controls - "packageName", - "packageVersion", - "link", //Link to control documentation -> controls - "riskFactors": [], - "impactedVersions": [], - "publishedDate", //Control discovery date -> controls - "discoveredDate", - "layerTime" - } + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc, + descriptions, + impact, + refs, + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + code, + source_location, + results: [ + { + status, + code_desc: Issues.code, // The code for the requirement test + message, + run_time, + start_time + } + ] + }, ], - "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles - "vulnerabilityScanPassed", // - "history": [], //Scan target package install history -> profiles - "scanTime", //Twistlock scan metadata -> profiles - "scanID" // + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +::: details Remaining GoSec Source Data +```json +{ + // Purpose: Go compilation errors + // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: Container for identified security issues + // Recording: Requirements - This entity records all identified security issues in a Go source code + "Issues": [ + { + // Purpose: The offending file + // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The line number of the offending code + // Recording: Requirement testing - This field specifies the location of the failling code + "line": "83", + // Purpose: The column number of the offending code + // Recording: Requirement testing - This field specifies the location of the failling code + "column": "14" } ], - "consoleURL" //Twistlock scan metadata -> profiles + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Meta data - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + } } ``` +::: -After that, we want to outline items that relate to specific instances of control tests ran against the scan target as part of the results structure. Usually, this strongly correlates to information that gives us a who, what, and when for the specific tests that are performed, as seen with the fields that are highlighted below: +We map these fields to `tags` in the OHDF schema due to each of these fields acting as descriptive traits of the control which we can categorize and sort the controls by. We won't use `Issues.severity` for `impact` as we have no concrete correlation between the two fields and as such cannot accurately convert between the two. -``` -//Data values are removed for visual clarity +Next, let's look at the fields `Issues.file`, `Issues.line`, and `Issues.column`. + +::: details OHDF Schema Mapping Ver. 3 +```typescript { - "results": [ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ { - "id", //Scan target metadata -> profiles - "name", // - "distro", // - "distroRelease", // - "digest", // - "collections", // - "packages": [], // - "vulnerabilities": [ + name, + version: GosecVersion, // Version of GoSec instance + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ { - "id", //ID of control tested against -> controls - "status", //Pass/fail result of the control test -> results - "cvss", //CVSS severity score of control -> controls - "description", //Description of control -> controls - "severity", //Severity of control failure -> controls - "packageName", //Package ran against control test -> results - "packageVersion", //Version of package ran against control test -> results - "link", //Link to control documentation -> controls - "riskFactors": [], //Risk factors associated with failing this specific control test -> results - "impactedVersions": [], //Vulnerable versions of package ran against control test -> results - "publishedDate", //Control discovery date -> controls - "discoveredDate", //Date this control result was discovered -> results - "layerTime" - } + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc, + descriptions, + impact, + refs, + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + code, + source_location, + results: [ + { + status, + code_desc: Issues.code, // The code for the requirement test + message: { // All materials describing where the issue occured + Issues.file, + Issues.line, + Issues.column + }, + run_time, + start_time + } + ] + }, ], - "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles - "vulnerabilityScanPassed", // - "history": [], //Scan target package install history -> profiles - "scanTime", //Twistlock scan metadata -> profiles - "scanID" // - } + status + }, ], - "consoleURL" //Twistlock scan metadata -> profiles + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } } ``` +::: -For fields that we cannot reasonably categorize or have no information about, we can instead just place them into the passthrough structure, as seen below: - +::: details Remaining GoSec Source Data +```json +{ + // Purpose: Go compilation errors + // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Meta data - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + } +} ``` -//Data values are removed for visual clarity +::: + +We map these fields to `message` in the OHDF schema as we can use these fields to create a verbose description of control test result. In particular, we use these fields to directly indicate to the reader where the test was performed and subsequently failed. + +Next, let's look at the fields `Golang errors` and `Stats`. + +::: details OHDF Schema Mapping Ver. 4 +```typescript { - "results": [ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ { - "id", //Scan target metadata -> profiles - "name", // - "distro", // - "distroRelease", // - "digest", // - "collections", // - "packages": [], // - "vulnerabilities": [ + name, + version: GosecVersion, // Version of GoSec instance + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ { - "id", //ID of control tested against -> controls - "status", //Pass/fail result of the control test -> results - "cvss", //CVSS severity score of control -> controls - "description", //Description of control -> controls - "severity", //Severity of control failure -> controls - "packageName", //Package ran against control test -> results - "packageVersion", //Version of package ran against control test -> results - "link", //Link to control documentation -> controls - "riskFactors": [], //Risk factors associated with failing this specific control test -> results - "impactedVersions": [], //Vulnerable versions of package ran against control test -> results - "publishedDate", //Control discovery date -> controls - "discoveredDate", //Date this control result was discovered -> results - "layerTime" //Information on package install time; extraneous -> passthrough - } + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc, + descriptions, + impact, + refs, + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + code, + source_location, + results: [ + { + status, + code_desc: Issues.code, // The code for the requirement test + message: { // All materials describing where the issue occured + Issues.file, + Issues.line, + Issues.column + }, + run_time, + start_time + } + ] + }, ], - "vulnerabilityDistribution": {}, //Twistlock scan metadata -> profiles - "vulnerabilityScanPassed", // - "history": [], //Scan target package install history -> profiles - "scanTime", //Twistlock scan metadata -> profiles - "scanID" // - } + status + }, ], - "consoleURL" //Twistlock scan metadata -> profiles + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors + name: 'Golang errors', + data: Golang errors + }, + { // Stats on GoSec scan + name: 'Stats', + data: Stats + }, + ], + raw + } } ``` +::: -With this, we now have a general outline which roughly connects each data field in the Twistlock sample export to one of our structures in the HDF. In order to improve the accuracy of this mapping, we can now begin connecting [specific fields in the HDF schema](#fullschema) with the data fields in the sample export using our rough draft as a guide. +For these fields, we can place them in `passthrough` as there are no reasonably applicable fields in the OHDF schema to place them in. -If we cannot find a field in the HDF schema that fits with a certain field in the sample export per our original groupings, we can instead look to the other structures to see if they have applicable fields or place the field into the passthrough structure as a last resort. +Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. -``` -//Data values are removed for visual clarity +::: details OHDF Schema Mapping Ver. 5 +```typescript { - "results": [ + platform: { // We fill in Heimdall for the platform as it handles the generation of this OHDF file + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, // See 'platform' reasoning + statistics: {}, // Not enough info to fill + profiles: [ { - "id", //profiles -> passthrough.auxiliary_data.data - "name", //profiles -> profiles.name - "distro", //profiles -> passthrough.auxiliary_data.data - "distroRelease", //profiles -> passthrough.auxiliary_data.data - "digest", //profiles -> passthrough.auxiliary_data.data - "collections", //profiles -> profiles.title - "packages": [], //profiles -> passthrough.auxiliary_data.data - "vulnerabilities": [ + name: 'Gosec scanner', // We know that this report is generated from GoSec + version: GosecVersion, // Version of GoSec instance + sha256: '', // Leave it empty as OHDF Converters will generate one for us + title: 'gosec', // We know that this report is generated from GoSec + supports: [], // Not enough info to fill + attributes: [], // Not enough info to fill + groups: [], // Not enough info to fill + controls: [ { - "id", //controls -> profiles.controls.id - "status", //results -> profiles.controls.results.status - "cvss", //controls -> profiles.controls.code - "description", //controls -> profiles.controls.desc - "severity", //controls -> profiles.controls.impact - "packageName", //results -> profiles.controls.results.code_desc - "packageVersion", //results -> profiles.controls.results.code_desc - "link", //controls -> profiles.controls.code - "riskFactors": [], //results -> profiles.controls.code - "impactedVersions": [], //results -> profiles.controls.results.code_desc - "publishedDate", //controls -> profiles.controls.code - "discoveredDate", //results -> profiles.controls.results.start_time - "layerTime" //passthrough -> profiles.controls.code - } + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc: '', // Not enough info to fill + impact: 0.5, // Have no solid information on impact of security issue, so we default to 0.5 + refs: [], // Not enough info to fill + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + source_location: {}, // Not enough info to fill + results: [ + { + status: 'Failure', // The security scan only reports failed requirements, so all findings we receive get fail statuses + code_desc: Issues.code, // The code failing the requirement test + message: { // All materials describing where the issue occured + Issues.file, + Issues.line, + Issues.column + }, + start_time // Not enough info to fill + } + ] + }, ], - "vulnerabilityDistribution": {}, //profiles -> profiles.summary - "vulnerabilityScanPassed", //profiles -> passthrough.auxiliary_data.data - "history": [], //profiles -> passthrough.auxiliary_data.data - "scanTime", //profiles -> passthrough.auxiliary_data.data - "scanID" //profiles -> passthrough.auxiliary_data.data - } + status: 'loaded' // Give loaded status to denote that profile is loaded by OHDF Converters + }, ], - "consoleURL" //profiles -> passthrough.auxiliary_data.data + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors + name: 'Golang errors', + data: Golang errors + }, + { // Stats on GoSec scan + name: 'Stats', + data: Stats + }, + ], + raw + } } ``` +::: -With this, we now have a detailed high-level mapping for the conversion from an external file format to the HDF, which we can use for the [technical implementation of a \*-to-HDF mapper](#create). -[placeholder] +Now we have a finalized mapping for GoSec to OHDF. diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index 39dfd0e00..e51a41355 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -6,100 +6,3 @@ author: Charles Hu --- -WORKING TO REFACTOR FOLLOWING SECTION - -[placeholder] - -## Mapper Creation - -### \*-to-HDF Creation Guide - - -4. Set up for \*-to-HDF mapper development. - - - 4a. - - - 4b. Create a blank TypeScript file under the src directory in hdf-converters. It should be named: - - ``` - {YOUR-EXPORT-NAME-HERE}-mapper.ts - ``` - - - 4c. Select the appropriate [mapper skeleton](#skeleton) for your export type. Place them in the file created in step 4b. Replace names (skeleton by default) as necessary. - - - 4d. Export your mapper class created in the previous steps by specifying its export in the index.ts file. Add the following line: - - ``` - export * from './src/{YOUR-EXPORT-NAME-HERE}-mapper'; - ``` - - - 4e. Create a new directory named {YOUR-EXPORT-NAME-HERE}_mapper under the sample_jsons directory in hdf-converters. Create another directory named sample_input_report in the directory you just made. The file structure should look like this: - - ``` - +-- sample_jsons - | +-- {YOUR-EXPORT-NAME-HERE}-mapper - | | +-- sample_input_report - ``` - - - 4f. Place your sample export under the sample_input_report directory. Your sample export should be genericized to avoid any leaking of sensitive information. The file structure should now look like this: - - ``` - +-- sample_jsons - | +-- {YOUR-EXPORT-NAME-HERE}-mapper - | | +-- sample_input_report - | | | +-- {YOUR-SAMPLE-EXPORT} - ``` - - - 4g. Create a blank TypeScript file under the test/mappers/forward directory in hdf-converters. It should be named: - - ``` - {YOUR-EXPORT-NAME-HERE}_mapper.spec.ts - ``` - - - 4h. Select the appropriate [mapper testing skeleton](#skeleton) for your export type. Place it in the file created in step 4g. Replace names (skeleton by default) as necessary. - -5. Add fingerprinting to identify your security service scan export. - - - 5a. Go to the file report_intake.ts under the heimdall2/apps/frontend/src/store directory. - - - 5b. Import your mapper file. You should be able to add the name of your mapper class to a pre-existing import statement pointing at hdf-converters as follows: - - ``` - import { - ASFFResults as ASFFResultsMapper, - BurpSuiteMapper, - ... - {YOUR-MAPPER-CLASS-HERE} - } from '@mitre/hdf-converters'; - ``` - - - 5c. Instantiate your mapper class in the convertToHdf switch block. Add the following lines: - - ``` - case '{YOUR-EXPORT-SERVICE-NAME-HERE}': - return new {YOUR-MAPPER-CLASS-HERE}(convertOptions.data).toHdf(); - ``` - - - 5d. Navigate to the file fingerprinting.ts in the src/utils directory in hdf-converters. Add keywords that are unique to your sample export to the fileTypeFingerprints variable. It should be formatted as follows: - - ``` - export const fileTypeFingerprints = { - asff: ['Findings', 'AwsAccountId', 'ProductArn'], - ... - {YOUR-EXPORT-SERVICE-NAME-HERE}: [{UNIQUE KEYWORDS AS STRINGS}] - }; - ``` - -6. Create the \*-to-HDF mapper. - - - 6a. Return to the {YOUR-EXPORT-NAME-HERE}-mapper.ts file. In the file, you should have a generic skeleton mapper picked according to your export type. - - - 6b. Certain security services produce exports which are not immediately usable by the skeleton mapper. In this case, pre-processing on the export and post-processing on the generated HDF file is necessary in order to ensure compatibility. - - - 6c. The skeleton mapper and [base-converter](#base) have been designed to provide the base functionality needed for \*-to-HDF mapper generation. For most developers, mapper creation will be limited to assigning objects from the export structure to correlating attributes in the mapper according to the HDF schema. - - - An example of this process is provided in the [\*-to-HDF Mapper Construction Example](#example2) section. - - - 6d. [Commit your changes](https://github.com/git-guides/git-commit) with the [signoff option](https://git-scm.com/docs/git-commit) and [push the changes](https://github.com/git-guides/git-push) to your development branch. This should queue up the Github Actions pipeline which includes a Netlify instance of Heimdall2 which you can use to test if your mapper is generating a HDF file correctly. - -[placeholder] From c3730a131c6f726cabb26782f8c2fb81cac6610f Mon Sep 17 00:00:00 2001 From: Ryan Lin Date: Tue, 18 Jun 2024 16:31:25 -0700 Subject: [PATCH 22/71] Minor wording changes Signed-off-by: Ryan Lin --- src/courses/mappers/03.md | 2 +- src/courses/mappers/05.md | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index 4fdd527bc..3e803d205 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -25,4 +25,4 @@ The [SAF CLI](https://github.com/mitre/saf) is a tool that provides various auto ## What Is Heimdall2? -[Heimdall2](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. Data that is imported into Heimdall2 is automatically converted to OHDF through OHDF Converters, which serves as the underlying library which services data format conversion requests in Heimdall2. +[Heimdall2](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. Data that is imported into Heimdall2 is automatically converted to OHDF through OHDF Converters, which serves as the underlying library that services data format conversion requests in Heimdall2. \ No newline at end of file diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index 6376cb3f3..ef9e6cc01 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -17,11 +17,11 @@ This structure contains metadata on the target system of the original security t ### 2. **Controls** -Controls are security requirements that are used to prevent, mitigate, and address various security risks to sensitive information and infrastructure. In the case of OHDF, the controls structure is a collection of requirements tested for by an external security tool to ensure that the target complies with vulnerability and weakness prevention standards. Any given profile contains any number of controls which were tested against the target system during the original security tool run. +Controls are security requirements that are used to prevent, mitigate, and address various security risks to sensitive information and infrastructure. In the case of OHDF, the controls structure is a collection of requirements tested for by an external security tool to ensure that the target complies with vulnerability and weakness prevention standards. Any given profile contains some number of controls which were tested against the target system during the original security tool run. ### 3. **Results** -The results structure contains information on the results of specific tests ran by the security tool on the target system against a security requirement/control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses exist but are rare) which cumulatively influence the determined compliance level of the target system for some set of requirements/controls. Any given control contains any number of results which reflect the implemented tests to check if the target system is actually compliant. +The results structure contains information on the results of specific tests ran by the security tool on the target system against a security requirement/control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses exist but are rare) which cumulatively influence the determined compliance level of the target system for some set of requirements/controls. Any given control contains some number of results which reflect the implemented tests to check if the target system is actually compliant. ## Overall Hierarchy From c6a78d18dff57db777f1a758271af984678eb9ad Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 19 Jun 2024 09:06:27 -0400 Subject: [PATCH 23/71] Schema mapping finalization Signed-off-by: Charles Hu --- src/courses/mappers/13.md | 190 +++++++++++++++++++++++++++++++++++--- src/courses/mappers/14.md | 2 +- 2 files changed, 178 insertions(+), 14 deletions(-) diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index d87436162..b8d6c8b8e 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -111,10 +111,10 @@ Let's apply this to our GoSec source data. Try to find the answers to these two // Recording: Requirement testing - This specifies the code that fails the requirement after source code testing "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", // Purpose: The line number of the offending code - // Recording: Requirement testing - This field specifies the location of the failling code + // Recording: Requirement testing - This field specifies the location of the failing code "line": "83", // Purpose: The column number of the offending code - // Recording: Requirement testing - This field specifies the location of the failling code + // Recording: Requirement testing - This field specifies the location of the failing code "column": "14", // Purpose: Whether this security issue should be ignored // Recording: Requirements - Specifies whether this security issue should be ignored @@ -213,7 +213,9 @@ Let's first start with an empty OHDF schema as follows: ``` ::: -We can begin our schema correlation by directly porting over fields from the GoSec source data that are obvious: `GosecVersion`, `Issues.rule_id`, `Issues.details`, `Issues.cwe`, and `Issues.code`. Try to map these fields youself as you follow along and refer to our solution to check your work. +We can begin our schema correlation by directly porting over fields from the GoSec source data that are obvious: `GosecVersion`, `Issues.rule_id`, `Issues.details`, and `Issues.cwe`. Try to map these fields youself as you follow along and refer to our solution to check your work. + +Note that these mapping are informal and do not need to adhere to any programming syntax. Proper implementation of these mappings will be done later in the course. ::: details OHDF Schema Mapping Ver. 1 ```typescript @@ -257,7 +259,7 @@ We can begin our schema correlation by directly porting over fields from the GoS results: [ { status, - code_desc: Issues.code, // The code for the requirement test + code_desc, message, run_time, start_time @@ -300,11 +302,14 @@ We can begin our schema correlation by directly porting over fields from the GoS // Purpose: The offending file // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The offending code + // Recording: Requirement testing - This specifies the code that fails the requirement after source code testing + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", // Purpose: The line number of the offending code - // Recording: Requirement testing - This field specifies the location of the failling code + // Recording: Requirement testing - This field specifies the location of the failing code "line": "83", // Purpose: The column number of the offending code - // Recording: Requirement testing - This field specifies the location of the failling code + // Recording: Requirement testing - This field specifies the location of the failing code "column": "14", // Purpose: Whether this security issue should be ignored // Recording: Requirements - Specifies whether this security issue should be ignored @@ -326,12 +331,137 @@ We can begin our schema correlation by directly porting over fields from the GoS ``` ::: -Note that these mapping are informal and do not need to adhere to any programming syntax. Proper implementation of these mappings will be done later in the course. +::: details Reasoning +- `version: GosecVersion`: We want to specifically place this in `version` in `profiles` because this is meta data on the actual security tool that generated these results. This is different from `version` on the top level since that refers to the platform, or the tool creating the actual OHDF file itself. -Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.nosec`, and `Issues.suppressions`. +- `id: Issues.rule_id`: `rule_id` gives us an ID used by GoSec to identify each failing requirement in the source code. + +- `title: Issues.details`: The source data doesn't provide a proper title that goes along with the failing requirement. In lieu of this, we can use `Issues.details` which does give us a human readable description of the requirement and repurpose it as a title for our control. + +- `tags: {Issues.cwe}`: `Issues.cwe` provides an association of our GoSec security issue with a known vulnerability database. This can be used in `tags` to act as meta data which can used to filter or organize controls created from these GoSec security issues. +::: + +Next, let's look at `Issues.code`, which can be a little bit tricky. ::: details OHDF Schema Mapping Ver. 2 ```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version: GosecVersion, // Version of GoSec instance + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc, + descriptions, + impact, + refs, + tags: { + Issues.cwe // Associated CWE for the requirement + }, + code, + source_location, + results: [ + { + status, + code_desc: Issues.code, // The code failing the requirement test + message, + run_time, + start_time + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +::: details Remaining GoSec Source Data +```json +{ + // Purpose: Go compilation errors + // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: Container for identified security issues + // Recording: Requirements - This entity records all identified security issues in a Go source code + "Issues": [ + { + // Purpose: The severity of the identified issue + // Recording: Requirements - This is specifically related to the severity level of the requirement + "severity": "MEDIUM", + // Purpose: How sure that the identified issue if applicable to this source code + // Recording: Requirements testing - This field gives the applicability of the issue after source code testing + "confidence": "HIGH", + // Purpose: The offending file + // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The line number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "line": "83", + // Purpose: The column number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "column": "14", + // Purpose: Whether this security issue should be ignored + // Recording: Requirements - Specifies whether this security issue should be ignored + "nosec": false, + // Purpose: The supression level for info on the security issue + // Recording: Requirements - Specifies the info suppression level of the security issue + "suppressions": null + } + ], + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Meta data - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + } +} +``` +::: + +::: details Reasoning +- `code_desc: Issues.code`: `Issues.code` refers to the source code that is explicitly failing the GoSec requirement. This does not align with our definition for `code_desc` but remember that we always aim to seek parity with the original security tool. GoSec focuses heavily on identifying a security issue and directly pinpointing where that issue occurs for immediate resolution. We want to mirror that behavior by also pinpointing where the security issue occurs at instead of providing a code description of what test went wrong. +::: + +Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.nosec`, and `Issues.suppressions`. + +::: details OHDF Schema Mapping Ver. 3 +```typescript { platform: { name, @@ -414,10 +544,10 @@ Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.n // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", // Purpose: The line number of the offending code - // Recording: Requirement testing - This field specifies the location of the failling code + // Recording: Requirement testing - This field specifies the location of the failing code "line": "83", // Purpose: The column number of the offending code - // Recording: Requirement testing - This field specifies the location of the failling code + // Recording: Requirement testing - This field specifies the location of the failing code "column": "14" } ], @@ -433,11 +563,15 @@ Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.n ``` ::: -We map these fields to `tags` in the OHDF schema due to each of these fields acting as descriptive traits of the control which we can categorize and sort the controls by. We won't use `Issues.severity` for `impact` as we have no concrete correlation between the two fields and as such cannot accurately convert between the two. +::: details Reasoning +We map these fields to `tags` in the OHDF schema due to each of these fields acting as descriptive traits of the control which we can categorize and sort the controls by. + +It may be tempting to map `Issues.severity` to `impact`; however, it is important to note that `severity` is not the same as `impact`. These two fields are separate and distinct metrics, and while conversion is possible, it is not performed in this case due to uncertainty on how to translate the two metrics properly. +::: Next, let's look at the fields `Issues.file`, `Issues.line`, and `Issues.column`. -::: details OHDF Schema Mapping Ver. 3 +::: details OHDF Schema Mapping Ver. 4 ```typescript { platform: { @@ -529,7 +663,9 @@ Next, let's look at the fields `Issues.file`, `Issues.line`, and `Issues.column` ``` ::: -We map these fields to `message` in the OHDF schema as we can use these fields to create a verbose description of control test result. In particular, we use these fields to directly indicate to the reader where the test was performed and subsequently failed. +::: details Reasoning +This is a situation similar to the one `Issues.code` is in. `Issues.file`, `Issues.line`, and `Issues.column` do not fit the definition given for `message` (i.e., they are not explanations for the test status); however, they do elaborate upon the location of the offending code snippet identified by GoSec, which we want to seek parity with. Thus, in lieu of any suitable substitutes, we instead use the locational information of the failing source code snippet as a description for the control result. +::: Next, let's look at the fields `Golang errors` and `Stats`. @@ -611,8 +747,12 @@ Next, let's look at the fields `Golang errors` and `Stats`. ``` ::: +::: details Reasoning For these fields, we can place them in `passthrough` as there are no reasonably applicable fields in the OHDF schema to place them in. +`Golang errors` is not used anywhere in `controls` as it is a description of compilation errors which would've already been flagged by GoSec as security issues if they already occured. Thus, to avoid duplication, `Golang errors` is omitted from the main OHDF structures. +::: + Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. ::: details OHDF Schema Mapping Ver. 5 @@ -682,4 +822,28 @@ Finally, let's fill the rest of the empty fields using what available informatio ``` ::: +::: details Reasoning +Unfilled fields are a result of a lack of sufficent information from the source data that can be used to reasonably associate with these fields. + +The reasoning for the filled fields are as follows: + +- `platform: {name: 'Heimdall Tools'}`: `platform` refers to the instance generating the OHDF file, which in this case is Heimdall2 or Heimdall Tools. + +- `platform: {release: HeimdallToolsVersion}`: Similar reasoning as above. + +- `version: HeimdallToolsVersion`: Similar reasoning as `platform` fields. + +- `name: 'Gosec scanner'`: `profiles` refers to the security tool that generated the original source data. In this case, it is the GoSec security scanning tool. + +- `version: GosecVersion`: We can import the version of GoSec here. + +- `title: 'gosec'`: We can give a succinct title for the profile here. + +- `impact: 0.5`: We use a default value of `0.5` since we do not have a direct mapping set up to convert the `Issues.severity` field. + +- `status: 'Failure'`: GoSec only reports security vulnerabilities if it finds that the scanned source code has such security issues present. As such, every reported issue in a GoSec scan will always be a result of a failed security test. + +- `status: 'loaded'`: The status of a profile is typically `loaded` since it has been ingested and converted to OHDF. +::: + Now we have a finalized mapping for GoSec to OHDF. diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index e51a41355..2becf7f83 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -5,4 +5,4 @@ title: Demo - Implementing a Mapper author: Charles Hu --- - +Now that we have developed a mapping, we can now create a mapper which actually implements our mapping in OHDF Converters. From 415a9843968fb8cc5397332502ce1b2c230c8b31 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 19 Jun 2024 12:02:52 -0400 Subject: [PATCH 24/71] Mapping update; mapper progress Signed-off-by: Charles Hu --- src/courses/mappers/13.md | 16 ++++- src/courses/mappers/14.md | 147 +++++++++++++++++++++++++++++++++++++- 2 files changed, 160 insertions(+), 3 deletions(-) diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index b8d6c8b8e..31ba173c1 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -213,6 +213,8 @@ Let's first start with an empty OHDF schema as follows: ``` ::: +#### Mapping Version 1 + We can begin our schema correlation by directly porting over fields from the GoSec source data that are obvious: `GosecVersion`, `Issues.rule_id`, `Issues.details`, and `Issues.cwe`. Try to map these fields youself as you follow along and refer to our solution to check your work. Note that these mapping are informal and do not need to adhere to any programming syntax. Proper implementation of these mappings will be done later in the course. @@ -341,6 +343,8 @@ Note that these mapping are informal and do not need to adhere to any programmin - `tags: {Issues.cwe}`: `Issues.cwe` provides an association of our GoSec security issue with a known vulnerability database. This can be used in `tags` to act as meta data which can used to filter or organize controls created from these GoSec security issues. ::: +#### Mapping Version 2 + Next, let's look at `Issues.code`, which can be a little bit tricky. ::: details OHDF Schema Mapping Ver. 2 @@ -458,6 +462,8 @@ Next, let's look at `Issues.code`, which can be a little bit tricky. - `code_desc: Issues.code`: `Issues.code` refers to the source code that is explicitly failing the GoSec requirement. This does not align with our definition for `code_desc` but remember that we always aim to seek parity with the original security tool. GoSec focuses heavily on identifying a security issue and directly pinpointing where that issue occurs for immediate resolution. We want to mirror that behavior by also pinpointing where the security issue occurs at instead of providing a code description of what test went wrong. ::: +#### Mapping Version 3 + Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.nosec`, and `Issues.suppressions`. ::: details OHDF Schema Mapping Ver. 3 @@ -569,6 +575,8 @@ We map these fields to `tags` in the OHDF schema due to each of these fields act It may be tempting to map `Issues.severity` to `impact`; however, it is important to note that `severity` is not the same as `impact`. These two fields are separate and distinct metrics, and while conversion is possible, it is not performed in this case due to uncertainty on how to translate the two metrics properly. ::: +#### Mapping Version 4 + Next, let's look at the fields `Issues.file`, `Issues.line`, and `Issues.column`. ::: details OHDF Schema Mapping Ver. 4 @@ -667,9 +675,11 @@ Next, let's look at the fields `Issues.file`, `Issues.line`, and `Issues.column` This is a situation similar to the one `Issues.code` is in. `Issues.file`, `Issues.line`, and `Issues.column` do not fit the definition given for `message` (i.e., they are not explanations for the test status); however, they do elaborate upon the location of the offending code snippet identified by GoSec, which we want to seek parity with. Thus, in lieu of any suitable substitutes, we instead use the locational information of the failing source code snippet as a description for the control result. ::: +#### Mapping Version 5 + Next, let's look at the fields `Golang errors` and `Stats`. -::: details OHDF Schema Mapping Ver. 4 +::: details OHDF Schema Mapping Ver. 5 ```typescript { platform: { @@ -753,9 +763,11 @@ For these fields, we can place them in `passthrough` as there are no reasonably `Golang errors` is not used anywhere in `controls` as it is a description of compilation errors which would've already been flagged by GoSec as security issues if they already occured. Thus, to avoid duplication, `Golang errors` is omitted from the main OHDF structures. ::: +#### Mapping Version 6 + Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. -::: details OHDF Schema Mapping Ver. 5 +::: details OHDF Schema Mapping Ver. 6 ```typescript { platform: { // We fill in Heimdall for the platform as it handles the generation of this OHDF file diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index 2becf7f83..dbe0736c6 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -5,4 +5,149 @@ title: Demo - Implementing a Mapper author: Charles Hu --- -Now that we have developed a mapping, we can now create a mapper which actually implements our mapping in OHDF Converters. +## Mapper Introduction + +::: note OHDF Converters Keywords +Programming keyword functions from OHDF Converters are used here. [Refer here](./09.md) for a refresher on OHDF Converters. +::: + +Now that we have developed a mapping, we can implement that mapping as a mapper which applies the mapping to any compatible file for a conversion to OHDF. + +## File Set Up + +A number of crucial files that support and provide the infrastructure needed for the *-to-OHDF mapper have to be set up first before we begin actual mapper development. + +::: note Specialized Security Tools +This guide is geared for security tools that provide scan-based export data. If your security tool provides a specialized form of export data or is an API, contact the SAF team for further guidance. +::: + +### Mapper File + +First, we need to create the file that hosts the mapper and link to it so other files in OHDF Converters can access it. + +1. Create a blank TypeScript file under the `src` directory in `hdf-converters`. It should be named: +``` +{YOUR-EXPORT-NAME-HERE}-mapper.ts +``` + +2. Select the appropriate mapper skeleton (see below) for your export type. Place them in the file created in step 1. Replace names (`skeleton` by default) as necessary. + +::: details JSON Mapper Skeleton +```typescript +import {ExecJSON} from 'inspecjs'; +import _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform +} from './base-converter'; + +const IMPACT_MAPPING: Map = new Map([ + ['critical', 0.9], + ['high', 0.7], + ['medium', 0.5], + ['low', 0.3] +]); + +export class SkeletonMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id: null //Insert data + }, + version: HeimdallToolsVersion, + statistics: { + duration: null //Insert data + }, + profiles: [ + { + name: '', //Insert data + title: null, //Insert data + maintainer: null, //Insert data + summary: null, //Insert data + license: null, //Insert data + copyright: null, //Insert data + copyright_email: null, //Insert data + supports: [], //Insert data + attributes: [], //Insert data + depends: [], //Insert data + groups: [], //Insert data + status: 'loaded', //Insert data + controls: [ + { + key: 'id', + tags: {}, //Insert data + descriptions: [], //Insert data + refs: [], //Insert data + source_location: {}, //Insert data + title: null, //Insert data + id: '', //Insert data + desc: null, //Insert data + impact: 0, //Insert data + code: null, //Insert data + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, //Insert data + code_desc: '', //Insert data + message: null, //Insert data + run_time: null, //Insert data + start_time: '' //Insert data + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed + ...(this.withRaw && {raw: data}) + }; + } + } + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw + } +} +``` +::: + +3. Export your mapper class created in the previous steps by specifying its export in the index.ts file. Add the following line: +``` +export * from './src/{YOUR-EXPORT-NAME-HERE}-mapper'; +``` + +### Sample File + +Next, we need to add a sample file for the mapper to ingest when running unit tests on it. + +1. Create a new directory named `{YOUR-EXPORT-NAME-HERE}_mapper` under the `sample_jsons` directory in `hdf-converters`. Create another directory named `sample_input_report` in the directory you just made. The directory structure should look like this: +``` ++-- sample_jsons +| +-- {YOUR-EXPORT-NAME-HERE}-mapper +| | +-- sample_input_report +``` + +2. Place your sample export under the `sample_input_report` directory. Your sample export should be genericized to avoid any leaking of sensitive information. The directory structure should now look like this: +``` ++-- sample_jsons +| +-- {YOUR-EXPORT-NAME-HERE}-mapper +| | +-- sample_input_report +| | | +-- {YOUR-SAMPLE-EXPORT} +``` + +### Unit Testing + + From 358320b74f096445d13397db0c281079f15aa5b8 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 19 Jun 2024 13:34:46 -0400 Subject: [PATCH 25/71] Clean up; first half of implementation section Signed-off-by: Charles Hu --- src/courses/mappers/12.md | 4 +- src/courses/mappers/14.md | 115 ++++++++++++++++++++++++++++++++++-- src/courses/mappers/15.md | 119 -------------------------------------- 3 files changed, 113 insertions(+), 125 deletions(-) diff --git a/src/courses/mappers/12.md b/src/courses/mappers/12.md index d2f3a42e6..89495c841 100644 --- a/src/courses/mappers/12.md +++ b/src/courses/mappers/12.md @@ -18,9 +18,9 @@ The following is an index of the remaining walkthrough portion of the course: - Requirement(s): OHDF schema knowledge, security tool schema knowledge 2. [Implementing a Mapper](./14.md) - Material type: Practical - - Requirement(s): TypeScript, OHDF schema knowledge + - Requirement(s): TypeScript, OHDF schema knowledge, OHDF Converters knowledge, file format (e.g., JSON, XML, CSV) knowledge 3. [Finalizing the Mapper](./15.md) - Material type: Practical - - Requirement(s): TypeScript, file format (e.g., JSON, XML, CSV) knowledge + - Requirement(s): TypeScript, OHDF Converters knowledge, file format (e.g., JSON, XML, CSV) knowledge 4. [More Practice](./16.md) 5. [Next Steps](./17.md) diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index dbe0736c6..489bdd41f 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -7,8 +7,8 @@ author: Charles Hu ## Mapper Introduction -::: note OHDF Converters Keywords -Programming keyword functions from OHDF Converters are used here. [Refer here](./09.md) for a refresher on OHDF Converters. +::: note OHDF Converters Utilities +Special utilities from OHDF Converters are used here. [Refer here](./09.md) for a refresher on OHDF Converters. ::: Now that we have developed a mapping, we can implement that mapping as a mapper which applies the mapping to any compatible file for a conversion to OHDF. @@ -30,7 +30,7 @@ First, we need to create the file that hosts the mapper and link to it so other {YOUR-EXPORT-NAME-HERE}-mapper.ts ``` -2. Select the appropriate mapper skeleton (see below) for your export type. Place them in the file created in step 1. Replace names (`skeleton` by default) as necessary. +2. Select the appropriate mapper skeleton (see below) for your export type. Place them in the file created in step 1. Replace names (`SKELETON` by default) as necessary. ::: details JSON Mapper Skeleton ```typescript @@ -51,7 +51,7 @@ const IMPACT_MAPPING: Map = new Map([ ['low', 0.3] ]); -export class SkeletonMapper extends BaseConverter { +export class SKELETONMapper extends BaseConverter { withRaw: boolean; mappings: MappedTransform< @@ -150,4 +150,111 @@ Next, we need to add a sample file for the mapper to ingest when running unit te ### Unit Testing +Now that we have a sample file, we can now add some unit tests which automatically test our mapper to ensure that it is producing readable and correct OHDF file outputs. +1. Create a blank TypeScript file under the `test/mappers/forward` directory in `hdf-converters`. It should be named: +``` +{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts +``` + +2. Select the appropriate mapper test skeleton (see below) for your export type. Place it in the file created in step 1. Replace names (`SKELETON` by default) as necessary. + +::: details JSON Mapper Test Skeleton +```typescript +import fs from 'fs'; +import {SKELETONMapper} from '../../../src/SKELETON-mapper'; +import {omitVersions} from '../../utils'; + +describe('SKELETON_mapper', () => { + it('Successfully converts SKELETON targeted at a local/cloned repository data', () => { + const mapper = new SKELETONMapper( + fs.readFileSync( + 'sample_jsons/SKELETON_mapper/sample_input_report/SKELETON.json', + {encoding: 'utf-8'} + ) + ); + + // fs.writeFileSync( + // 'sample_jsons/SKELETON_mapper/SKELETON-hdf.json', + // JSON.stringify(mapper.toHdf(), null, 2) + // ); + + expect(omitVersions(mapper.toHdf())).toEqual( + omitVersions( + JSON.parse( + fs.readFileSync( + 'sample_jsons/SKELETON_mapper/SKELETON-hdf.json', + { + encoding: 'utf-8' + } + ) + ) + ) + ); + }); +}); + +describe('SKELETON_mapper_withraw', () => { + it('Successfully converts withraw flagged SKELETON targeted at a local/cloned repository data', () => { + const mapper = new SKELETONMapper( + fs.readFileSync( + 'sample_jsons/SKELETON_mapper/sample_input_report/SKELETON.json', + {encoding: 'utf-8'} + ), + true + ); + + // fs.writeFileSync( + // 'sample_jsons/SKELETON_mapper/SKELETON-hdf-withraw.json', + // JSON.stringify(mapper.toHdf(), null, 2) + // ); + + expect(omitVersions(mapper.toHdf())).toEqual( + omitVersions( + JSON.parse( + fs.readFileSync( + 'sample_jsons/SKELETON_mapper/SKELETON-hdf-withraw.json', + { + encoding: 'utf-8' + } + ) + ) + ) + ); + }); +}); +``` +::: + +### Fingerprinting + +OHDF Converters has a fingerprinting service that detects a security tool data format and automatically applies the correct mapper to convert it to OHDF. To enable this feature, we need to explicitly declare keywords unique to the security tool data format as follows: + +1. Go to the file `report_intake.ts` under the `heimdall2/apps/frontend/src/store` directory. + +2. Import your mapper file. You should be able to add the name of your mapper class to a pre-existing import statement pointing at `hdf-converters` as follows: +```typescript +import { + ASFFResults as ASFFResultsMapper, + BurpSuiteMapper, + ... + {YOUR-MAPPER-CLASS-HERE} +} from '@mitre/hdf-converters'; +``` + +3. Instantiate your mapper class in the `convertToHdf` switch block. Add the following lines: +```typescript +case '{YOUR-EXPORT-SERVICE-NAME-HERE}': + return new {YOUR-MAPPER-CLASS-HERE}(convertOptions.data).toHdf(); +``` + +4. Navigate to the file `fingerprinting.ts` in the `src/utils` directory in `hdf-converters`. Add keywords that are unique to your sample export to the `fileTypeFingerprints` variable. It should be formatted as follows: +```typescript +export const fileTypeFingerprints = { + asff: ['Findings', 'AwsAccountId', 'ProductArn'], + ... + {YOUR-EXPORT-SERVICE-NAME-HERE}: [{UNIQUE KEYWORDS AS STRINGS}] +}; +``` + +## Mapper Implementation diff --git a/src/courses/mappers/15.md b/src/courses/mappers/15.md index 4558ba66d..11d444238 100644 --- a/src/courses/mappers/15.md +++ b/src/courses/mappers/15.md @@ -5,123 +5,4 @@ title: Demo - Finalizing the Mapper author: Charles Hu --- -WORKING TO REFACTOR FOLLOWING SECTION -[placeholder] - -7. Set up and use regression testing on your mapper. - - - 7a. Uncomment out the commented out lines in the {YOUR-SAMPLE-EXPORT}-hdf.json file created in step 4f. This will allow the regression tests to automatically generate a HDF output file whenever you run the tests. The commented out lines should look similar to the following: - - ``` - // fs.writeFileSync( - // 'sample_jsons/skeleton_mapper/skeleton-hdf.json', - // JSON.stringify(mapper.toHdf(), null, 2) - // ); - ``` - - - 7b. Using the terminal, cd into the hdf-converters directory and run the following command. This command will run your mapper against the sample export file in sample_jsons and test to see if the output is generated as expected. - - ``` - yarn run test --verbose --silent=false ./test/mappers/forward/{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts - ``` - - - 7c. Your tests should generate HDF output files for when --with-raw is not flagged (default behavior) and when it is flagged (denoted by -withraw in the filename). It will also compare the contents of these generated files with a temporary mapper instance created in the test itself. Review the test output to ensure that the tests are all passing and review the HDF output files to ensure that the contents of the mapping are being generated correctly. - - - 7d. Recomment out the lines from step 7b. - -8. Document your new mapper in the README for hdf-converters under the Supported Formats section. It should be formatted as follows: - -``` -{#}. [{YOUR-EXPORT-NAME-HERE}] - {MAPPER INPUT DESCRIPTION} -``` - -9. Commit your final changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, your mapper will be merged into the main development branch and [scheduled for release](https://github.com/mitre/heimdall2/wiki/How-to-create-a-Heimdall2-release) as an officially supported conversion format for the HDF Converters. - -10. Create a development branch against the [SAF CLI repository](https://github.com/mitre/saf) and create a draft pull request for your new branch. - -11. Set up for SAF CLI mapper integration. - - - 11a. In the package.json file, update the versions of @mitre/hdf-converters and @mitre/heimdall-lite to the [latest release of Heimdall2](https://github.com/mitre/heimdall2/releases). - - - 11b. In the src/commands/convert directory, create a blank TypeScript file. It should be named: - - ``` - {YOUR-EXPORT-NAME-HERE}2hdf.ts - ``` - - - 11c. In the test/sample_data directory, create a directory named {YOUR-EXPORT-NAME-HERE}. Underneath it, create a directory named sample_input_report. The file structure should now look like this: - - ``` - +-- sample_data - | +-- {YOUR-EXPORT-NAME-HERE} - | | +-- sample_input_report - ``` - - - 11d. Place your sample export under the sample_input_report directory. Your sample export should be genericized to avoid any leaking of sensitive information. Under the {YOUR-EXPORT-NAME-HERE} directory, place your output HDF files generated during the testing phase of step 7c. The file structure should now look like this: - - ``` - +-- sample_data - | +-- {YOUR-EXPORT-NAME-HERE} - | | +-- sample_input_report - | | | +-- {YOUR-SAMPLE-EXPORT} - | | +-- {YOUR-EXPORT-NAME-HERE}-hdf.json - | | +-- {YOUR-EXPORT-NAME-HERE}-hdf-withraw.json - ``` - - - 11e. In the test/commands/convert directory, create a blank TypeScript file. It should be named: - - ``` - {YOUR-EXPORT-NAME-HERE}2hdf.test.ts - ``` - -12. Integrate your mapper with the SAF CLI. - - - 12a. Insert the [skeleton](#skeleton) for integrating a HDF mapper with the SAF CLI. Replace names (skeleton by default) as necessary. - - - 12b. Insert the [skeleton](#skeleton) for a convert command test for the SAF CLI. Replace names (skeleton by default) as necessary. - - - 12c. Navigate to the index.ts file under the src/commands/convert directory. Import your mapper using the existing import block as follows: - - ``` - import { - ASFFResults, - ... - {YOUR-MAPPER-CLASS-HERE} - } from '@mitre/hdf-converters' - ``` - - - 12d. Under the switch block in the getFlagsForInputFile function, add your mapper class as it is defined in step 5d for fingerprinting for the generic convert command. If the convert command for your mapper has any additional flags beyond the standard --input and --output flags, return the entire flag block in the switch case. This is demonstrated as follows: - - ``` - switch (Convert.detectedType) { - ... - case {YOUR-EXPORT-SERVICE-NAME-HERE}: - return {YOUR-CLI-CONVERT-CLASS}.flags //Only add if special flags exist - ... - return {} - } - ``` - -13. Edit the README file to reflect your newly added conversion command under the To HDF section. It should be formatted as follows: - -``` -##### {YOUR-EXPORT-NAME-HERE} to HDF - -\``` -convert {YOUR-EXPORT-NAME-HERE}2hdf Translate a {YOUR-EXPORT-NAME-HERE} results {EXPORT-TYPE} into - a Heimdall Data Format JSON file - -OPTIONS - -i, --input=input Input {EXPORT-TYPE} File - -o, --output=output Output HDF JSON File - -w, --with-raw Include raw input file in HDF JSON file - -EXAMPLES - saf convert {YOUR-EXPORT-NAME-HERE}2hdf -i {INPUT-NAME} -o output-hdf-name.json -\``` -``` - -14. Commit your changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, merged, and [released](https://github.com/mitre/saf/wiki/Creating-a-Release-of-the-SAF-CLI), your mapper will be callable using the SAF CLI. - -[placeholder] From 69071d6be874925ef8ab350d2e5a7a31cab526a4 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 19 Jun 2024 15:28:31 -0400 Subject: [PATCH 26/71] Title changes; adding clarification to concepts Signed-off-by: Charles Hu --- src/courses/mappers/09.md | 2 +- src/courses/mappers/10.md | 5 +++-- src/courses/mappers/11.md | 2 +- src/courses/mappers/12.md | 2 +- src/courses/mappers/13.md | 24 ++++++++++++++++++++---- src/courses/mappers/14.md | 4 +++- src/courses/mappers/15.md | 2 +- src/courses/mappers/16.md | 2 +- src/courses/mappers/README.md | 2 ++ 9 files changed, 33 insertions(+), 12 deletions(-) diff --git a/src/courses/mappers/09.md b/src/courses/mappers/09.md index 6b8db59d9..958bc0cbb 100644 --- a/src/courses/mappers/09.md +++ b/src/courses/mappers/09.md @@ -1,7 +1,7 @@ --- order: 9 next: 10.md -title: Getting Started - OHDF Converters +title: Mapper Preparations - OHDF Converters author: Charles Hu --- diff --git a/src/courses/mappers/10.md b/src/courses/mappers/10.md index ac557b5a7..ada3c7e12 100644 --- a/src/courses/mappers/10.md +++ b/src/courses/mappers/10.md @@ -1,7 +1,7 @@ --- order: 10 next: 11.md -title: Getting Started - The Art of Mapper Making +title: Mapper Preparations - The Art of Mapper Making author: Charles Hu --- @@ -31,7 +31,8 @@ Understand how your security data is meant to be consumed in the original securi - How does the original security tool vendor group security data? Is it by type of concern? Where/what component was affected? - What associations does the tool make to common security references (e.g., NIST SP 800-53, CVE, CWE, CCE, OWASP, STIG IDs)? -- What is the purpose of the security tool (vulnerability scanning, information visualization, etc.)? +- What is the purpose of the security tool (e.g., vulnerability scanning, information visualization, etc.)? +- How does the security tool organize its results (e.g., by requirement, by system, etc.)? These answers will help ensure that the intent of the data isn't skewed by the mapping process. It is important to try and "seek parity" with the original display style in the vendor's own tool. In other words, users must be able to recognize and navigate the security data in Heimdall just as easily as they can in the original native format. diff --git a/src/courses/mappers/11.md b/src/courses/mappers/11.md index f881ff143..fc66fd4a4 100644 --- a/src/courses/mappers/11.md +++ b/src/courses/mappers/11.md @@ -1,7 +1,7 @@ --- order: 11 next: 12.md -title: Getting Started - Setting Up +title: Mapper Preparations - Setting Up author: Charles Hu --- diff --git a/src/courses/mappers/12.md b/src/courses/mappers/12.md index 89495c841..f14e97b92 100644 --- a/src/courses/mappers/12.md +++ b/src/courses/mappers/12.md @@ -1,7 +1,7 @@ --- order: 12 next: 13.md -title: Demo - Introduction +title: Mapping Introduction author: Charles Hu --- diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index 31ba173c1..ce6901185 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -1,7 +1,7 @@ --- order: 13 next: 14.md -title: Demo - Mapping a Schema +title: Mapping a Schema author: Charles Hu --- @@ -141,9 +141,27 @@ Let's apply this to our GoSec source data. Try to find the answers to these two Note that this process is subjective and your answers may vary from ours. Don't be so quick to backtrack on your own answers, as your solutions may be as equally valid as ours. There is no objective answer to this process and what's important is that you can identify and break down the source data into useful pieces that we can correlate back to the OHDF schema. +The purpose of this annotation is to understand the intention of the security tool that produced the source data. By breaking down the source data field by field, we can gain a better understanding of how the security tool structures its export data and intends for it to be read by a user. GoSec, for example, organizes its data by security issues because GoSec is intended for code correction and hardening. This manifests in the real world through the user reading the GoSec report issue by issue and solving them as they go along. We can use this knowledge to help guide us in both correlating the schemas and reconfiguring the structure of the source data to fit OHDF. + ### 2. Correlating the Schemas -Now that we're familiar with the specifics of the GoSec schema, we can begin to map these fields to the OHDF schema. +Now that we're familiar with the specifics of the GoSec schema, we can begin to map these fields to the OHDF schema. We'll do this by taking a field in the source data and correlating it to the most applicable OHDF schema field. While performing these correlations, it is important to account for the intention and structure of the source data schema. + +These mapping are informal and do not need to adhere to any programming syntax. The mapping process entails taking the full field path from the source data and placing it as the corresponding value for the OHDF schema field. Proper implementation of these mappings will be done later in the course. An example of such mapping is as follows: +```typescript +{ + profiles: [ + { + controls: [ + { + title: Issues.details + } + ] + } + ] +} +``` +This shows us a mapping of the field `Issues.details` from the source data to the field `profiles.controls.title` in OHDF. Note that since we used an export from GoSec and are not basing our mapping off the full schema, we will inevitably miss some fields. We can rectify this by adding them into our mapping post hoc whenever needed; however, we can still capture these missed fields without manual intervention by using our `passthrough` field to capture unmapped data. @@ -217,8 +235,6 @@ Let's first start with an empty OHDF schema as follows: We can begin our schema correlation by directly porting over fields from the GoSec source data that are obvious: `GosecVersion`, `Issues.rule_id`, `Issues.details`, and `Issues.cwe`. Try to map these fields youself as you follow along and refer to our solution to check your work. -Note that these mapping are informal and do not need to adhere to any programming syntax. Proper implementation of these mappings will be done later in the course. - ::: details OHDF Schema Mapping Ver. 1 ```typescript { diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index 489bdd41f..748b8bcb7 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -1,7 +1,7 @@ --- order: 14 next: 15.md -title: Demo - Implementing a Mapper +title: Implementing a Mapper author: Charles Hu --- @@ -258,3 +258,5 @@ export const fileTypeFingerprints = { ``` ## Mapper Implementation + + diff --git a/src/courses/mappers/15.md b/src/courses/mappers/15.md index 11d444238..a23f3107d 100644 --- a/src/courses/mappers/15.md +++ b/src/courses/mappers/15.md @@ -1,7 +1,7 @@ --- order: 15 next: 16.md -title: Demo - Finalizing the Mapper +title: Finalizing the Mapper author: Charles Hu --- diff --git a/src/courses/mappers/16.md b/src/courses/mappers/16.md index 22ff5ba2b..b46817bc2 100644 --- a/src/courses/mappers/16.md +++ b/src/courses/mappers/16.md @@ -1,6 +1,6 @@ --- order: 16 -title: Demo - More Practice +title: More Practice author: Charles Hu --- diff --git a/src/courses/mappers/README.md b/src/courses/mappers/README.md index 3fc6a078f..d919e4840 100644 --- a/src/courses/mappers/README.md +++ b/src/courses/mappers/README.md @@ -9,6 +9,8 @@ author: Charles Hu The purpose of this class is to provide you with the foundational knowledge needed to create data format mappers for mapping data to the [OASIS Heimdall Data Format (OHDF)](https://saf.mitre.org/framework/normalize). In the following course, you will be taught the art and science of schema translation through a combination of both guided walkthroughs and hands-on demonstrations. +The class is split into 2 sections + ### Objectives By the end of this class, you should be able to achieve the following objectives: From 40b6460f7d2710e572c1b4f9067d006fa4185325 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 19 Jun 2024 15:32:25 -0400 Subject: [PATCH 27/71] Clean up Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 4 ---- 1 file changed, 4 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 345b4a509..61d5ed7f4 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -23,16 +23,12 @@ OASIS Heimdall Data Format (OHDF) is a security data format used to normalize ge - Supports data format conversion from numerous established security tools such as AWS Security Hub's AWS Security Finding Format (ASFF) and Tenable Nessus' Nessus file format. - Allows the integration of currently unsupported security tool data formats through the development of OHDF mappers for the OHDF Converters tool. -[DEV NOTE: Maybe want to throw a graphic here] - ### 2. Preserving data integrity with original source data. - Uses mappings which maximize meaningful schema field conversions. - Leverages schema fields `passthrough` and `raw` to preserve the original data in its entirety. - Allows for bidirectional format conversions to and from OHDF. -[DEV NOTE: Maybe want to throw a graphic here] - ### 3. Maximizing interoperability and data sharing.​ - Provides a consistent and standardized format for communication. From 8267ec520529f32bc88087e781c44101d2101711 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 19 Jun 2024 16:27:07 -0400 Subject: [PATCH 28/71] Flat mappings Signed-off-by: Charles Hu --- src/courses/mappers/12.md | 2 +- src/courses/mappers/13.md | 58 +++++++++++++++++++++++++++++++++++ src/courses/mappers/README.md | 2 +- 3 files changed, 60 insertions(+), 2 deletions(-) diff --git a/src/courses/mappers/12.md b/src/courses/mappers/12.md index f14e97b92..ea31bc42e 100644 --- a/src/courses/mappers/12.md +++ b/src/courses/mappers/12.md @@ -5,7 +5,7 @@ title: Mapping Introduction author: Charles Hu --- -## Demo Introduction +## Mapping Introduction Now that you've finished learning about OHDF and setting up your environment, we can start creating some OHDF mappers. diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index ce6901185..35e1b4d2d 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -235,6 +235,16 @@ Let's first start with an empty OHDF schema as follows: We can begin our schema correlation by directly porting over fields from the GoSec source data that are obvious: `GosecVersion`, `Issues.rule_id`, `Issues.details`, and `Issues.cwe`. Try to map these fields youself as you follow along and refer to our solution to check your work. +::: details Correlated Fields +- `profiles.version` <-> `GosecVersion` + +- `profiles.controls.id` <-> `Issues.rule_id` + +- `profiles.controls.title` <-> `Issues.details` + +- `profiles.controls.tags` <-> `Issues.cwe` +::: + ::: details OHDF Schema Mapping Ver. 1 ```typescript { @@ -363,6 +373,10 @@ We can begin our schema correlation by directly porting over fields from the GoS Next, let's look at `Issues.code`, which can be a little bit tricky. +::: details Correlated Fields +- `profiles.controls.results.code_desc` <-> `Issues.code` +::: + ::: details OHDF Schema Mapping Ver. 2 ```typescript { @@ -482,6 +496,16 @@ Next, let's look at `Issues.code`, which can be a little bit tricky. Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.nosec`, and `Issues.suppressions`. +::: details Correlated Fields +- `profiles.controls.tags` <-> `Issues.severity` + +- `profiles.controls.tags` <-> `Issues.confidence` + +- `profiles.controls.tags` <-> `Issues.nosec` + +- `profiles.controls.tags` <-> `Issues.suppressions` +::: + ::: details OHDF Schema Mapping Ver. 3 ```typescript { @@ -595,6 +619,14 @@ It may be tempting to map `Issues.severity` to `impact`; however, it is importan Next, let's look at the fields `Issues.file`, `Issues.line`, and `Issues.column`. +::: details Correlated Fields +- `profiles.controls.results.message` <-> `Issues.file` + +- `profiles.controls.results.message` <-> `Issues.line` + +- `profiles.controls.results.message` <-> `Issues.column` +::: + ::: details OHDF Schema Mapping Ver. 4 ```typescript { @@ -695,6 +727,12 @@ This is a situation similar to the one `Issues.code` is in. `Issues.file`, `Issu Next, let's look at the fields `Golang errors` and `Stats`. +::: details Correlated Fields +- `passthrough.auxiliary_data` <-> `Golang errors` + +- `passthrough.auxiliary_data` <-> `Stats` +::: + ::: details OHDF Schema Mapping Ver. 5 ```typescript { @@ -783,6 +821,26 @@ For these fields, we can place them in `passthrough` as there are no reasonably Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. +::: details Correlated Fields +- `platform.name` <-> `'Heimdall Tools'` + +- `platform.release` <-> `HeimdallToolsVersion` + +- `version` <-> `HeimdallToolsVersion` + +- `profiles.name` <-> `'Gosec scanner'` + +- `profiles.version` <-> `GosecVersion` + +- `profiles.title` <-> `'gosec'` + +- `profiles.controls.impact` <-> `0.5` + +- `profiles.controls.results.status` <-> `'Failure'` + +- `profiles.status` <-> `'loaded'` +::: + ::: details OHDF Schema Mapping Ver. 6 ```typescript { diff --git a/src/courses/mappers/README.md b/src/courses/mappers/README.md index d919e4840..b34864104 100644 --- a/src/courses/mappers/README.md +++ b/src/courses/mappers/README.md @@ -9,7 +9,7 @@ author: Charles Hu The purpose of this class is to provide you with the foundational knowledge needed to create data format mappers for mapping data to the [OASIS Heimdall Data Format (OHDF)](https://saf.mitre.org/framework/normalize). In the following course, you will be taught the art and science of schema translation through a combination of both guided walkthroughs and hands-on demonstrations. -The class is split into 2 sections +The class is split into 2 sections. The first portion will introduce you to the OHDF schema and its specificities, while the second portion will show you how to apply OHDF schema to mappers for conversions from any security tool data format to OHDF. ### Objectives From 4e57b27a723c49c68f3c0281fe244a6a705422c3 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Thu, 20 Jun 2024 11:25:10 -0400 Subject: [PATCH 29/71] Implementation progress; finalization finished Signed-off-by: Charles Hu --- src/courses/mappers/12.md | 2 +- src/courses/mappers/13.md | 6 +- src/courses/mappers/14.md | 435 +++++++++++++++++++++++++++++++++++++- src/courses/mappers/15.md | 36 ++++ src/courses/mappers/16.md | 1 + src/courses/mappers/17.md | 3 +- 6 files changed, 474 insertions(+), 9 deletions(-) diff --git a/src/courses/mappers/12.md b/src/courses/mappers/12.md index ea31bc42e..a88342acc 100644 --- a/src/courses/mappers/12.md +++ b/src/courses/mappers/12.md @@ -5,7 +5,7 @@ title: Mapping Introduction author: Charles Hu --- -## Mapping Introduction +## Overview Now that you've finished learning about OHDF and setting up your environment, we can start creating some OHDF mappers. diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index 35e1b4d2d..a176df83d 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -8,7 +8,7 @@ author: Charles Hu ## Mapping Introduction ::: note Security Tool Type -This walkthrough is targeted at converting security scans to OHDF. If your security tool provides exports that are not security scans or are APIs, contact the SAF team for further instruction on how to develop those services into a OHDF mapper. +This walkthrough is targeted at converting security scans to OHDF. If your security tool provides exports that are not security scans or are APIs, contact the SAF team for further instruction on how to develop those services into an OHDF mapper. ::: We begin the creation of every OHDF mapper by first planning out how we want correlate the fields in the OHDF and security tool's schemas. This mapping is important for the following reasons: @@ -830,8 +830,6 @@ Finally, let's fill the rest of the empty fields using what available informatio - `profiles.name` <-> `'Gosec scanner'` -- `profiles.version` <-> `GosecVersion` - - `profiles.title` <-> `'gosec'` - `profiles.controls.impact` <-> `0.5` @@ -921,8 +919,6 @@ The reasoning for the filled fields are as follows: - `name: 'Gosec scanner'`: `profiles` refers to the security tool that generated the original source data. In this case, it is the GoSec security scanning tool. -- `version: GosecVersion`: We can import the version of GoSec here. - - `title: 'gosec'`: We can give a succinct title for the profile here. - `impact: 0.5`: We use a default value of `0.5` since we do not have a direct mapping set up to convert the `Issues.severity` field. diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index 748b8bcb7..e8a86bdd2 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -71,6 +71,7 @@ export class SKELETONMapper extends BaseConverter { { name: '', //Insert data title: null, //Insert data + version: null, //Insert data maintainer: null, //Insert data summary: null, //Insert data license: null, //Insert data @@ -148,9 +149,9 @@ Next, we need to add a sample file for the mapper to ingest when running unit te | | | +-- {YOUR-SAMPLE-EXPORT} ``` -### Unit Testing +### Regression Testing -Now that we have a sample file, we can now add some unit tests which automatically test our mapper to ensure that it is producing readable and correct OHDF file outputs. +Now that we have a sample file, we can now add some regression tests which automatically test our mapper to ensure that it is producing readable and correct OHDF file outputs. 1. Create a blank TypeScript file under the `test/mappers/forward` directory in `hdf-converters`. It should be named: ``` @@ -259,4 +260,434 @@ export const fileTypeFingerprints = { ## Mapper Implementation +With the necessary files now set up, we can begin the actual creation of the OHDF mapper using the skeleton mapper base in the `{YOUR-EXPORT-NAME-HERE}-mapper.ts` file. The skeleton mapper and the `base-converter` class have been designed to provide the base functionality needed for *-to-HDF mapper generation. For most developers, mapper creation will be limited to assigning objects from the export structure to correlating attributes in the mapper according to the mappings they developed earlier. + +::: warning File Processing + Certain security services produce exports which are not immediately usable by the skeleton mapper. In such case, pre-processing on the export and or post-processing on the generated OHDF file is necessary in order to ensure compatibility. +::: + +While developing the mapper, it's useful to occassionally check on the outputed OHDF file to check that the mapper is working as intended. You can do this by starting a local instance of Heimdall2 with the following command: +```shell +yarn start:dev +``` + +Import your source data and then export it as an OHDF JSON to check what your mapper is actually mapping. + +### Mapper Demo - GoSec + +This section is a demonstration on implementing an OHDF mapper for GoSec, assuming that the [appropriate file set up for the mapper](#file-set-up) has been performed. + +Here is our developed mapping for GoSec for reference: + +::: details GoSec-to-OHDF Schema Mapping +```typescript +{ + platform: { // We fill in Heimdall for the platform as it handles the generation of this OHDF file + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, // See 'platform' reasoning + statistics: {}, // Not enough info to fill + profiles: [ + { + name: 'Gosec scanner', // We know that this report is generated from GoSec + version: GosecVersion, // Version of GoSec instance + sha256: '', // Leave it empty as OHDF Converters will generate one for us + title: 'gosec', // We know that this report is generated from GoSec + supports: [], // Not enough info to fill + attributes: [], // Not enough info to fill + groups: [], // Not enough info to fill + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc: '', // Not enough info to fill + impact: 0.5, // Have no solid information on impact of security issue, so we default to 0.5 + refs: [], // Not enough info to fill + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + source_location: {}, // Not enough info to fill + results: [ + { + status: 'Failure', // The security scan only reports failed requirements, so all findings we receive get fail statuses + code_desc: Issues.code, // The code failing the requirement test + message: { // All materials describing where the issue occured + Issues.file, + Issues.line, + Issues.column + }, + start_time // Not enough info to fill + } + ] + }, + ], + status: 'loaded' // Give loaded status to denote that profile is loaded by OHDF Converters + }, + ], + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors + name: 'Golang errors', + data: Golang errors + }, + { // Stats on GoSec scan + name: 'Stats', + data: Stats + }, + ], + raw + } +} +``` +::: + +::: details GoSec Annotated Source Data +```json +{ + // Purpose: Go compilation errors + // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: Container for identified security issues + // Recording: Requirements - This entity records all identified security issues in a Go source code + "Issues": [ + { + // Purpose: The severity of the identified issue + // Recording: Requirements - This is specifically related to the severity level of the requirement + "severity": "MEDIUM", + // Purpose: How sure that the identified issue if applicable to this source code + // Recording: Requirements testing - This field gives the applicability of the issue after source code testing + "confidence": "HIGH", + // Purpose: The associated CWE for the security issue + // Recording: Requirements - This gives the associated CWE for the security issue + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + // Purpose: The internal GoSec ID for the security issue + // Recording: Requirements - This gives an ID for the security issue + "rule_id": "G304", + // Purpose: Explanation of the security issue + // Recording: Requirements - This explains the security issue + "details": "Potential file inclusion via variable", + // Purpose: The offending file + // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The offending code + // Recording: Requirement testing - This specifies the code that fails the requirement after source code testing + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + // Purpose: The line number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "line": "83", + // Purpose: The column number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "column": "14", + // Purpose: Whether this security issue should be ignored + // Recording: Requirements - Specifies whether this security issue should be ignored + "nosec": false, + // Purpose: The supression level for info on the security issue + // Recording: Requirements - Specifies the info suppression level of the security issue + "suppressions": null + } + ], + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Meta data - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + // Purpose: The version of the GoSec instance currently running + // Recording: Meta data - Info on the scan itself + "GosecVersion": "dev" +} +``` +::: + +Mapper creation has been streamlined to be as simple as possible for a developer. Most of the work involves simple references to the object path for a field in the source data as so: +```typescript +version: {path: 'GosecVersion'} +``` + +This primarily applies in cases where the field is simply carried over. Some fields from the source data need to be processed or transformed in some way, which will be elaborated upon later. + +#### Unfilled/Omitted and Hard Coded Fields + +First, let's assign mappings which are unfilled/omitted or are not dependent on the source data (i.e., hard coded data). This include fields like our mappings for `profiles.name` and `profiles.sha256` + +::: details GoSec-to-OHDF Mapper +```typescript +import {ExecJSON} from 'inspecjs'; +import _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform +} from './base-converter'; + +const IMPACT_MAPPING: Map = new Map([ + ['critical', 0.9], + ['high', 0.7], + ['medium', 0.5], + ['low', 0.3] +]); + +export class GoSecMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: 'Gosec scanner', + title: 'gosec', + version: null, //Insert data + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + key: 'id', + tags: {}, //Insert data + refs: [], + source_location: {}, + title: null, //Insert data + id: '', //Insert data + desc: '', + impact: 0.5, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: '', //Insert data + message: null, //Insert data + start_time: '' + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed + ...(this.withRaw && {raw: data}) + }; + } + } + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw + } +} +``` +::: + +::: details Remaining GoSec-to-OHDF Schema Mapping +```typescript +{ + profiles: [ + { + version: GosecVersion, // Version of GoSec instance + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + results: [ + { + code_desc: Issues.code, // The code failing the requirement test + message: { // All materials describing where the issue occured + Issues.file, + Issues.line, + Issues.column + } + } + ] + }, + ] + }, + ], + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors + name: 'Golang errors', + data: Golang errors + }, + { // Stats on GoSec scan + name: 'Stats', + data: Stats + }, + ], + raw + } +} +``` +::: + +#### Simple Portable Fields + +Next, let's look at the fields which can be just simply be directly ported over from the source data like `GosecVersion`. To do this, we just need to invoke the `path` keyword from `base-converter` and feed the direct JSON object path as a value like so: +```typescript +version: {path: 'GosecVersion'} +``` + +For nested fields (i.e., fields requiring traversal through parent fields), we need to have the mapper traverse into the level containing the fields we want to access. Think of this as a similar process as using `cd` to traverse through a directory to access a file. For example, if we can allow the access of fields using `path` in the `Issues` superfield in the source data as follows: +```typescript +path: 'Issues' +``` + +Let's put this into practice and start implementing the mappings for simple fields that don't require transformation or processing: + +::: details GoSec-to-OHDF Mapper +```typescript +import {ExecJSON} from 'inspecjs'; +import _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform +} from './base-converter'; + +const IMPACT_MAPPING: Map = new Map([ + ['critical', 0.9], + ['high', 0.7], + ['medium', 0.5], + ['low', 0.3] +]); + +export class GoSecMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: 'Gosec scanner', + title: 'gosec', + version: {path: 'GosecVersion'}, + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + path: 'Issues', + key: 'id', + tags: { + cwe: {path: 'cwe'}, + nosec: {path: 'nosec'}, + suppressions: {path: 'suppressions'}, + severity: {path: 'severity'}, + confidence: {path: 'confidence'} + }, + refs: [], + source_location: {}, + title: {path: 'details'}, + id: {path: 'rule_id'}, + desc: '', + impact: 0.5, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: {path: 'code'}, + message: null, //Insert data + start_time: '' + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed + ...(this.withRaw && {raw: data}) + }; + } + } + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw + } +} +``` +::: + +::: details Remaining GoSec-to-OHDF Schema Mapping +```typescript +{ + profiles: [ + { + controls: [ + { + results: [ + { + message: { // All materials describing where the issue occured + Issues.file, + Issues.line, + Issues.column + } + } + ] + }, + ] + }, + ], + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors + name: 'Golang errors', + data: Golang errors + }, + { // Stats on GoSec scan + name: 'Stats', + data: Stats + }, + ], + raw + } +} +``` +::: + +#### Transformed/Processed Fields + diff --git a/src/courses/mappers/15.md b/src/courses/mappers/15.md index a23f3107d..de902ef80 100644 --- a/src/courses/mappers/15.md +++ b/src/courses/mappers/15.md @@ -5,4 +5,40 @@ title: Finalizing the Mapper author: Charles Hu --- +## Mapper Finalization +Now that we have a mapper developed that can convert files from *-to-OHDF, we need to perform some final touches to make sure that our mapper works and can be integrated into OHDF Converters. + +### Using Regression Testing + +First, we have to activate the regression testing suite that we created earlier to actually be able to automatically run and review your mapper. + +1. Uncomment out the commented out lines in the `{YOUR-SAMPLE-EXPORT}-hdf.json` file. This will allow the regression tests to automatically generate an OHDF output file whenever you run the tests. These files are needed for the tests to check the output of your mappers. The commented out lines should look similar to the following: +```typescript +// fs.writeFileSync( +// 'sample_jsons/SKELETON_mapper/SKELETON-hdf.json', +// JSON.stringify(mapper.toHdf(), null, 2) +// ); +``` + +2. Using the terminal, `cd` into the `hdf-converters` directory and run the following command. This command will run your mapper against the sample export file in `sample_jsons` and test to see if the output is generated as expected. This intial run, however, will be to create a baseline OHDF file for future regression tests to run against. +```shell +yarn run test --verbose --silent=false ./test/mappers/forward/{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts +``` + +3. After running this command, you should see two files named `SKELETON-hdf.json` and `SKELETON-hdf-withraw.json` appear in the `sample_jsons/SKELETON_mapper/` directory. Check these files to make sure that the OHDF mapper output looks correct and aligns with your mapping. `SKELETON-hdf.json` should match your mapping completely, while `SKELETON-hdf-withraw.json` should also include your original source data in the OHDF output file. + +4. Recomment out the lines from step 1. + +3. Future uses of the command in step 2 will now leverage the baseline files you generated to perform regression testing. It will compare the contents of these generated files with temporary outputs created by the mapper instance to check for field alignment. Review the test output to ensure that the tests are all passing. + +### Documentation + +Document your new mapper in the `README.md` file for `hdf-converters` under the `Supported Formats` section. It should be formatted as follows: +```markdown +{#}. [{YOUR-EXPORT-NAME-HERE}] - {MAPPER INPUT DESCRIPTION} +``` + +### GitHub Merging + +Commit your final changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, your mapper will be merged into the main development branch and [scheduled for release](https://github.com/mitre/heimdall2/wiki/How-to-create-a-Heimdall2-release) as an officially supported conversion format for OHDF Converters. diff --git a/src/courses/mappers/16.md b/src/courses/mappers/16.md index b46817bc2..f7a8a6726 100644 --- a/src/courses/mappers/16.md +++ b/src/courses/mappers/16.md @@ -1,5 +1,6 @@ --- order: 16 +next: 17.md title: More Practice author: Charles Hu --- diff --git a/src/courses/mappers/17.md b/src/courses/mappers/17.md index dec53a97c..805d205e0 100644 --- a/src/courses/mappers/17.md +++ b/src/courses/mappers/17.md @@ -1,5 +1,6 @@ --- -order: 16 +order: 17 +next: 18.md title: Next Steps author: Charles Hu --- From cb8010eeb5e7ab26cd0c858e8eceaf2f19d9ce7b Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Thu, 20 Jun 2024 15:17:15 -0400 Subject: [PATCH 30/71] Mapper implementation Signed-off-by: Charles Hu --- src/courses/mappers/13.md | 24 +-- src/courses/mappers/14.md | 410 ++++++++++++++++++++++++++++++++++---- 2 files changed, 380 insertions(+), 54 deletions(-) diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index a176df83d..b4b7c2de0 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -796,14 +796,10 @@ Next, let's look at the fields `Golang errors` and `Stats`. ], passthrough: { auxiliary_data: [ - { // Go source data compilation errors - name: 'Golang errors', - data: Golang errors - }, - { // Stats on GoSec scan - name: 'Stats', - data: Stats - }, + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } ], raw } @@ -891,14 +887,10 @@ Finally, let's fill the rest of the empty fields using what available informatio ], passthrough: { auxiliary_data: [ - { // Go source data compilation errors - name: 'Golang errors', - data: Golang errors - }, - { // Stats on GoSec scan - name: 'Stats', - data: Stats - }, + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } ], raw } diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index e8a86bdd2..72c04aa3a 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -331,14 +331,10 @@ Here is our developed mapping for GoSec for reference: ], passthrough: { auxiliary_data: [ - { // Go source data compilation errors - name: 'Golang errors', - data: Golang errors - }, - { // Stats on GoSec scan - name: 'Stats', - data: Stats - }, + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } ], raw } @@ -432,13 +428,6 @@ import { MappedTransform } from './base-converter'; -const IMPACT_MAPPING: Map = new Map([ - ['critical', 0.9], - ['high', 0.7], - ['medium', 0.5], - ['low', 0.3] -]); - export class GoSecMapper extends BaseConverter { withRaw: boolean; @@ -534,14 +523,10 @@ export class GoSecMapper extends BaseConverter { ], passthrough: { auxiliary_data: [ - { // Go source data compilation errors - name: 'Golang errors', - data: Golang errors - }, - { // Stats on GoSec scan - name: 'Stats', - data: Stats - }, + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } ], raw } @@ -575,13 +560,6 @@ import { MappedTransform } from './base-converter'; -const IMPACT_MAPPING: Map = new Map([ - ['critical', 0.9], - ['high', 0.7], - ['medium', 0.5], - ['low', 0.3] -]); - export class GoSecMapper extends BaseConverter { withRaw: boolean; @@ -673,14 +651,10 @@ export class GoSecMapper extends BaseConverter { ], passthrough: { auxiliary_data: [ - { // Go source data compilation errors - name: 'Golang errors', - data: Golang errors - }, - { // Stats on GoSec scan - name: 'Stats', - data: Stats - }, + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } ], raw } @@ -690,4 +664,364 @@ export class GoSecMapper extends BaseConverter { #### Transformed/Processed Fields +Finally, let's look at fields that require some level of processing before we can use them in the OHDF mapper. + +The fields like `Issues.file`, `Issues.line`, and `Issues.column` need to be combined to make a coherent locational message. We can combine them using a simple function that concatenates them together. The function to do this is provided: +```typescript +function formatMessage(input: Record): string { + return `${_.get(input, 'file')}, line:${_.get(input, 'line')}, column:${_.get(input, 'column')}`; +} +``` +This function just pulls the three fields and joins them into a single string. + +To invoke this, we can use the `transformer` keyword and feed the function as a value for the transformer to invoke. This is implemented as follows: + +::: details GoSec-to-OHDF Mapper +```typescript +import {ExecJSON} from 'inspecjs'; +import _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform +} from './base-converter'; + +function formatMessage(input: Record): string { + return `${_.get(input, 'file')}, line:${_.get(input, 'line')}, column:${_.get( + input, + 'column' + )}`; +} + +export class GoSecMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: 'Gosec scanner', + title: 'gosec', + version: {path: 'GosecVersion'}, + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + path: 'Issues', + key: 'id', + tags: { + cwe: {path: 'cwe'}, + nosec: {path: 'nosec'}, + suppressions: {path: 'suppressions'}, + severity: {path: 'severity'}, + confidence: {path: 'confidence'} + }, + refs: [], + source_location: {}, + title: {path: 'details'}, + id: {path: 'rule_id'}, + desc: '', + impact: 0.5, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: {path: 'code'}, + message: {transformer: formatMessage}, + start_time: '' + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed + ...(this.withRaw && {raw: data}) + }; + } + } + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw + } +} +``` +::: + +::: details Remaining GoSec-to-OHDF Schema Mapping +```typescript +{ + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } + ], + raw + } +} +``` +::: + +We can also combine keywords such as using `path` to traverse to a particular field and then apply a function using `transformer`. For example, we can target the `Issues.cwe` field specifically and apply the following function to create corresponding NIST 800-53s: +```typescript +import {CweNistMapping} from './mappings/CweNistMapping'; + +const CWE_NIST_MAPPING = new CweNistMapping(); +const DEFAULT_NIST_TAG = ['SI-2', 'RA-5']; + +function nistTag(input: Record): string[] { + const cwe = [`${_.get(input, 'id')}`]; + return CWE_NIST_MAPPING.nistFilter(cwe, DEFAULT_NIST_TAG); +} +``` + +We can then correlate it with a `profiles.controls.tags.nist` field in the OHDF mapper as so: + +::: details GoSec-to-OHDF Mapper +```typescript +import {ExecJSON} from 'inspecjs'; +import _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform +} from './base-converter'; +import {CweNistMapping} from './mappings/CweNistMapping'; + +const CWE_NIST_MAPPING = new CweNistMapping(); +const DEFAULT_NIST_TAG = ['SI-2', 'RA-5']; + +function nistTag(input: Record): string[] { + const cwe = [`${_.get(input, 'id')}`]; + return CWE_NIST_MAPPING.nistFilter(cwe, DEFAULT_NIST_TAG); +} + +function formatMessage(input: Record): string { + return `${_.get(input, 'file')}, line:${_.get(input, 'line')}, column:${_.get( + input, + 'column' + )}`; +} + +export class GoSecMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: 'Gosec scanner', + title: 'gosec', + version: {path: 'GosecVersion'}, + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + path: 'Issues', + key: 'id', + tags: { + nist: { + path: 'cwe', + transformer: nistTag + }, + cwe: {path: 'cwe'}, + nosec: {path: 'nosec'}, + suppressions: {path: 'suppressions'}, + severity: {path: 'severity'}, + confidence: {path: 'confidence'} + }, + refs: [], + source_location: {}, + title: {path: 'details'}, + id: {path: 'rule_id'}, + desc: '', + impact: 0.5, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: {path: 'code'}, + message: {transformer: formatMessage}, + start_time: '' + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed + ...(this.withRaw && {raw: data}) + }; + } + } + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw + } +} +``` +::: + +::: details Remaining GoSec-to-OHDF Schema Mapping +```typescript +{ + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } + ], + raw + } +} +``` +::: + +For the remaining fields that we want to place in `passthrough`, we need to use the [lodash library](https://lodash.com/docs/) to preserve the field in its entirety. In particular, we will use the `_.get(OBJECT, FIELD)` command to pull a field from the source data object. + + +::: details GoSec-to-OHDF Mapper +```typescript +import {ExecJSON} from 'inspecjs'; +import _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform +} from './base-converter'; +import {CweNistMapping} from './mappings/CweNistMapping'; + +const CWE_NIST_MAPPING = new CweNistMapping(); +const DEFAULT_NIST_TAG = ['SI-2', 'RA-5']; + +function nistTag(input: Record): string[] { + const cwe = [`${_.get(input, 'id')}`]; + return CWE_NIST_MAPPING.nistFilter(cwe, DEFAULT_NIST_TAG); +} + +function formatMessage(input: Record): string { + return `${_.get(input, 'file')}, line:${_.get(input, 'line')}, column:${_.get( + input, + 'column' + )}`; +} + +export class GoSecMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: 'Gosec scanner', + title: 'gosec', + version: {path: 'GosecVersion'}, + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + path: 'Issues', + key: 'id', + tags: { + nist: { + path: 'cwe', + transformer: nistTag + }, + cwe: {path: 'cwe'}, + nosec: {path: 'nosec'}, + suppressions: {path: 'suppressions'}, + severity: {path: 'severity'}, + confidence: {path: 'confidence'} + }, + refs: [], + source_location: {}, + title: {path: 'details'}, + id: {path: 'rule_id'}, + desc: '', + impact: 0.5, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: {path: 'code'}, + message: {transformer: formatMessage}, + start_time: '' + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [ + { + name: 'Gosec', + data: { + 'Golang errors': _.get(data, 'Golang errors'), + 'Stats': _.get(data, 'Stats') + } + } + ], + ...(this.withRaw && {raw: data}) + }; + } + } + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw + } +} +``` +::: +Now we have a fully implemented GoSec-to-OHDF mapper. From 2020df7f36c7169ad6eb182e5fc41aa2cc7ff23d Mon Sep 17 00:00:00 2001 From: Ryan Lin Date: Thu, 20 Jun 2024 12:51:23 -0700 Subject: [PATCH 31/71] Mapping a Schema - DbProtect Signed-off-by: Ryan Lin --- src/courses/mappers/13.md | 698 +++++++++++++++++++++++++++++++++++++- 1 file changed, 697 insertions(+), 1 deletion(-) diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index b4b7c2de0..cf2bc7e1e 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -2,7 +2,7 @@ order: 13 next: 14.md title: Mapping a Schema -author: Charles Hu +author: Charles Hu, Ryan Lin --- ## Mapping Introduction @@ -921,3 +921,699 @@ The reasoning for the filled fields are as follows: ::: Now we have a finalized mapping for GoSec to OHDF. + + +## Mapping Demo - DbProtect + +It is also possible to convert XML-based results formats. The OHDF library relies on `fast-xml-parser` to convert these XML files into a JSON-like format for compatibility with the base converter. Let us take a look at one such example: The DbProtect Mapper. + +### 1. Breaking Down the Data + +Let's first start with our DbProtect sample. + +::: details DbProtect Source Data +```xml + + + + + + + + + + + + + + + + + + + + + TEST ORGANIZATION (Local DBP server) + Audit + Microsoft SQL Server + CONDS181 + 10.0.10.204, 1433, MSSQLSERVER + Heimdall Test scan report generation + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + Fact + Improper Access Controls + Medium + 2986 + Schema ownership + Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole + Feb 18 2021 15:57 + + + TEST ORGANIZATION (Local DBP server) + Audit + Microsoft SQL Server + CONDS181 + 10.0.10.204, 1433, MSSQLSERVER + Heimdall Test scan report generation + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + Fact + Improper Access Controls + Medium + 2986 + Schema ownership + Schema name=db_accessadmin;Database=AppDetective;Owner name=db_accessadmin + Feb 18 2021 15:57 + + ... + + + +``` +::: + +You may notice that the metadata field maps corresponding keys to each of the values in a row of the data field. Consider ways you might try to restructure this data, but focus mainly on the purpose of each of the values for now. We will handle data restructuring in a later portion. + +Unlike with GoSec, DbProtect does not have a published schema. Thus, we must empirically reason the mapping based on our sample data. Thus, even more so than the previous example, this process is subjective and your mapping may vary from ours. One thing we can use to inform ourselves about the purpose of each field in place of a schema, however, is the metadata fields at the top of the sample. Recall the three questions we ask ourselves to tie back identified purposes to the three general OHDF schema structures: + +- Is this field recording meta data? +- Is this field recording requirements? +- Is this field recording requirement testing? + +Also recall that, for each field in the source data, we should be asking ourselves the following two questions: + +- What is the purpose of this field? +- What is this field recording (meta data, requirements, requirement testing)? + +Let us now apply this philosophy to our DbProtect source data. Try to find the answers to these two questions for each field yourself and then refer back to our annotated solution to check your work. + +::: details DbProtect Annotated Source Data +```xml + + + + + + + + + + + + + + + + + + + + + + + + + TEST ORGANIZATION (Local DBP server) + + + Audit + + + Microsoft SQL Server + + + CONDS181 + + + 10.0.10.204, 1433, MSSQLSERVER + + + Heimdall Test scan report generation + + + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + + + Fact + + + Improper Access Controls + + + Medium + + + 2986 + + + Schema ownership + + + Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole + + + Feb 18 2021 15:57 + + ... + + +``` +::: + +Note that this process is subjective and your answers may vary from ours. Don't be so quick to backtrack on your own answers, as your solutions may be as equally valid as ours. There is no objective answer to this process and what's important is that you can identify and break down the source data into useful pieces that we can correlate back to the OHDF schema. + +### 2. Correlating the Schemas + +Now that we're familiar with the specifics of the DbProtect report structure, we can begin to map these fields to the OHDF schema. + +Note that since we used an export from DbProtect and are not basing our mapping off the full schema, we will inevitably miss some fields. We can rectify this by adding them into our mapping post hoc whenever needed; however, we can still capture these missed fields without manual intervention by using our `passthrough` field to capture unmapped data. + +Let's first start with an empty OHDF schema as follows: + +::: details Empty OHDF Schema +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id, + title, + desc, + descriptions, + impact, + refs, + tags, + code, + source_location, + results: [ + { + status, + code_desc, + message, + run_time, + start_time + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +#### Mapping Version 1 + +We can begin our schema correlation by directly porting over fields from the DbProtect source data that are obvious: `Check ID`, `Result Status`, and `Date`. Try to map these fields yourself, and refer to our solution below to check your work. + +As in the previous example, note that these mapping are informal and do not need to adhere to any programming syntax. Proper implementation of these mappings will be done later in the course. + +::: details Correlated Fields +- `profiles.controls.id` <-> `Check ID` + +- `profiles.controls.results.status` <-> `Result Status` + +- `profiles.controls.results.start_time` <-> `Date` +::: + +::: details OHDF Schema Mapping Ver. 1 +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title, + desc, + descriptions, + impact, + refs, + tags: { + nist, + cci + }, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc, + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +::: details Remaining DbProtect Source Data +```xml + + + + + + + ... + + + + + + TEST ORGANIZATION (Local DBP server) + + + Audit + + + Microsoft SQL Server + + + CONDS181 + + + 10.0.10.204, 1433, MSSQLSERVER + + + Heimdall Test scan report generation + + + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + + + Improper Access Controls + + + Medium + + + Schema ownership + + + Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole + + ... + + +``` +::: + +::: details Reasoning + +- `id: 'Check ID'`: `Check ID` gives us an ID used by DbProtect to identify each failing requirement. + +- `status: 'Result Status'`: `Result Status` gives us information about the result of the scan, whether it passed or failed or was skipped. + +- `start_time: 'Date'`: `Date` provides information about when the scan was run. +::: + +#### Mapping Version 2 + +Now let us handle some of the more detailed information about the specific controls, namely `Task`, `Check Category`, `Risk DV`, `Check`, and `Details`. + +::: details Correlated Fields +- `profiles.controls.desc` <-> `Task`, `Check Category` + +- `profiles.controls.impact` <-> `Risk DV` + +- `profiles.controls.title` <-> `Check` + +- `profiles.controls.results.code_desc` <-> `Details` +::: + +::: details OHDF Schema Mapping Ver. 2 +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title: 'Check', + desc: ['Task', 'Check Category'], + descriptions, + impact: 'Risk DV', + refs, + tags: { + nist, + cci + }, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc: 'Details', + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +::: details Remaining DbProtect Source Data +```xml + + + + + + + ... + + + + + + TEST ORGANIZATION (Local DBP server) + + + Microsoft SQL Server + + + CONDS181 + + + 10.0.10.204, 1433, MSSQLSERVER + + + Heimdall Test scan report generation + + + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + + ... + + +``` +::: + +::: details Reasoning + +For the control description, we want to give information about the type of control being run. Thus, it makes sense to store the category of the check, and the particular task it was for (whether it was for an Audit, or for another reason). + +In this case, we can directly map impact to `Risk DV` because there exists an intuitive mapping: High, Medium, Low, and Informational can map to 0.7, 0.5, 0.3, and 0, respectively. + +Note that `Check` appears to also correspond to the `Check ID`, and is a brief desciption of the check being run. Thus, it would make sense to map it to the title field of a control. + +Finally, for the details, recall that the `code_desc` is looking for the test expectations as defined by the particular control. `Details` is telling us about the particular result's associated parameters. +::: + +#### Mapping Version 3 + +Finally, we are left with the more general, report-level information from our DbProtect sample file: `Organization`, `Asset Type`, `Check Asset`, `IP Address, Port, Instance`, `Job Name`, `Policy`. Notice that OHDF does not have fields that correspond to some of this additional info, so consider ways to condense this data and encode it into other fields. + +::: details Correlated Fields +- `profiles.summary` <-> `Organization`, `Asset`, `Asset Type`, `IP Address, Port, Instance` +- `profiles.title` <-> `Job Name` + +- `profiles.name` <-> `Policy` +::: + +::: details OHDF Schema Mapping Ver. 3 +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name: 'Policy', + version, + sha256, + title: 'Job Name', + maintainer, + summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title: 'Check', + desc: ['Task', 'Check Category'], + descriptions, + impact: 'Risk DV', + refs, + tags: { + nist, + cci + }, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc: 'Details', + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +::: details Reasoning +- `profiles.summary` <-> `Organization`, `Asset`, `Asset Type`, `IP Address, Port, Instance` +- `profiles.title` <-> `Job Name` + +- `profiles.name` <-> `Policy` + +As mentioned previously, OHDF does not have a specific place to put information like the `Organization`, `Asset`, or `Asset Type`. However, we do have a summary field for profiles. Recall our goal of preserving as much data as possible from the source. With this in mind, it would be reasonable to map all these fields to the summary for the sake of preservation. + +The profile name and title fields are a little tricky. Note that the `Policy` field refers to the baseline guidance that the scan tested against. This aligns more with the profile name than the `Job Name`, which is just the a name the customer added for the report. Thus, we map the `Policy` field to the `profiles.name` and the `Job Name` field to the `profiles.title` instead. +::: + +#### Mapping Version 4 + +Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. + +::: details Correlated Fields +- `platform.name` <-> `'Heimdall Tools'` + +- `platform.release` <-> `HeimdallToolsVersion` + +- `version` <-> `HeimdallToolsVersion` + +- `profiles.controls.tags.nist` <-> `DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS` + +- `profiles.controls.tags.cci` <-> `DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS` + +- `profiles.status` <-> `'loaded'` +::: + +::: details OHDF Schema Mapping Ver. 3 +```typescript +{ + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id + }, + version: HeimdallToolsVersion, + statistics: { + duration + }, + profiles: [ + { + name: 'Policy', + version, + sha256, + title: 'Job Name', + maintainer, + summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title: 'Check', + desc: ['Task', 'Check Category'], + descriptions, + impact: 'Risk DV', + refs, + tags: { + nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + cci: DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS + }, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc: 'Details', + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + status: 'loaded' + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +::: details Reasoning +Unfilled fields are a result of a lack of sufficent information from the source data that can be used to reasonably associate with these fields. + +The reasoning for the filled fields are as follows: + +- `platform: {name: 'Heimdall Tools'}`: `platform` refers to the instance generating the OHDF file, which in this case is Heimdall2 or Heimdall Tools. + +- `platform: {release: HeimdallToolsVersion}`: Similar reasoning as above. + +- `version: HeimdallToolsVersion`: Similar reasoning as `platform` fields. + +- `profiles.controls.tags.nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS`: The DbProtect sample does not have any associated NIST tags within it. Thus, we use the default tags for a static code analysis. + +- `profiles.controls.tags.cci: DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS`: Similar reasoning as above. + +- `status: 'loaded'`: The status of a profile is typically `loaded` since it has been ingested and converted to OHDF. +::: + +Now we have a finalized mapping for DbProtect to OHDF. From 567ff307084b3d9191e07e2ba04195394af22d16 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Thu, 20 Jun 2024 15:52:05 -0400 Subject: [PATCH 32/71] Practice examples Signed-off-by: Charles Hu --- src/courses/mappers/16.md | 129 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 129 insertions(+) diff --git a/src/courses/mappers/16.md b/src/courses/mappers/16.md index f7a8a6726..b36115534 100644 --- a/src/courses/mappers/16.md +++ b/src/courses/mappers/16.md @@ -5,4 +5,133 @@ title: More Practice author: Charles Hu --- +The following are some practice source data sets to create mappers with. +## JFrog Xray + +[Based on this mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/jfrog-xray-mapper.ts). + +::: details Source Data +```json +{ + "total_count": 1, + "data": [ + { + "id": "", + "severity": "High", + "summary": "Acorn regexp.js Regular Expression Validation UTF-16 Surrogate Handling Infinite Loop DoS", + "issue_type": "security", + "provider": "JFrog", + "component": "acorn", + "source_id": "npm://acorn", + "source_comp_id": "npm://acorn:5.7.3", + "component_versions": { + "id": "acorn", + "vulnerable_versions": [ + "5.5.0 ≤ Version < 5.7.4", + "6.0.0 ≤ Version < 6.4.1", + "7.0.0", + "7.1.0" + ], + "fixed_versions": ["5.7.4", "6.4.1", "7.1.1"], + "more_details": { + "cves": [ + { + "cvss_v2": "7.1/AV:N/AC:M/Au:N/C:N/I:N/A:C", + "cvss_v3": "7.5/CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H" + } + ], + "description": "Acorn contains an infinite loop condition in regexp.js that is triggered when handling UTF_16 surrogates while validating regular expressions. This may allow a context-dependent attacker to hang a process using the library.", + "provider": "JFrog" + } + }, + "edited": "2020-11-03T19:30:42-05:00" + } + ] +} +``` +::: + +## Twistlock + +[Based on this mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/twistlock-mapper.ts). + +::: details Source Data +```json +{ + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "collections": ["All", "TEST-COLLECTION"], + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } + ], + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceDistribution": { + "critical": 0, + "high": 0, + "medium": 0, + "low": 0, + "total": 0 + }, + "complianceScanPassed": true, + "vulnerabilities": [ + { + "id": "CVE-2021-43529", + "status": "affected", + "cvss": 9.8, + "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "severity": "critical", + "packageName": "nss-util", + "packageVersion": "3.67.0-7.el8_5", + "link": "https://access.redhat.com/security/cve/CVE-2021-43529", + "riskFactors": [ + "Remote execution", + "Attack complexity: low", + "Attack vector: network", + "Critical severity", + "Recent vulnerability" + ], + "impactedVersions": ["*"], + "publishedDate": "2021-12-01T00:00:00Z", + "discoveredDate": "2022-05-18T12:24:22Z", + "layerTime": "2022-05-16T23:12:25Z" + } + ], + "vulnerabilityDistribution": { + "critical": 1, + "high": 0, + "medium": 0, + "low": 0, + "total": 1 + }, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-16T23:12:02Z", + "instruction": "ARG GOPROXY=http://nexus-repository-manager.nexus-repository-manager.svc.cluster.local:8081/repository/goproxy/ HTTP_PROXY=http://localhost:3128 http_proxy=http://localhost:3128" + } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" +} +``` +::: From 929bd003e3320eb8df9b3842d95ba1394b04f4b1 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Fri, 21 Jun 2024 11:27:35 -0400 Subject: [PATCH 33/71] Appendix - SAF CLI Signed-off-by: Charles Hu --- src/courses/mappers/18.md | 271 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 271 insertions(+) create mode 100644 src/courses/mappers/18.md diff --git a/src/courses/mappers/18.md b/src/courses/mappers/18.md new file mode 100644 index 000000000..1f0c2368f --- /dev/null +++ b/src/courses/mappers/18.md @@ -0,0 +1,271 @@ +--- +order: 18 +title: Appendix - SAF CLI Integration +author: Charles Hu +--- + +## SAF CLI Integration + +The following is a supplemental lesson on how to integrate your developed mapper with the SAF CLI. Integration with the SAF CLI will allow your mapper to be used in a command line environment, independent of Heimdall2. + +If you have not yet created a mapper, please follow the primary course and do so. Once completed, you will be able to continue with this lesson. + +### Set Up + +First, we need set up the necessary files to begin integrating your mapper with the SAF CLI. + +1. Create a development branch against the [SAF CLI repository](https://github.com/mitre/saf) and create a draft pull request for your new branch. + +2. In the `package.json` file, update the versions of `@mitre/hdf-converters` and `@mitre/heimdall-lite` to the [latest release of Heimdall2](https://github.com/mitre/heimdall2/releases). + +3. In the `src/commands/convert` directory, create a blank TypeScript file. It should be named: +``` +{YOUR-EXPORT-NAME-HERE}2hdf.ts +``` + +4. In the `test/sample_data` directory, create a directory named `{YOUR-EXPORT-NAME-HERE}`. Underneath it, create a directory named `sample_input_report`. The file structure should now look like this: +``` ++-- sample_data +| +-- {YOUR-EXPORT-NAME-HERE} +| | +-- sample_input_report +``` + +5. Place your sample export under the `sample_input_report` directory. Your sample export should be genericized to avoid any leaking of sensitive information. Under the `{YOUR-EXPORT-NAME-HERE}` directory, place your output OHDF files generated during the original testing phase of your mapper development. The file structure should now look like this: +``` ++-- sample_data +| +-- {YOUR-EXPORT-NAME-HERE} +| | +-- sample_input_report +| | | +-- {YOUR-SAMPLE-EXPORT} +| | +-- {YOUR-EXPORT-NAME-HERE}-hdf.json +| | +-- {YOUR-EXPORT-NAME-HERE}-hdf-withraw.json +``` + +6. In the `test/commands/convert` directory, create a blank TypeScript file. It should be named: +``` +{YOUR-EXPORT-NAME-HERE}2hdf.test.ts +``` + +### Integration + +With file set up out of the way, we can begin filling out the necessary files to create a `saf convert` command for our mapper. + +1. Insert the skeleton convert command file (see below) in the file `{YOUR-EXPORT-NAME-HERE}2hdf.ts` which you created earlier. Replace names (`SKELETON` by default) as necessary. + +::: details Skeleton Convert Command File +```typescript +import {Command, Flags} from '@oclif/core' +import fs from 'fs' +import {SKELETONMapper as Mapper} from '@mitre/hdf-converters' +import {checkSuffix} from '../../utils/global' + +export default class SKELETON2HDF extends Command { + static usage = 'convert SKELETON2hdf -i -o ' + + static description = 'Translate a SKELETON output file into an HDF results set' + + static examples = ['saf convert SKELETON2hdf -i SKELETON.json -o output-hdf-name.json'] + + static flags = { + help: Flags.help({char: 'h'}), + input: Flags.string({char: 'i', required: true, description: 'Input SKELETON file'}), + output: Flags.string({char: 'o', required: true, description: 'Output HDF file'}), + 'with-raw': Flags.boolean({char: 'w', required: false}), + } + + async run() { + const {flags} = await this.parse(SKELETON2HDF) + const input = fs.readFileSync(flags.input, 'utf8') + + const converter = new Mapper(input, flags.['with-raw']) + fs.writeFileSync(checkSuffix(flags.output), JSON.stringify(converter.toHdf())) + } +} +``` +::: + +2. Insert the appropriate skeleton convert command test file (see below) in the file `{YOUR-EXPORT-NAME-HERE}2hdf.test.ts` which you created earlier. Replace names (`SKELETON` by default) as necessary. + +::: details JSON Skeleton Convert Command Test File +```typescript +import {expect, test} from '@oclif/test' +import tmp from 'tmp' +import path from 'path' +import fs from 'fs' +import {omitHDFChangingFields} from '../utils' + +describe('Test SKELETON', () => { + const tmpobj = tmp.dirSync({unsafeCleanup: true}) + + test + .stdout() + .command([ + 'convert SKELETON2hdf', + '-i', + path.resolve( + './test/sample_data/SKELETON/sample_input_report/SKELETON_sample.json', + ), + '-o', + `${tmpobj.name}/SKELETONtest.json`, + ]) + .it('hdf-converter output test', () => { + const converted = JSON.parse( + fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, 'utf8'), + ) + const sample = JSON.parse( + fs.readFileSync( + path.resolve('./test/sample_data/SKELETON/SKELETON-hdf.json'), + 'utf8', + ), + ) + expect(omitHDFChangingFields(converted)).to.eql( + omitHDFChangingFields(sample), + ) + }) +}) + +describe('Test SKELETON withraw flag', () => { + const tmpobj = tmp.dirSync({unsafeCleanup: true}) + + test + .stdout() + .command([ + 'convert SKELETON2hdf', + '-i', + path.resolve( + './test/sample_data/SKELETON/sample_input_report/SKELETON_sample.json', + ), + '-o', + `${tmpobj.name}/SKELETONtest.json`, + '-w', + ]) + .it('hdf-converter withraw output test', () => { + const converted = JSON.parse( + fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, 'utf8'), + ) + const sample = JSON.parse( + fs.readFileSync( + path.resolve('./test/sample_data/SKELETON/SKELETON-hdf-withraw.json'), + 'utf8', + ), + ) + expect(omitHDFChangingFields(converted)).to.eql( + omitHDFChangingFields(sample), + ) + }) +}) +``` +::: + +::: details XML Skeleton Convert Command Test File +```typescript +import {expect, test} from '@oclif/test' +import tmp from 'tmp' +import path from 'path' +import fs from 'fs' +import {omitHDFChangingFields} from '../utils' + +describe('Test SKELETON', () => { + const tmpobj = tmp.dirSync({unsafeCleanup: true}) + + test + .stdout() + .command([ + 'convert SKELETON2hdf', + '-i', + path.resolve( + './test/sample_data/SKELETON/sample_input_report/SKELETON_sample.xml', + ), + '-o', + `${tmpobj.name}/SKELETONtest.json`, + ]) + .it('hdf-converter output test', () => { + const converted = JSON.parse( + fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, 'utf8'), + ) + const sample = JSON.parse( + fs.readFileSync( + path.resolve('./test/sample_data/SKELETON/SKELETON-hdf.json'), + 'utf8', + ), + ) + expect(omitHDFChangingFields(converted)).to.eql( + omitHDFChangingFields(sample), + ) + }) +}) + +describe('Test SKELETON withraw flag', () => { + const tmpobj = tmp.dirSync({unsafeCleanup: true}) + + test + .stdout() + .command([ + 'convert SKELETON2hdf', + '-i', + path.resolve( + './test/sample_data/SKELETON/sample_input_report/SKELETON_sample.xml', + ), + '-o', + `${tmpobj.name}/SKELETONtest.json`, + '-w', + ]) + .it('hdf-converter withraw output test', () => { + const converted = JSON.parse( + fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, 'utf8'), + ) + const sample = JSON.parse( + fs.readFileSync( + path.resolve('./test/sample_data/SKELETON/SKELETON-hdf-withraw.json'), + 'utf8', + ), + ) + expect(omitHDFChangingFields(converted)).to.eql( + omitHDFChangingFields(sample), + ) + }) +}) +``` +::: + +3. Navigate to the `index.ts` file under the `src/commands/convert` directory. Import your mapper using the existing import block as follows: +```typescript +import { + ASFFResults, + ... + {YOUR-MAPPER-CLASS-HERE} +} from '@mitre/hdf-converters' +``` + +4. Under the switch block in the `getFlagsForInputFile` function, add your mapper class as it is defined for fingerprinting for the generic convert command. If the convert command for your mapper has any additional flags beyond the standard `--input` and `--output` flags, return the entire flag block in the switch case. This is demonstrated as follows: +```typescript +switch (Convert.detectedType) { + ... + case {YOUR-EXPORT-SERVICE-NAME-HERE}: + return {YOUR-CLI-CONVERT-CLASS}.flags //Only add if special flags exist + ... + return {} +} +``` + +5. Edit the `README.md` file to reflect your newly added conversion command under the `Convert To HDF` section. It should be formatted as follows: + +```markdown +##### {YOUR-EXPORT-NAME-HERE} to HDF + +\``` +convert {YOUR-EXPORT-NAME-HERE}2hdf Translate a {YOUR-EXPORT-NAME-HERE} results {EXPORT-TYPE} into an HDF results set + + USAGE + $ saf convert {YOUR-EXPORT-NAME-HERE}hdf -i <{INPUT-NAME}> -o + + OPTIONS + -i, --input=input Input {EXPORT-TYPE} File + -o, --output=output Output HDF JSON File + -w, --with-raw Include raw input file in HDF JSON file + + EXAMPLES + $ saf convert {YOUR-EXPORT-NAME-HERE}2hdf -i {INPUT-NAME} -o output-hdf-name.json +\``` +``` + +5. Commit your changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, merged, and [released](https://github.com/mitre/saf/wiki/Creating-a-Release-of-the-SAF-CLI), your mapper will be callable using the SAF CLI. From 43a1656df19be8b4b81f3a00e1323cb0b8ab62d4 Mon Sep 17 00:00:00 2001 From: Ryan Lin Date: Fri, 21 Jun 2024 10:51:00 -0700 Subject: [PATCH 34/71] Mapping implementation DbProtect Signed-off-by: Ryan Lin --- src/courses/mappers/13.md | 2 +- src/courses/mappers/14.md | 670 ++++++++++++++++++++++++++++++++++++++ 2 files changed, 671 insertions(+), 1 deletion(-) diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index cf2bc7e1e..a3a5d8729 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -1531,7 +1531,7 @@ Finally, let's fill the rest of the empty fields using what available informatio - `profiles.status` <-> `'loaded'` ::: -::: details OHDF Schema Mapping Ver. 3 +::: details OHDF Schema Mapping Ver. 4 ```typescript { platform: { diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index 72c04aa3a..cfba117b7 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -1025,3 +1025,673 @@ export class GoSecMapper extends BaseConverter { ::: Now we have a fully implemented GoSec-to-OHDF mapper. + + +### Mapper Demo - DbProtect + +This section is a demonstration for implementing an OHDF mapper that handles XML-based source data, namely DbProtect. As in the previous section, we assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. + +Here is our developed mapping for DbProtect for reference: + +::: details DbProtect-to-OHDF Schema Mapping +```typescript +{ + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id + }, + version: HeimdallToolsVersion, + statistics: { + duration + }, + profiles: [ + { + name: 'Policy', + version, + sha256, + title: 'Job Name', + maintainer, + summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title: 'Check', + desc: ['Task', 'Check Category'], + descriptions, + impact: 'Risk DV', + refs, + tags: { + nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + cci: DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS + }, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc: 'Details', + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + status: 'loaded' + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +::: details DbProtect Annotated Source Data +```xml + + + + + + + + + + + + + + + + + + + + + + + + + TEST ORGANIZATION (Local DBP server) + + + Audit + + + Microsoft SQL Server + + + CONDS181 + + + 10.0.10.204, 1433, MSSQLSERVER + + + Heimdall Test scan report generation + + + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + + + Fact + + + Improper Access Controls + + + Medium + + + 2986 + + + Schema ownership + + + Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole + + + Feb 18 2021 15:57 + + ... + + +``` +::: + +As in the previous GoSec example, most of the work involves simple references to the object path for a field in the source data. For example: + +```typescript +title: {path: 'Check'} +``` + +Again, some fields from the source data need to be processed or transformed in some way, which will be elaborated upon later. + +#### Unfilled/Omitted and Hard Coded Fields + +First, let's assign mappings which are unfilled/omitted or are not dependent on the source data (i.e., hard coded data). This include fields like our mappings for `platform.name` and `profiles.sha256`. Note that for our tags, we use the global method in the Heimdall repo, `getCCIsForNISTTags`, as well as the global constant `DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS`. We can also just directly put the source data into the passthrough. Also note the `compileFindings` function we wrote to deal with the strange structure of the XML, which has metadata correlated with each row in the data field. No need to worry about this function for now - just think of it as a way of assigning the metadata keys to each data row explicitly, so that our base converter has a way to easily access fields and know what they are. + +::: details DbProtect-to-OHDF Mapper +```typescript +import {ExecJSON} from 'inspecjs'; +import * as _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, + parseXml +} from './base-converter'; + +function compileFindings( + input: Record +): Record { + const keys = _.get(input, 'dataset.metadata.item'); + const findings = _.get(input, 'dataset.data.row'); + + let output: unknown[] = []; + + if (Array.isArray(keys) && Array.isArray(findings)) { + const keyNames = keys.map((element: Record): string => { + return _.get(element, 'name') as string; + }); + output = findings.map((element: Record) => { + return Object.fromEntries( + keyNames.map(function (name: string, i: number) { + return [name, _.get(element, `value[${i}]`)]; + }) + ); + }); + } + return Object.fromEntries([['data', output]]); +} + +export class DBProtectMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: {}, + title: {}, + summary: {}, + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + key: 'id', + tags: { + nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + cci: getCCIsForNISTTags(DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS) + }, + refs: [], + source_location: {}, + title: {}, + id: {}, + desc: {}, + impact: {}, + code: {}, + results: [ + { + status: {}, + code_desc: {}, + start_time: {}, + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return {...(this.withRaw && {raw: data})}; + } + } + }; + constructor(dbProtectXml: string, withRaw = false) { + super(compileFindings(parseXml(dbProtectXml))); + this.withRaw = withRaw; + } +} +``` +::: + +::: details Remaining DbProtect-to-OHDF Schema Mapping +```typescript +{ + profiles: [ + { + name: 'Policy', + title: 'Job Name', + maintainer, + summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title: 'Check', + desc: ['Task', 'Check Category'], + descriptions, + impact: 'Risk DV', + refs, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc: 'Details', + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + }, + ] +} +``` +::: + +#### Simple Portable Fields + +Next, let's look at the fields which can be just simply be directly ported over from the source data like `Policy`. To do this, we just need to invoke the `path` keyword from `base-converter` and feed the direct JSON object path as a value like so: +```typescript +name: {path: 'data.[0].Policy'} +``` +Note that in this example, we must call the path with `data.[0]`, since even though the Policy is the same fo all data rows, we still must specify an element to extract the data from. + +Let's put this into practice and start implementing the mappings for simple fields that don't require transformation or processing: + +::: details DbProtect-to-OHDF Mapper +```typescript +import {ExecJSON} from 'inspecjs'; +import * as _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, + parseXml +} from './base-converter'; + +function compileFindings( + input: Record +): Record { + const keys = _.get(input, 'dataset.metadata.item'); + const findings = _.get(input, 'dataset.data.row'); + + let output: unknown[] = []; + + if (Array.isArray(keys) && Array.isArray(findings)) { + const keyNames = keys.map((element: Record): string => { + return _.get(element, 'name') as string; + }); + output = findings.map((element: Record) => { + return Object.fromEntries( + keyNames.map(function (name: string, i: number) { + return [name, _.get(element, `value[${i}]`)]; + }) + ); + }); + } + return Object.fromEntries([['data', output]]); +} + +export class DBProtectMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: {path: 'data.[0].Policy'}, + title: {path: 'data.[0].Job Name'}, + summary: {}, + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + path: 'data', + key: 'id', + tags: { + nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + cci: getCCIsForNISTTags(DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS) + }, + refs: [], + source_location: {}, + title: {path: 'Check'}, + id: {}, + desc: {}, + impact: {}, + code: {}, + results: [ + { + status: {}, + code_desc: {path: 'Details'}, + start_time: {path: 'Date'}, + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return {...(this.withRaw && {raw: data})}; + } + } + }; + constructor(dbProtectXml: string, withRaw = false) { + super(compileFindings(parseXml(dbProtectXml))); + this.withRaw = withRaw; + } +} +``` +::: + +::: details Remaining DbProtect-to-OHDF Schema Mapping +```typescript +{ + profiles: [ + { + maintainer, + summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + desc: ['Task', 'Check Category'], + descriptions, + impact: 'Risk DV', + refs, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + message, + run_time, + } + ] + }, + ], + }, + ] +} +``` +::: + +#### Transformed/Processed Fields + +As in the previous example, there are several fields that need to be processed further. To do so, we can make use of the `transformer` field supported by the OHDF Converters library. Firstly, some simple transformes include casting the `id` field to a string, and mapping the `impact` fields properly (by creating a mapping and passing it into the `impactMapping` function in `base-converter`): + +```typescript +const IMPACT_MAPPING: Map = new Map([ + ['high', 0.7], + ['medium', 0.5], + ['low', 0.3], + ['informational', 0] +]); + +function idToString(id: unknown): string { + if (typeof id === 'string' || typeof id === 'number') { + return id.toString(); + } else { + return ''; + } +} +``` + +For the OHDF fields that concatenate information from multiple DbProtect fields, we must write corresponding transformers that format these strings: +```typescript +function formatSummary(entry: unknown): string { + const text = []; + text.push(`Organization : ${_.get(entry, 'Organization')}`); + text.push(`Asset : ${_.get(entry, 'Check Asset')}`); + text.push(`Asset Type : ${_.get(entry, 'Asset Type')}`); + text.push(`IP Address, Port, Instance : ${_.get(entry, 'Asset Type')}`); + text.push( + `IP Address, Port, Instance : ${_.get( + entry, + 'IP Address, Port, Instance' + )} ` + ); + return text.join('\n'); +} + +function formatDesc(entry: unknown): string { + const text = []; + text.push(`Task : ${_.get(entry, 'Task')}`); + text.push(`Check Category : ${_.get(entry, 'Check Category')}`); + return text.join('; '); +} +``` +Finally, we write one more function to map the `Result Status` to the proper `ExecJSON` statuses: +```typescript +function getStatus(input: unknown): ExecJSON.ControlResultStatus { + switch (input) { + case 'Fact': + return ExecJSON.ControlResultStatus.Skipped; + case 'Failed': + return ExecJSON.ControlResultStatus.Failed; + case 'Finding': + return ExecJSON.ControlResultStatus.Failed; + case 'Not A Finding': + return ExecJSON.ControlResultStatus.Passed; + } + return ExecJSON.ControlResultStatus.Skipped; +} +``` +Writing out all these transformers and applying them to the mapping fed into `base-converter` looks something like this: + +:::details +```typescript +import {ExecJSON} from 'inspecjs'; +import * as _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, + parseXml +} from './base-converter'; +import { + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + getCCIsForNISTTags +} from './utils/global'; + +const IMPACT_MAPPING: Map = new Map([ + ['high', 0.7], + ['medium', 0.5], + ['low', 0.3], + ['informational', 0] +]); + +function compileFindings( + input: Record +): Record { + const keys = _.get(input, 'dataset.metadata.item'); + const findings = _.get(input, 'dataset.data.row'); + + let output: unknown[] = []; + + if (Array.isArray(keys) && Array.isArray(findings)) { + const keyNames = keys.map((element: Record): string => { + return _.get(element, 'name') as string; + }); + output = findings.map((element: Record) => { + return Object.fromEntries( + keyNames.map(function (name: string, i: number) { + return [name, _.get(element, `value[${i}]`)]; + }) + ); + }); + } + return Object.fromEntries([['data', output]]); +} + +function formatSummary(entry: unknown): string { + const text = []; + text.push(`Organization : ${_.get(entry, 'Organization')}`); + text.push(`Asset : ${_.get(entry, 'Check Asset')}`); + text.push(`Asset Type : ${_.get(entry, 'Asset Type')}`); + text.push(`IP Address, Port, Instance : ${_.get(entry, 'Asset Type')}`); + text.push( + `IP Address, Port, Instance : ${_.get( + entry, + 'IP Address, Port, Instance' + )} ` + ); + return text.join('\n'); +} + +function formatDesc(entry: unknown): string { + const text = []; + text.push(`Task : ${_.get(entry, 'Task')}`); + text.push(`Check Category : ${_.get(entry, 'Check Category')}`); + return text.join('; '); +} + +function getStatus(input: unknown): ExecJSON.ControlResultStatus { + switch (input) { + case 'Fact': + return ExecJSON.ControlResultStatus.Skipped; + case 'Failed': + return ExecJSON.ControlResultStatus.Failed; + case 'Finding': + return ExecJSON.ControlResultStatus.Failed; + case 'Not A Finding': + return ExecJSON.ControlResultStatus.Passed; + } + return ExecJSON.ControlResultStatus.Skipped; +} + +function idToString(id: unknown): string { + if (typeof id === 'string' || typeof id === 'number') { + return id.toString(); + } else { + return ''; + } +} + +export class DBProtectMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: {path: 'data.[0].Policy'}, + title: {path: 'data.[0].Job Name'}, + summary: {path: 'data.[0]', transformer: formatSummary}, + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + path: 'data', + key: 'id', + tags: { + nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + cci: getCCIsForNISTTags(DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS) + }, + refs: [], + source_location: {}, + title: {path: 'Check'}, + id: {path: 'Check ID', transformer: idToString}, + desc: {transformer: formatDesc}, + impact: { + path: 'Risk DV', + transformer: impactMapping(IMPACT_MAPPING) + }, + code: { + transformer: (vulnerability: Record): string => + JSON.stringify(vulnerability, null, 2) + }, + results: [ + { + status: {path: 'Result Status', transformer: getStatus}, + code_desc: {path: 'Details'}, + start_time: {path: 'Date'}, + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return {...(this.withRaw && {raw: data})}; + } + } + }; + constructor(dbProtectXml: string, withRaw = false) { + super(compileFindings(parseXml(dbProtectXml))); + this.withRaw = withRaw; + } +} +``` +::: + +Now we have a fully implemented DbProtect-to-OHDF mapper. From e975cf03fc18af6fa483f1e4b9ddbf11696ca9f6 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Fri, 21 Jun 2024 13:58:01 -0400 Subject: [PATCH 35/71] Proofreading; CVSS Signed-off-by: Charles Hu --- src/courses/mappers/06.md | 2 +- src/courses/mappers/README.md | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index bc7734992..9e42a3f83 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -104,7 +104,7 @@ controls: [ - `title`: Title of control. - `desc`: Description of the control. - `descriptions`: Additional descriptions; usually 'check' and 'fix' text for control. -- `impact`: Security severity of control. +- `impact`: Security severity of control. On a scale of 0.1 to 1. This metric is aligned with the [Common Vulnerability Scoring System (CVSS)](https://www.first.org/cvss/). - `refs`: References to external control documentation. - `tags`: Control tags; typically correlate to existing vulnerability/weakness database (e.g., NIST, CVE, CWE). - `code`: Control source code for code preservation. diff --git a/src/courses/mappers/README.md b/src/courses/mappers/README.md index b34864104..e0b231ffa 100644 --- a/src/courses/mappers/README.md +++ b/src/courses/mappers/README.md @@ -7,9 +7,9 @@ author: Charles Hu ## Overview -The purpose of this class is to provide you with the foundational knowledge needed to create data format mappers for mapping data to the [OASIS Heimdall Data Format (OHDF)](https://saf.mitre.org/framework/normalize). In the following course, you will be taught the art and science of schema translation through a combination of both guided walkthroughs and hands-on demonstrations. +The purpose of this class is to provide you with the foundational knowledge needed to create data format mappers for mapping data to the [OASIS Heimdall Data Format (OHDF)](https://saf.mitre.org/framework/normalize). In the following course, you will be taught the art and science of schema translation through a combination of both guided explanations and hands-on demonstrations. -The class is split into 2 sections. The first portion will introduce you to the OHDF schema and its specificities, while the second portion will show you how to apply OHDF schema to mappers for conversions from any security tool data format to OHDF. +The class is split into 2 sections. The first portion will introduce you to the OHDF schema and its specificities, while the second portion will show you how to apply the OHDF schema to mappers for conversions from any security tool data format to OHDF. ### Objectives From e58fefaa97bf22090b69a5dd80c5521fc81efd4f Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 24 Jun 2024 11:01:33 -0400 Subject: [PATCH 36/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 4 +++- src/courses/mappers/03.md | 8 +++---- src/courses/mappers/04.md | 50 +++++++++++++++------------------------ 3 files changed, 26 insertions(+), 36 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 61d5ed7f4..8121eacb1 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -9,6 +9,8 @@ author: Charles Hu OASIS Heimdall Data Format (OHDF) is a security data format used to normalize generated data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security validation profiles, controls, and results. +OASIS Open is an international standards body that works on the development and advancement of open source technological standards. OHDF is currently in the process of becoming an OASIS Open standard. + ## Why OHDF? - Many security tools do not provide context to relevant compliance standards for comparison across security tools.​ @@ -39,7 +41,7 @@ OASIS Heimdall Data Format (OHDF) is a security data format used to normalize ge - Provides a clear schema for technologies/processes to support. - Includes a simple file format that technologies/processes can accept. -### 5. Allowing for the mapping and enrichment of security data to relevant compliance standards (GDPR, NIST SP 800-53, PCI-DSS, etc.). +### 5. Allowing for the mapping and enrichment of security data to relevant compliance standards (GDPR, NIST SP 800-53, CCIs, PCI-DSS, etc.). - Uses mappers which provide and append relevant compliance standards to converted security tool data. diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index 3e803d205..dcb0a817c 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -7,7 +7,7 @@ author: Charles Hu ## Where Is OHDF Used? -OHDF is part of the SAF normalization process (see below) and is officially implemented and used in a plethora of tools and libraries including InspecJS, OHDF Converters, the SAF CLI, and Heimdall2. +OHDF is part of the SAF normalization process (see below) and is officially implemented and used in a plethora of tools and libraries including InspecJS, OHDF Converters, the SAF CLI, and Heimdall. ![](./img/saf_security_validation_lifecycle.png) @@ -17,12 +17,12 @@ OHDF is part of the SAF normalization process (see below) and is officially impl ## What Is OHDF Converters? -[OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated into [Heimdall2](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification within an automated build pipeline. +[OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated into [Heimdall](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification within an automated build pipeline. ## What Is the SAF CLI? The [SAF CLI](https://github.com/mitre/saf) is a tool that provides various automation support functions for CI/CD. One of its main functions is the `saf convert` command, which allows for the conversion of data between OHDF and several supported security tool data formats. -## What Is Heimdall2? +## What Is Heimdall? -[Heimdall2](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. Data that is imported into Heimdall2 is automatically converted to OHDF through OHDF Converters, which serves as the underlying library that services data format conversion requests in Heimdall2. \ No newline at end of file +[Heimdall](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. Data that is imported into Heimdall is automatically converted to OHDF through OHDF Converters, which serves as the underlying library that services data format conversion requests in Heimdall. \ No newline at end of file diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index b6269b310..177946e33 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -7,69 +7,57 @@ author: Charles Hu ## What Is a Mapper? -A mapper is a design pattern used to correlate (or map) items in two different objects with one another. Mappers are useful in that they allow us to connect items in objects that are nominally different but semantically the same. A result of this is that we can easily transform one object type into another through the use of mappings which define the direct relationship of items in each object type. +A mapper is an instance of an adapter design pattern which is used to correlate (or map) items in two different objects with one another. Mappers are useful in that they allow us to correlate values in objects that are nominally different but semantically the same. A result of this is that we can easily transform one object type into another through the use of mappings which define the direct relationship of values in each object type. An important aspect of the transformation process is that while the objects containing the values are transformed, the values themselves typically remain the same. -Here are some scenarios which demonstrate some key aspects of mappers: +Mappings are the actual correlation of values between two different objects. They are the basis for mappers and are responsible for defining which values between two objects are semantically the same. Mappers are the implementation of mappings which perform the necessary processing to transform the objects according to relationships found in the mappings. In order to have a mapper that is as accurate as possible in its transformations, the mappings should ideally include correlations for all values in the objects. + +Here is a scenario which demonstrates some key aspects of mappers: ::: details Transferring IDs -Say we have to transfer the credentials of an employee who is moving from Business A to Business B. The data formats the businesses use for IDs are as follows: +Say we have a business that is changing its employee identification software and needs to transfer the current credentials of its employees from Software A to Software B. The data formats the softwares use for IDs are as follows: ```json -// Business A +// Software A {Name, DoB, Age, Title} -// Business B +// Software B {employee, employeeBirthday, employeeAge, jobTitle} ``` -How do we transfer John's credentials from Business A to Business B? +How do we transfer John's credentials from Software A to Software B? ```json {Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} ``` -What we can do is create a mapping which correlates the items from Business A's ID scheme to Business B's: +What we can do is create a mapping which correlates the items from Software A's ID scheme to Software B's: ```json {employee: Name, employeeBirthday: DoB, employeeAge: Age, jobTitle: Title} ``` -With this, we can then develop a mapper which takes John's credentials from Business A and transforms it to Business B's format as so: +With this, we can then develop a mapper which takes John's credentials from Software A and transforms it to Software B's format as so: ```json {Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} - || -\ / - \/ + || + \ / + \/ -MAPPER + MAPPER - || -\ / - \/ + || + \ / + \/ {employee: 'John Doe', employeeBirthday: 10-6-1992, employeeAge: 32, jobTitle: 'Security Technician'} ``` The important thing to note here is that mappers rely on underlying mappings which match semantically similar fields between two objects. These matches allow us to correctly convert each item in one object to the other. -::: - -::: details Translating a foreign language -Say we are given the job to translate the traditional Chinese sentence '我愛貓' into English. -Without knowledge of the language, this is an impossible task. - -However, say we now also had a mapper which utilized the following mapping: -```json -{'愛': 'love', '我': 'I', '貓': 'cats'} -``` - -Now this task becomes much more easier. We can apply this mapper which will translate the sentence from '我愛貓' to 'I love cats' and vice versa. - -The important thing to note here is that mappers make translating between two objects trivial, which means that anyone can do it and we can automate mappers to perform object conversions for us. +Also note that mappers make translating between two objects trivial, which means that anyone can do it and we can automate mappers to perform object conversions for us. ::: - ## What Is an OHDF Mapper? -An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security tool data format to another overarching security tool data format. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to HDF (\*-to-HDF) and vice versa (HDF-to-\*) using the tools provided by the existing conversion infrastructure. +An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security tool data format to another overarching security tool data format. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to OHDF (\*-to-OHDF) and vice versa (OHDF-to-\*) using the tools provided by the existing conversion infrastructure. OHDF mappers are built upon the schemas that define the involved data formats, and the mechanics of the mappers revolve around correlating each schema's fields as accurately as possible. From 5a5ce418192d85ae441d9ba578a23fba3e37ef89 Mon Sep 17 00:00:00 2001 From: Ryan Lin Date: Mon, 24 Jun 2024 09:49:34 -0700 Subject: [PATCH 37/71] Added aside sections for 800-53, CCIs, and RMF Signed-off-by: Ryan Lin --- src/courses/mappers/02.md | 14 ++++++++++++++ src/courses/mappers/14.md | 2 +- 2 files changed, 15 insertions(+), 1 deletion(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 8121eacb1..bbe25bbe2 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -45,6 +45,20 @@ OASIS Open is an international standards body that works on the development and - Uses mappers which provide and append relevant compliance standards to converted security tool data. +this is gonna be an area where we actually do a lot of background knowledge training for the student. do one of those aside sections to provide background and context for rmf and then nist 800-53 and then cci. link the latest version of the documents and show an example of nist control family / cci + + +:::details Aside: More on RMF, NIST 800-53, and CCI + +The Risk Management Framework (**RMF**) is a general process that integrates security, privacy, and risk management activities into the development life cycle. More info can be found [here](https://csrc.nist.gov/projects/risk-management/about-rmf). + +National Institute of Standards and Technology (**NIST 800-53**) is a compliance standard created by the US government that contains a set of rules that every system must fulfill. More info can be found [here](https://secureframe.com/blog/nist-800-53-compliance). + +Control Correlation Identifiers (**CCIs**) are standard identifiers and descriptions that aim to correlate high-level policy expressions and low-level technical implementations. More info can be found [here](https://public.cyber.mil/stigs/cci/#:~:text=The%20Control%20Correlation%20Identifier%20%28CCI%29%20provides%20a%20standard,between%20high-level%20policy%20expressions%20and%20low-level%20technical%20implementations.) + +::: + + ## What Else? You can read more about OHDF [here](https://saf.mitre.org/framework/normalize). diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index cfba117b7..b4ed4367a 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -1534,7 +1534,7 @@ function getStatus(input: unknown): ExecJSON.ControlResultStatus { ``` Writing out all these transformers and applying them to the mapping fed into `base-converter` looks something like this: -:::details +:::details Full Mapper Code ```typescript import {ExecJSON} from 'inspecjs'; import * as _ from 'lodash'; From 21da7f239e82b0cef1c8723641f218bffb07d5c7 Mon Sep 17 00:00:00 2001 From: Ryan Lin Date: Mon, 24 Jun 2024 11:11:22 -0700 Subject: [PATCH 38/71] More context for OHDF within the SAF Signed-off-by: Ryan Lin --- src/courses/mappers/03.md | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index dcb0a817c..58cb042c8 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -7,7 +7,14 @@ author: Charles Hu ## Where Is OHDF Used? -OHDF is part of the SAF normalization process (see below) and is officially implemented and used in a plethora of tools and libraries including InspecJS, OHDF Converters, the SAF CLI, and Heimdall. +The SAF has five core capabilities, which you can read more about [here](../user/03.md). Here is how OHDF relates to these five pillars: + +- **Plan**: The OHDF spec is written such that it includes all the information described in the guidance, as well as all the relavant metadata. Thus, the information is carried alongside the results. +- **Harden**: The OHDF spec is not really relevant in this case. +- **Validate**: InSpec's results format is a subset of the OHDF spec. This means that InSpec itself is natively supported! Moreover, it's easy to write InSpec such that all the guidance information is passed through into both the OHDF profile and OHDF results formats. +- **Normalize**: Normalization is the primary use of OHDF. With the use of OHDF Converters, we are able to map many different security results formats to a standard format (OHDF). These converters can either be implemented directly, or accessed via the SAF CLI. +- **Visualize**: OHDF is ingested by a variety of tools (ex. Heimdall) and transformed in many different ways. For example, a results file can be turned into a threshold file for pipeline use, turned into a POAM for ingestion by eMASS, or ingested by Heimdall directly for display purposes. + ![](./img/saf_security_validation_lifecycle.png) From ad56537c81bbea596c29cafd3649b19477af411f Mon Sep 17 00:00:00 2001 From: Ryan Lin Date: Mon, 24 Jun 2024 11:17:40 -0700 Subject: [PATCH 39/71] Added examples for NIST tags and CCIs Signed-off-by: Ryan Lin --- src/courses/mappers/02.md | 19 +++++++++++++++++-- 1 file changed, 17 insertions(+), 2 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index bbe25bbe2..0d8cd723d 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -52,9 +52,24 @@ this is gonna be an area where we actually do a lot of background knowledge trai The Risk Management Framework (**RMF**) is a general process that integrates security, privacy, and risk management activities into the development life cycle. More info can be found [here](https://csrc.nist.gov/projects/risk-management/about-rmf). -National Institute of Standards and Technology (**NIST 800-53**) is a compliance standard created by the US government that contains a set of rules that every system must fulfill. More info can be found [here](https://secureframe.com/blog/nist-800-53-compliance). +National Institute of Standards and Technology (**NIST 800-53**) is a compliance standard created by the US government that contains a set of rules that every system must fulfill. More info can be found [here](https://secureframe.com/blog/nist-800-53-compliance). Here is an example of a NIST control: -Control Correlation Identifiers (**CCIs**) are standard identifiers and descriptions that aim to correlate high-level policy expressions and low-level technical implementations. More info can be found [here](https://public.cyber.mil/stigs/cci/#:~:text=The%20Control%20Correlation%20Identifier%20%28CCI%29%20provides%20a%20standard,between%20high-level%20policy%20expressions%20and%20low-level%20technical%20implementations.) +``` +AC-12: Session Termination + +Automatically terminate a user session after [Assignment: organization-defined conditions, or trigger events requiring session disconnect]. +``` + +Control Correlation Identifiers (**CCIs**) are standard identifiers and descriptions that aim to correlate high-level policy expressions and low-level technical implementations. More info can be found [here](https://public.cyber.mil/stigs/cci/#:~:text=The%20Control%20Correlation%20Identifier%20%28CCI%29%20provides%20a%20standard,between%20high-level%20policy%20expressions%20and%20low-level%20technical%20implementations.). Here is an example of a CCI: +``` +CCI-000002: Disseminate the organization-level; mission/business process-level; and/or system-level access control policy that addresses purpose, scope, roles, responsibilities, management commitment, coordination among organizational entities, and compliance to organization-defined personnel or roles. + +References: +- NIST: NIST SP 800-53 (v3): AC-1 a +- NIST: NIST SP 800-53 Revision 4 (v4): AC-1 a 1 +- NIST: NIST SP 800-53 Revision 5 (v5): AC-1 a 1 (a) +- NIST: NIST SP 800-53A (v1): AC-1.1 (iii) +``` ::: From 7aa33cb50b7472bb7f48d6faa053d76c6ef8a15d Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 24 Jun 2024 18:12:26 -0400 Subject: [PATCH 40/71] Formatting, tone alignment Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 17 +++++++-------- src/courses/mappers/03.md | 25 ++++++++++++++++------ src/courses/mappers/img/heimdall_view.png | Bin 0 -> 168257 bytes 3 files changed, 26 insertions(+), 16 deletions(-) create mode 100644 src/courses/mappers/img/heimdall_view.png diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 0d8cd723d..9b0eba5c4 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -9,7 +9,7 @@ author: Charles Hu OASIS Heimdall Data Format (OHDF) is a security data format used to normalize generated data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security validation profiles, controls, and results. -OASIS Open is an international standards body that works on the development and advancement of open source technological standards. OHDF is currently in the process of becoming an OASIS Open standard. +OASIS Open is an international standards body that works on the development and advancement of open source technological standards. OHDF is currently in the process of becoming an OASIS Open standard. For more information on the OHDF charter for OASIS Open, [refer here](https://groups.oasis-open.org/communities/tc-community-home2?CommunityKey=f8888caa-8401-46f8-bf10-018dc7d3f577). ## Why OHDF? @@ -40,27 +40,28 @@ OASIS Open is an international standards body that works on the development and - Provides a clear schema for technologies/processes to support. - Includes a simple file format that technologies/processes can accept. +- Compatible with [Heimdall](./03.md#what-is-heimdall) to provide data visualization. ### 5. Allowing for the mapping and enrichment of security data to relevant compliance standards (GDPR, NIST SP 800-53, CCIs, PCI-DSS, etc.). - Uses mappers which provide and append relevant compliance standards to converted security tool data. -this is gonna be an area where we actually do a lot of background knowledge training for the student. do one of those aside sections to provide background and context for rmf and then nist 800-53 and then cci. link the latest version of the documents and show an example of nist control family / cci +:::note What Are All These Abbreviations? +The aforementioned terms are all security compliance related guidelines, frameworks, or implementations. The following are explanations on terms that are commonly used in this course: -:::details Aside: More on RMF, NIST 800-53, and CCI +:::details NIST RMF, NIST 800-53, and CCI -The Risk Management Framework (**RMF**) is a general process that integrates security, privacy, and risk management activities into the development life cycle. More info can be found [here](https://csrc.nist.gov/projects/risk-management/about-rmf). - -National Institute of Standards and Technology (**NIST 800-53**) is a compliance standard created by the US government that contains a set of rules that every system must fulfill. More info can be found [here](https://secureframe.com/blog/nist-800-53-compliance). Here is an example of a NIST control: +- The National Institute of Standards and Technology Risk Management Framework (NIST RMF) is a general security compliance framework that integrates security, privacy, and risk management activities into the development life cycle. More information can be found [here](https://csrc.nist.gov/projects/risk-management/about-rmf). +- National Institute of Standards and Technology Special Publication 800-53 (**NIST SP 800-53**) is a compliance standard created by the U.S. government that contains a set of rules that every system must fulfill. More information can be found [here](https://secureframe.com/blog/nist-800-53-compliance). An example of a NIST control is as follows: ``` AC-12: Session Termination Automatically terminate a user session after [Assignment: organization-defined conditions, or trigger events requiring session disconnect]. ``` -Control Correlation Identifiers (**CCIs**) are standard identifiers and descriptions that aim to correlate high-level policy expressions and low-level technical implementations. More info can be found [here](https://public.cyber.mil/stigs/cci/#:~:text=The%20Control%20Correlation%20Identifier%20%28CCI%29%20provides%20a%20standard,between%20high-level%20policy%20expressions%20and%20low-level%20technical%20implementations.). Here is an example of a CCI: +- Control Correlation Identifiers (**CCIs**) are standard identifiers and descriptions that aim to correlate high-level policy expressions and low-level technical implementations of security requirements. More information can be found [here](https://public.cyber.mil/stigs/cci/). An example of a CCI is as follows: ``` CCI-000002: Disseminate the organization-level; mission/business process-level; and/or system-level access control policy that addresses purpose, scope, roles, responsibilities, management commitment, coordination among organizational entities, and compliance to organization-defined personnel or roles. @@ -70,10 +71,8 @@ References: - NIST: NIST SP 800-53 Revision 5 (v5): AC-1 a 1 (a) - NIST: NIST SP 800-53A (v1): AC-1.1 (iii) ``` - ::: - ## What Else? You can read more about OHDF [here](https://saf.mitre.org/framework/normalize). diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index 58cb042c8..8ce3dfc93 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -7,17 +7,26 @@ author: Charles Hu ## Where Is OHDF Used? -The SAF has five core capabilities, which you can read more about [here](../user/03.md). Here is how OHDF relates to these five pillars: +OHDF is a cornerstone of the Security Automation Framework and is officially implemented and used in a plethora of tools and libraries including InspecJS, OHDF Converters, the SAF CLI, and Heimdall. -- **Plan**: The OHDF spec is written such that it includes all the information described in the guidance, as well as all the relavant metadata. Thus, the information is carried alongside the results. -- **Harden**: The OHDF spec is not really relevant in this case. -- **Validate**: InSpec's results format is a subset of the OHDF spec. This means that InSpec itself is natively supported! Moreover, it's easy to write InSpec such that all the guidance information is passed through into both the OHDF profile and OHDF results formats. -- **Normalize**: Normalization is the primary use of OHDF. With the use of OHDF Converters, we are able to map many different security results formats to a standard format (OHDF). These converters can either be implemented directly, or accessed via the SAF CLI. -- **Visualize**: OHDF is ingested by a variety of tools (ex. Heimdall) and transformed in many different ways. For example, a results file can be turned into a threshold file for pipeline use, turned into a POAM for ingestion by eMASS, or ingested by Heimdall directly for display purposes. +## What Is the Security Automation Framework? +The Security Automation Framework (SAF) is a DevSecOps framework which provides a suite of tools for assessing, applying, and managing the security compliance of computer systems. SAF has five core capabilities, of which OHDF is involved in varying degrees: + +- **Plan**: OHDF is defined such that it includes all information described in the guidance, as well as relavant meta data. Thus, the information provided by the guidance are incorporated with the security tool results. + +- **Harden**: OHDF is not typically used in this capability. + +- **Validate**: InSpec's results format is a subset of the OHDF, meaning that InSpec is natively supported. Moreover, it's easy to write InSpec such that all the guidance information is passed through into both the OHDF profile and OHDF results formats. + +- **Normalize**: Normalization is the primary use of OHDF. With the use of OHDF Converters, we are able to map many different security results formats to a standard format (OHDF). These converters can either be accessed directly or via the SAF CLI. + +- **Visualize**: OHDF is ingested by a variety of tools and transformed in many different ways. For example, a results file can be turned into a threshold file for pipeline use, turned into a POAM for ingestion by eMASS, or ingested by Heimdall directly for display purposes. ![](./img/saf_security_validation_lifecycle.png) +You can read more about SAF [here](../user/03.md). + ## What Is InspecJS? [InspecJS](https://github.com/mitre/heimdall2/tree/master/libs/inspecjs) is a library that provides schema definitions, classes, and utilities for OHDF file handling. InspecJS plays a pivotal role in the contextualization process where it converts the individual statuses for each finding into an overall status for the control. @@ -32,4 +41,6 @@ The [SAF CLI](https://github.com/mitre/saf) is a tool that provides various auto ## What Is Heimdall? -[Heimdall](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. Data that is imported into Heimdall is automatically converted to OHDF through OHDF Converters, which serves as the underlying library that services data format conversion requests in Heimdall. \ No newline at end of file +[Heimdall](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. 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Charles Hu --- src/courses/mappers/03.md | 4 ++-- src/courses/mappers/04.md | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index 8ce3dfc93..b392838b2 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -29,11 +29,11 @@ You can read more about SAF [here](../user/03.md). ## What Is InspecJS? -[InspecJS](https://github.com/mitre/heimdall2/tree/master/libs/inspecjs) is a library that provides schema definitions, classes, and utilities for OHDF file handling. InspecJS plays a pivotal role in the contextualization process where it converts the individual statuses for each finding into an overall status for the control. +[InspecJS](https://github.com/mitre/heimdall2/tree/master/libs/inspecjs) is a library that provides schema definitions, classes, and utilities for OHDF file handling. InspecJS plays a pivotal role in the contextualization process where it performs tasks such as converting the individual statuses for each finding into an overall status for the control. ## What Is OHDF Converters? -[OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated into [Heimdall](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification within an automated build pipeline. +[OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated in tools such as [Heimdall](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification for systems such as automated build pipelines. ## What Is the SAF CLI? diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 177946e33..bdd0bb21d 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -57,7 +57,7 @@ Also note that mappers make translating between two objects trivial, which means ## What Is an OHDF Mapper? -An OHDF mapper is a mapper that allows the underlying conversion infrastructure found in OHDF Converters to correlate certain objects or values from one overarching security tool data format to another overarching security tool data format. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to OHDF (\*-to-OHDF) and vice versa (OHDF-to-\*) using the tools provided by the existing conversion infrastructure. +An OHDF mapper is a mapper specifically focused on transforming security tool data formats to and from OHDF. It consists of a mapping and a number of helper functions which facilitate the actual application of the mapping. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to OHDF (\*-to-OHDF) and vice versa (OHDF-to-\*) using the tools provided by the existing conversion infrastructure. OHDF mappers are built upon the schemas that define the involved data formats, and the mechanics of the mappers revolve around correlating each schema's fields as accurately as possible. From b621f18e79424fcdaa4909be91a7de2c69208451 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Tue, 25 Jun 2024 11:40:07 -0400 Subject: [PATCH 42/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/03.md | 10 +- src/courses/mappers/04.md | 272 +------------------ src/courses/mappers/10.md | 6 +- src/courses/mappers/12.md | 4 +- src/courses/mappers/13.md | 14 +- src/courses/mappers/14.md | 16 +- src/courses/mappers/img/saf_cli_features.png | Bin 0 -> 93978 bytes 7 files changed, 31 insertions(+), 291 deletions(-) create mode 100644 src/courses/mappers/img/saf_cli_features.png diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index b392838b2..e7d04176f 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -37,10 +37,18 @@ You can read more about SAF [here](../user/03.md). ## What Is the SAF CLI? -The [SAF CLI](https://github.com/mitre/saf) is a tool that provides various automation support functions for CI/CD. One of its main functions is the `saf convert` command, which allows for the conversion of data between OHDF and several supported security tool data formats. +The Security Automation Framework Command Line Interface (SAF CLI) brings together applications, techniques, libraries, and tools developed by MITRE and the security community to streamline security automation for systems and DevOps pipelines. + +An example of a typical use case of the SAF CLI is for security automation support for CI/CD. This process utilizes the `saf convert` command, which allows for the conversion of data between OHDF and several supported security tool data formats. The SAF CLI is set up to automatically ingest security reports generated from the build pipeline and can forward the newly generated OHDF files to a visualizer such as Heimdall which allows a security assessor to review the state of the current software build. + +![SAF CLI Utility Overview](./img/saf_cli_features.png) ## What Is Heimdall? [Heimdall](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. Data that is imported into Heimdall is automatically converted to OHDF through OHDF Converters, which serves as the underlying library that services data format conversion requests in Heimdall. ![An instance of Heimdall visualizing a security result set](./img/heimdall_view.png) + +## Knowledge Check + + diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index bdd0bb21d..5cddf4a4d 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -57,274 +57,6 @@ Also note that mappers make translating between two objects trivial, which means ## What Is an OHDF Mapper? -An OHDF mapper is a mapper specifically focused on transforming security tool data formats to and from OHDF. It consists of a mapping and a number of helper functions which facilitate the actual application of the mapping. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to OHDF (\*-to-OHDF) and vice versa (OHDF-to-\*) using the tools provided by the existing conversion infrastructure. +An OHDF mapper is a mapper specifically focused on transforming security tool data formats to and from OHDF. It consists of a mapping and a number of helper functions which facilitate the actual application of the mapping. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to OHDF (\*-to-OHDF) and vice versa (OHDF-to-\*) using helper functions and utilities provided by the existing conversion infrastructure in OHDF Converters. -OHDF mappers are built upon the schemas that define the involved data formats, and the mechanics of the mappers revolve around correlating each schema's fields as accurately as possible. - -### Examples - -The following section show some simplified examples of security tool data that has been converted to OHDF using OHDF mappers. - -Here are some key questions to keep note of while reading through these examples: - -- How is the source data structured/organized (e.g., by requirement, by target system, by finding)? -- How is the OHDF file structured? -- Where are data fields in the source data going when converted to OHDF? - -#### GoSec - -::: details Source Data -```json -{ - "Golang errors": {}, - "Issues": [ - { - "severity": "MEDIUM", - "confidence": "HIGH", - "cwe": { - "id": "22", - "url": "https://cwe.mitre.org/data/definitions/22.html" - }, - "rule_id": "G304", - "details": "Potential file inclusion via variable", - "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", - "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - "line": "83", - "column": "14", - "nosec": false, - "suppressions": null - } - ], - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - }, - "GosecVersion": "dev" -} -``` -::: - -::: details Converted OHDF File -```json -{ - "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, - "version": "2.10.8", - "statistics": {}, - "profiles": [ - { - "name": "Gosec scanner", - "title": "gosec", - "version": "dev", - "supports": [], - "attributes": [], - "groups": [], - "status": "loaded", - "controls": [ - { - "tags": { - "nist": ["SI-10"], - "cwe": { - "id": "22", - "url": "https://cwe.mitre.org/data/definitions/22.html" - }, - "nosec": "", - "suppressions": "", - "severity": "MEDIUM", - "confidence": "HIGH" - }, - "refs": [], - "source_location": {}, - "title": "Potential file inclusion via variable", - "id": "G304", - "desc": "", - "impact": 0.5, - "results": [ - { - "status": "failed", - "code_desc": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - "message": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go, line:83, column:14", - "start_time": "" - } - ] - } - ], - "sha256": "d0506f4b7715bf8b1cd81a8a87ab8efcce41ebeb2b5ec5fcfb23d3bdd136f48c" - } - ], - "passthrough": { - "auxiliary_data": [{ "name": "Gosec", "data": { "Golang errors": {} } }] - } -} -``` -::: - -#### Twistlock - -::: details Source Data -```json -{ - "results": [ - { - "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", - "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", - "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", - "distroRelease": "RHEL8", - "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", - "collections": ["All", "TEST-COLLECTION"], - "packages": [ - { - "type": "os", - "name": "nss-util", - "version": "3.67.0-7.el8_5", - "licenses": ["MPLv2.0"] - } - ], - "applications": [ - { - "name": ".net-core", - "version": "5.0.17", - "path": "/usr/lib64/dotnet/dotnet" - } - ], - "complianceDistribution": { - "critical": 0, - "high": 0, - "medium": 0, - "low": 0, - "total": 0 - }, - "complianceScanPassed": true, - "vulnerabilities": [ - { - "id": "CVE-2021-43529", - "status": "affected", - "cvss": 9.8, - "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", - "severity": "critical", - "packageName": "nss-util", - "packageVersion": "3.67.0-7.el8_5", - "link": "https://access.redhat.com/security/cve/CVE-2021-43529", - "riskFactors": [ - "Remote execution", - "Attack complexity: low", - "Attack vector: network", - "Critical severity", - "Recent vulnerability" - ], - "impactedVersions": ["*"], - "publishedDate": "2021-12-01T00:00:00Z", - "discoveredDate": "2022-05-18T12:24:22Z", - "layerTime": "2022-05-16T23:12:25Z" - } - ], - "vulnerabilityDistribution": { - "critical": 5, - "high": 1, - "medium": 86, - "low": 5, - "total": 97 - }, - "vulnerabilityScanPassed": true, - "history": [ - { - "created": "2022-05-03T08:38:31Z" - } - ], - "scanTime": "2022-05-18T12:24:32.855444532Z", - "scanID": "6284e580d9600f8d0db159e2" - } - ], - "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" -} -``` -::: - -::: details Converted OHDF File -```json -{ - "platform": { - "name": "Heimdall Tools", - "release": "2.10.8", - "target_id": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a" - }, - "version": "2.10.8", - "statistics": {}, - "profiles": [ - { - "name": "Twistlock Scan", - "title": "Twistlock Project: All / TEST-COLLECTION", - "summary": "Package Vulnerability Summary: 97 Application Compliance Issue Total: 0", - "supports": [], - "attributes": [], - "groups": [], - "status": "loaded", - "controls": [ - { - "tags": { - "nist": ["SI-2", "RA-5"], - "cci": ["CCI-002605", "CCI-001643"], - "cveid": "CVE-2021-43529" - }, - "refs": [], - "source_location": {}, - "title": "CVE-2021-43529", - "id": "CVE-2021-43529", - "desc": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", - "impact": 0.9, - "code": "{\n \"id\": \"CVE-2021-43529\",\n \"status\": \"affected\",\n \"cvss\": 9.8,\n \"description\": \"DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec\",\n \"severity\": \"critical\",\n \"packageName\": \"nss-util\",\n \"packageVersion\": \"3.67.0-7.el8_5\",\n \"link\": \"https://access.redhat.com/security/cve/CVE-2021-43529\",\n \"riskFactors\": [\n \"Remote execution\",\n \"Attack complexity: low\",\n \"Attack vector: network\",\n \"Critical severity\",\n \"Recent vulnerability\"\n ],\n \"impactedVersions\": [\n \"*\"\n ],\n \"publishedDate\": \"2021-12-01T00:00:00Z\",\n \"discoveredDate\": \"2022-05-18T12:24:22Z\",\n \"layerTime\": \"2022-05-16T23:12:25Z\"\n}", - "results": [ - { - "status": "failed", - "code_desc": "Package \"nss-util\" should be updated to latest version above impacted versions [\"*\"]", - "message": "Expected latest version of \"nss-util\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-util\"", - "start_time": "2022-05-18T12:24:22Z" - } - ] - } - ], - "sha256": "998180601124e9d2b4f03be239a5bb68d9045ba2dc5a26fa2c8d453500288b2e" - } - ], - "passthrough": { - "auxiliary_data": [ - { - "name": "Twistlock", - "data": { - "results": [ - { - "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", - "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", - "distroRelease": "RHEL8", - "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", - "packages": [ - { - "type": "os", - "name": "nss-util", - "version": "3.67.0-7.el8_5", - "licenses": ["MPLv2.0"] - } - ], - "applications": [ - { - "name": ".net-core", - "version": "5.0.17", - "path": "/usr/lib64/dotnet/dotnet" - } - ], - "complianceScanPassed": true, - "vulnerabilityScanPassed": true, - "history": [{ "created": "2022-05-03T08:38:31Z" }], - "scanTime": "2022-05-18T12:24:32.855444532Z", - "scanID": "6284e580d9600f8d0db159e2" - } - ], - "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" - } - } - ] - } -} -``` -::: +OHDF mappers are built upon an understanding of the security tool data format (whether through formal schemas or on-hand export examples) and the OHDF schema, and the mechanics of the mappers revolve around correlating the fields in each as accurately as possible. diff --git a/src/courses/mappers/10.md b/src/courses/mappers/10.md index ada3c7e12..83a3db61f 100644 --- a/src/courses/mappers/10.md +++ b/src/courses/mappers/10.md @@ -7,7 +7,7 @@ author: Charles Hu ## The Art of Mapper Making -Mapper creation is an inherently tricky process as every situation demands a unique and tailored solution. As a result, there is no one objective best template or process to follow as schema translations will always be designed on a case-by-case basis. +Mapper creation is an inherently tricky process as every situation demands a unique and tailored solution. As a result, there is no one objective best template or process to follow as field translations will always be designed on a case-by-case basis. But don't fret! Mapper making, like many forms of development, is a skill you have to cultivate and improve at. So while there is no one-size-fits-all solution, you can still train yourself to produce mappers that are the best for your needs and uses. @@ -17,13 +17,13 @@ To help in improving your mapper making skills, the following section details a ### 1. Reach Out -Don't be afraid to reach out to the SAF team for assistance with mapper development. Our developers can help you with everything from schema mapping decisions to mapper integration with OHDF Converters. +Don't be afraid to reach out to the SAF team for assistance with mapper development. Our developers can help you with everything from mapping decisions to mapper integration with OHDF Converters. You can contact us through email (saf@groups.mitre.org) for inquiries and by creating a [GitHub issue on the Heimdall2 repository](https://github.com/mitre/heimdall2/issues/new/choose) for technical implementation issues. ### 2. Reference Existing Solutions -Try to browse and reference existing solutions in [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) to glean some insight to how previous schema mappers were implemented. Through this, you might be able to find potential solutions to issues you encounter while making your mapper. +Try to browse and reference existing solutions in [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) to glean some insight to how previous mappers were implemented. Through this, you might be able to find potential solutions to issues you encounter while making your mapper. ### 3. Understand Your Security Tool and Data diff --git a/src/courses/mappers/12.md b/src/courses/mappers/12.md index a88342acc..b896a2781 100644 --- a/src/courses/mappers/12.md +++ b/src/courses/mappers/12.md @@ -13,9 +13,9 @@ The rest of this course will consist of practice examples demonstrating and expl The following is an index of the remaining walkthrough portion of the course: -1. [Mapping a Schema](./13.md) +1. [Creating a Mapping](./13.md) - Material type: Conceptual - - Requirement(s): OHDF schema knowledge, security tool schema knowledge + - Requirement(s): OHDF schema knowledge, security tool schema/format knowledge 2. [Implementing a Mapper](./14.md) - Material type: Practical - Requirement(s): TypeScript, OHDF schema knowledge, OHDF Converters knowledge, file format (e.g., JSON, XML, CSV) knowledge diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index a3a5d8729..153c80913 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -1,7 +1,7 @@ --- order: 13 next: 14.md -title: Mapping a Schema +title: Creating a Mapping author: Charles Hu, Ryan Lin --- @@ -11,14 +11,14 @@ author: Charles Hu, Ryan Lin This walkthrough is targeted at converting security scans to OHDF. If your security tool provides exports that are not security scans or are APIs, contact the SAF team for further instruction on how to develop those services into an OHDF mapper. ::: -We begin the creation of every OHDF mapper by first planning out how we want correlate the fields in the OHDF and security tool's schemas. This mapping is important for the following reasons: +We begin the creation of every OHDF mapper by first planning out how we want correlate the fields in the OHDF and security tool's data format. This mapping is important for the following reasons: 1. It gives us a good framework for guiding how we actually implement the *-to-OHDF mapper. -2. It notifies us of potential knowledge gaps we may have of a security tool's schema. We need to close these gaps as best as we can in order to ensure that we can create schema field correlations that are as accurate/applicable as possible. -3. It gives us a chance to review our mapping of the schemas in a format that is still human readable. -4. It helps us reduce the amount of corrections and rewrites we have to perform on the actual mapper implementation due to schema mapping errors. +2. It notifies us of potential knowledge gaps we may have of a security tool's data format. We need to close these gaps as best as we can in order to ensure that we can create field correlations that are as accurate/applicable as possible. +3. It gives us a chance to review our mapping in a format that is still human readable. +4. It helps us reduce the amount of corrections and rewrites we have to perform on the actual mapper implementation due to potential mapping errors. -As we develop the mappings in the following examples, note that we will break down and analyze the schemas according to the OHDF schema structures we previously learned about (profiles, controls, and results). This is not necessarily the only or the best way to do this and you are encouraged to develop your own methods for correlating schemas that work best for you. +As we develop the mappings in the following examples, note that we will break down and analyze the fields according to the OHDF schema structures we previously learned about (profiles, controls, and results). This is not necessarily the only or the best way to do this and you are encouraged to develop your own methods for correlating fields that work best for you. ::: note Use of Exported Security Tool Data The following examples will use generated instances of exported security tool data that do not reflect the entirety of the schemas they are based on. Ideally, you will want to use the full schema when creating a mapping; however, the full schema is typically not readily available. To reflect this, we will be using generated export data and will fill in missing schema data when possible. @@ -63,7 +63,7 @@ Let's first start with our GoSec sample, which you should be already familiar wi ``` ::: -We can begin our mapping process by identifying the purpose of each field in the source data according to the [schema for GoSec](https://github.com/securego/gosec/blob/master/issue/issue.go). While we do this, it's also important that we try to tie back each identified purpose to the three general OHDF schema structures that we learned about earlier; that is, in addition to finding the purpose of each field, we should also ask ourselves the following: +We can begin our mapping process by identifying the purpose of each field in the source data. This is relatively simple in this case as we have a [formal schema for GoSec](https://github.com/securego/gosec/blob/master/issue/issue.go) that defines many of its fields. While we do this, it's also important that we try to tie back each identified purpose to the three general OHDF schema structures that we learned about earlier; that is, in addition to finding the purpose of each field, we should also ask ourselves the following: - Is this field recording meta data? - Is this field recording requirements? diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index b4ed4367a..31c15ddb3 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -279,7 +279,7 @@ This section is a demonstration on implementing an OHDF mapper for GoSec, assumi Here is our developed mapping for GoSec for reference: -::: details GoSec-to-OHDF Schema Mapping +::: details GoSec-to-OHDF Mapping ```typescript { platform: { // We fill in Heimdall for the platform as it handles the generation of this OHDF file @@ -490,7 +490,7 @@ export class GoSecMapper extends BaseConverter { ``` ::: -::: details Remaining GoSec-to-OHDF Schema Mapping +::: details Remaining GoSec-to-OHDF Mapping ```typescript { profiles: [ @@ -629,7 +629,7 @@ export class GoSecMapper extends BaseConverter { ``` ::: -::: details Remaining GoSec-to-OHDF Schema Mapping +::: details Remaining GoSec-to-OHDF Mapping ```typescript { profiles: [ @@ -764,7 +764,7 @@ export class GoSecMapper extends BaseConverter { ``` ::: -::: details Remaining GoSec-to-OHDF Schema Mapping +::: details Remaining GoSec-to-OHDF Mapping ```typescript { passthrough: { @@ -896,7 +896,7 @@ export class GoSecMapper extends BaseConverter { ``` ::: -::: details Remaining GoSec-to-OHDF Schema Mapping +::: details Remaining GoSec-to-OHDF Mapping ```typescript { passthrough: { @@ -1033,7 +1033,7 @@ This section is a demonstration for implementing an OHDF mapper that handles XML Here is our developed mapping for DbProtect for reference: -::: details DbProtect-to-OHDF Schema Mapping +::: details DbProtect-to-OHDF Mapping ```typescript { platform: { @@ -1283,7 +1283,7 @@ export class DBProtectMapper extends BaseConverter { ``` ::: -::: details Remaining DbProtect-to-OHDF Schema Mapping +::: details Remaining DbProtect-to-OHDF Mapping ```typescript { profiles: [ @@ -1434,7 +1434,7 @@ export class DBProtectMapper extends BaseConverter { ``` ::: -::: details Remaining DbProtect-to-OHDF Schema Mapping +::: details Remaining DbProtect-to-OHDF Mapping ```typescript { profiles: [ diff --git a/src/courses/mappers/img/saf_cli_features.png b/src/courses/mappers/img/saf_cli_features.png new file mode 100644 index 0000000000000000000000000000000000000000..91d4b9bc006ef3d9baf358d3a04bf3959dffc1b6 GIT binary patch literal 93978 zcmc$Fg;Sef&@L@jC@#gJxI47P3j}w!;_mJ)MT=9c5Zo#5?k>gJQrrp&5TLl<1b*M# zJ9GblFEb1zL*94Kp514kefGRj%8F9xsKlsnaB%1{(g0OBI0R)lxR=~^!xJoHrJU!6Q5*l(fM+JnWvK+z61(|!l3x;I zl;xM&S`A$YAs=tr9&JYL8uYg>c~Fq0$ItVoWyQuXyA}CD2#Mw&cal?QW8aV3aef&FtUAAtwb!Q>zJC9hKOO(G zF)h2`s6H@gwu1cEudaL3gWs;oN6?+gpC5+%92seqneF=rkdidHB_^Nw)7ec11 z<%tRO1}WTKXRmc3vUeL1?37f++DR*t;Is0z4m+ 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zIbenOsl*Xe|J3EpGQ_C)FM;U$-T9KTM_02+dJsxDy6Nh9Zz?mAu+xgeF!8xLWu;-K z7U04?N1kySy$EA@sE&_WUdadfg;OC8$2ku`dT0{Nq#CDjuh?{S0t6WZ}v7f+Um zyB8&QMB(SRA!HUu1}>RpCYL3!#pDA*j!%q2B+ZEVoH7zRYd&rqu`1iov6rNRcg@LY z!v_4DFIj;Rm@2yJaFTR+wJ-^nA(5M)H0%XS~bCZ{sV z%k*At4s%?E@>2*=?EXB+x{*rubwmZrx$soz{A!tNT;Nf(YM%LF$*(M;jZY(*K~KT9 zi;elc0#`|cRR>)@NjuaU`$!@D(-t(QJEP51$du0p*IwI`ixg92fR%>M@Rc!AG>O#d z)0jEs_OUKMPQ;jn1eZYzpYQd!)gSL+v~o@5*>}eszTZ?V#(11lljgWDTTIh?Nz-)e zK7pL*5WDgXglydy+w8m*c;VzXSD4m_J}OpS(-~3rnoX#6h_mYWxqwlTK{YE2fF)qzl0@86B~T>OR~eO2(Fy8U8*0^$DQp+|Eo<`)mJ2GQOJ|l5!`_DM zH*5a4fI_?GzM-0E*d642>;^xa@tm(9X;P{ZM~g{K{p=h$8=_5L7u7U?-`}{JBkjD- z4#2g~K=Eb%`qbp~@o1^9C6N`R0vj}JM6hcZtCYKpS!nLmRj@|phb)z^kk)=3iahCR zi723NG;0f`AIe)apXJnPDRc<2^l@SB>w0vU{mv_&w8$8fK-fdSmm8kTF&(9D3MKmZ ze$Qk|U-Zveq#Mspi-@;2D3XLe))IRfrM~wK%x*}!q zHL4la?Kf+xnXHsBALEe;QV6M9+MDsg%sqEo>@JtlVVMzu{o1GO$=ES{gw&+h@S&9d zt+7HK9)|?$q0C)>TcvyK(B%HlN7n>Sd1tX5PtLFb-c@xCeJU7-(x(d6aG|;nxBl6h zY Date: Tue, 25 Jun 2024 11:57:40 -0400 Subject: [PATCH 43/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 8 +++++--- src/courses/mappers/03.md | 6 +----- src/courses/mappers/04.md | 2 -- 3 files changed, 6 insertions(+), 10 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 9b0eba5c4..b8cf84171 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -52,16 +52,18 @@ The aforementioned terms are all security compliance related guidelines, framewo :::details NIST RMF, NIST 800-53, and CCI -- The National Institute of Standards and Technology Risk Management Framework (NIST RMF) is a general security compliance framework that integrates security, privacy, and risk management activities into the development life cycle. More information can be found [here](https://csrc.nist.gov/projects/risk-management/about-rmf). +- National Institute of Standards and Technology (NIST) is a U.S. agency that promotes U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve quality of life. More information can be found (here) [https://www.nist.gov/]. -- National Institute of Standards and Technology Special Publication 800-53 (**NIST SP 800-53**) is a compliance standard created by the U.S. government that contains a set of rules that every system must fulfill. More information can be found [here](https://secureframe.com/blog/nist-800-53-compliance). An example of a NIST control is as follows: +- The NIST Risk Management Framework (NIST RMF) provides a process that integrates security, privacy, and cyber supply chain risk management activities into the system development life cycle. More information can be found [here](https://csrc.nist.gov/projects/risk-management/about-rmf). + +- The NIST Special Publication 800-53 (**NIST SP 800-53**) provides a catalog of security and privacy controls for information systems and organizations to protect organizational operations and assets, individuals, other organizations, and the Nation from a diverse set of threats and risks. More information can be found [here](https://csrc.nist.gov/pubs/sp/800/53/r5/upd1/final). An example of a NIST control is as follows: ``` AC-12: Session Termination Automatically terminate a user session after [Assignment: organization-defined conditions, or trigger events requiring session disconnect]. ``` -- Control Correlation Identifiers (**CCIs**) are standard identifiers and descriptions that aim to correlate high-level policy expressions and low-level technical implementations of security requirements. More information can be found [here](https://public.cyber.mil/stigs/cci/). An example of a CCI is as follows: +- Control Correlation Identifiers (**CCIs**) are standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements. More information can be found [here](https://public.cyber.mil/stigs/cci/). An example of a CCI is as follows: ``` CCI-000002: Disseminate the organization-level; mission/business process-level; and/or system-level access control policy that addresses purpose, scope, roles, responsibilities, management commitment, coordination among organizational entities, and compliance to organization-defined personnel or roles. diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index e7d04176f..b00ac3118 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -13,7 +13,7 @@ OHDF is a cornerstone of the Security Automation Framework and is officially imp The Security Automation Framework (SAF) is a DevSecOps framework which provides a suite of tools for assessing, applying, and managing the security compliance of computer systems. SAF has five core capabilities, of which OHDF is involved in varying degrees: -- **Plan**: OHDF is defined such that it includes all information described in the guidance, as well as relavant meta data. Thus, the information provided by the guidance are incorporated with the security tool results. +- **Plan**: OHDF is defined such that it includes all information described in the guidance, as well as relevant metadata. Thus, the information provided by the guidance is incorporated with the security tool results. - **Harden**: OHDF is not typically used in this capability. @@ -48,7 +48,3 @@ An example of a typical use case of the SAF CLI is for security automation suppo [Heimdall](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. Data that is imported into Heimdall is automatically converted to OHDF through OHDF Converters, which serves as the underlying library that services data format conversion requests in Heimdall. ![An instance of Heimdall visualizing a security result set](./img/heimdall_view.png) - -## Knowledge Check - - diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 5cddf4a4d..e1b2d4e4a 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -51,8 +51,6 @@ With this, we can then develop a mapper which takes John's credentials from Soft ``` The important thing to note here is that mappers rely on underlying mappings which match semantically similar fields between two objects. These matches allow us to correctly convert each item in one object to the other. - -Also note that mappers make translating between two objects trivial, which means that anyone can do it and we can automate mappers to perform object conversions for us. ::: ## What Is an OHDF Mapper? From 115643262ea9ac359ccfbff47bdb56762fdcef59 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Tue, 25 Jun 2024 12:41:42 -0400 Subject: [PATCH 44/71] REview changes Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 42 +++++++++++++++++++++++++++++---------- src/courses/mappers/03.md | 2 +- src/courses/mappers/04.md | 4 ++-- 3 files changed, 35 insertions(+), 13 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index b8cf84171..690cd9d0b 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -46,25 +46,46 @@ OASIS Open is an international standards body that works on the development and - Uses mappers which provide and append relevant compliance standards to converted security tool data. -:::note What Are All These Abbreviations? +:::::::note What Are All These Abbreviations? The aforementioned terms are all security compliance related guidelines, frameworks, or implementations. The following are explanations on terms that are commonly used in this course: -:::details NIST RMF, NIST 800-53, and CCI +:::details NIST +The National Institute of Standards and Technology (NIST) is a U.S. agency that promotes U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve quality of life. -- National Institute of Standards and Technology (NIST) is a U.S. agency that promotes U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve quality of life. More information can be found (here) [https://www.nist.gov/]. +More information can be found (here) [https://www.nist.gov/]. +::: + +:::details NIST RMF +The NIST Risk Management Framework (NIST RMF) provides a process that integrates security, privacy, and cyber supply chain risk management activities into the system development life cycle. + +More information can be found [here](https://csrc.nist.gov/projects/risk-management/about-rmf). +::: + +:::::details NIST SP 800-53 +- The NIST Special Publication 800-53 (**NIST SP 800-53**) provides a catalog of security and privacy controls for information systems and organizations to protect organizational operations and assets, individuals, other organizations, and the Nation from a diverse set of threats and risks. -- The NIST Risk Management Framework (NIST RMF) provides a process that integrates security, privacy, and cyber supply chain risk management activities into the system development life cycle. More information can be found [here](https://csrc.nist.gov/projects/risk-management/about-rmf). +More information can be found [here](https://csrc.nist.gov/pubs/sp/800/53/r5/upd1/final). -- The NIST Special Publication 800-53 (**NIST SP 800-53**) provides a catalog of security and privacy controls for information systems and organizations to protect organizational operations and assets, individuals, other organizations, and the Nation from a diverse set of threats and risks. More information can be found [here](https://csrc.nist.gov/pubs/sp/800/53/r5/upd1/final). An example of a NIST control is as follows: -``` +:::details NIST SP 800-53 Example AC-12: Session Termination Automatically terminate a user session after [Assignment: organization-defined conditions, or trigger events requiring session disconnect]. -``` +::: +::::: + +:::details DISA +The Defense Information Systems Agency is a U.S. agency conducting DODIN (Department of Defense information networks) operations to enable lethality across all warfighting domains in defense of our nation. + +More information can be found [here](https://www.disa.mil/). +::: + +:::::details CCIs +Control Correlation Identifiers (**CCIs**) are standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements. They are analogous to NIST SP 800-53s in that they both provide security and privacy controls; however, CCIs also provide specific technical implementations for those controls as well. + +More information can be found [here](https://public.cyber.mil/stigs/cci/). -- Control Correlation Identifiers (**CCIs**) are standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements. More information can be found [here](https://public.cyber.mil/stigs/cci/). An example of a CCI is as follows: -``` +:::details CCI Example CCI-000002: Disseminate the organization-level; mission/business process-level; and/or system-level access control policy that addresses purpose, scope, roles, responsibilities, management commitment, coordination among organizational entities, and compliance to organization-defined personnel or roles. References: @@ -72,8 +93,9 @@ References: - NIST: NIST SP 800-53 Revision 4 (v4): AC-1 a 1 - NIST: NIST SP 800-53 Revision 5 (v5): AC-1 a 1 (a) - NIST: NIST SP 800-53A (v1): AC-1.1 (iii) -``` ::: +::::: +::::::: ## What Else? diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index b00ac3118..134e08cfc 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -19,7 +19,7 @@ The Security Automation Framework (SAF) is a DevSecOps framework which provides - **Validate**: InSpec's results format is a subset of the OHDF, meaning that InSpec is natively supported. Moreover, it's easy to write InSpec such that all the guidance information is passed through into both the OHDF profile and OHDF results formats. -- **Normalize**: Normalization is the primary use of OHDF. With the use of OHDF Converters, we are able to map many different security results formats to a standard format (OHDF). These converters can either be accessed directly or via the SAF CLI. +- **Normalize**: With the use of OHDF Converters, we are able to map many different security results formats to our standard format, OHDF. These converters can either be accessed directly or via the SAF CLI. - **Visualize**: OHDF is ingested by a variety of tools and transformed in many different ways. For example, a results file can be turned into a threshold file for pipeline use, turned into a POAM for ingestion by eMASS, or ingested by Heimdall directly for display purposes. diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index e1b2d4e4a..9a33e7d05 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -55,6 +55,6 @@ The important thing to note here is that mappers rely on underlying mappings whi ## What Is an OHDF Mapper? -An OHDF mapper is a mapper specifically focused on transforming security tool data formats to and from OHDF. It consists of a mapping and a number of helper functions which facilitate the actual application of the mapping. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to OHDF (\*-to-OHDF) and vice versa (OHDF-to-\*) using helper functions and utilities provided by the existing conversion infrastructure in OHDF Converters. +An OHDF mapper is a mapper specifically focused on transforming security data to and from OHDF. It consists of a mapping and a number of helper functions which facilitate the actual application of the mapping. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to OHDF (\*-to-OHDF) and vice versa (OHDF-to-\*) using helper functions and utilities provided by the existing conversion infrastructure in OHDF Converters. -OHDF mappers are built upon an understanding of the security tool data format (whether through formal schemas or on-hand export examples) and the OHDF schema, and the mechanics of the mappers revolve around correlating the fields in each as accurately as possible. +OHDF mappers are built upon an understanding of the security data format (whether through formal schemas or on-hand export examples) and the OHDF schema, and the mechanics of the mappers revolve around correlating the fields in each as accurately as possible. From c087c9cabaa25066197ef55efa2e6892f773ec99 Mon Sep 17 00:00:00 2001 From: Ryan Lin Date: Tue, 25 Jun 2024 09:55:06 -0700 Subject: [PATCH 45/71] Wording changes to what is a mapper Signed-off-by: Ryan Lin --- src/courses/mappers/04.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 9a33e7d05..0f0f3b689 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -7,7 +7,7 @@ author: Charles Hu ## What Is a Mapper? -A mapper is an instance of an adapter design pattern which is used to correlate (or map) items in two different objects with one another. Mappers are useful in that they allow us to correlate values in objects that are nominally different but semantically the same. A result of this is that we can easily transform one object type into another through the use of mappings which define the direct relationship of values in each object type. An important aspect of the transformation process is that while the objects containing the values are transformed, the values themselves typically remain the same. +A mapper is an example of the Adapter Design Pattern which is used to correlate (or map) items in two different objects with one another. Mappers are useful in that they allow us to correlate values in objects that are nominally different but semantically the same. A result of this is that we can easily transform one object type into another through the use of mappings which define the direct relationship of values in each object type. An important aspect of the transformation process is that while the objects containing the values are transformed, the values themselves typically remain the same. Mappings are the actual correlation of values between two different objects. They are the basis for mappers and are responsible for defining which values between two objects are semantically the same. Mappers are the implementation of mappings which perform the necessary processing to transform the objects according to relationships found in the mappings. In order to have a mapper that is as accurate as possible in its transformations, the mappings should ideally include correlations for all values in the objects. 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zg@sG3u$TO>s?}L=fx@r9|9{tC(zpMWv7l^y%$_Ox{^svjZv5h~CBze37J_?jfi%#H z-GPDg@U{UCoM5s0vAo{v{huH1E8i=d?vBu(e){G2y8rx_UQgFA*9@J8S9=4;7j@v+ zbG@Aw{zM?rbin_9z5U<2_y3(0(A^gP_wD_kbHB{q|Ml%#)>DF5YY@0#qaCnte8=qW zia)HHg%g&%*k1qT`faH>cC}V}KOU2Q2^oMscM5ni<80vOsqQbpdk2(a_g0lg&%Xcv z-Tv?=FLFbsz*i%}LLJ4P3;hl+yW?YX<*aIU#LG^_QnMz`*N z@9lp)?&E59>3WyZFgb7H;-~xdf-ddEo0J^%nbdmzy{-Rl{nC8@-?wq4Q}nS9H^HOF zmh;b-zuzz42PUR1r~K#J&E5C^@B8iN+AV(^l>e^~ySHrXRhNIS#kgcK!xUNMjl+Zg Y% Date: Tue, 25 Jun 2024 14:24:02 -0400 Subject: [PATCH 47/71] Markdown table addition Signed-off-by: Charles Hu --- src/courses/mappers/13.md | 130 +++++++++++++++++--------------------- 1 file changed, 59 insertions(+), 71 deletions(-) diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index 153c80913..4b65d7fa2 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -236,13 +236,12 @@ Let's first start with an empty OHDF schema as follows: We can begin our schema correlation by directly porting over fields from the GoSec source data that are obvious: `GosecVersion`, `Issues.rule_id`, `Issues.details`, and `Issues.cwe`. Try to map these fields youself as you follow along and refer to our solution to check your work. ::: details Correlated Fields -- `profiles.version` <-> `GosecVersion` - -- `profiles.controls.id` <-> `Issues.rule_id` - -- `profiles.controls.title` <-> `Issues.details` - -- `profiles.controls.tags` <-> `Issues.cwe` +OHDF | Source Data +-|- +`profiles.version` | `GosecVersion` +`profiles.controls.id` | `Issues.rule_id` +`profiles.controls.title` | `Issues.details` +`profiles.controls.tags` | `Issues.cwe` ::: ::: details OHDF Schema Mapping Ver. 1 @@ -374,7 +373,9 @@ We can begin our schema correlation by directly porting over fields from the GoS Next, let's look at `Issues.code`, which can be a little bit tricky. ::: details Correlated Fields -- `profiles.controls.results.code_desc` <-> `Issues.code` +OHDF | Source Data +-|- +`profiles.controls.results.code_desc` | `Issues.code` ::: ::: details OHDF Schema Mapping Ver. 2 @@ -496,14 +497,13 @@ Next, let's look at `Issues.code`, which can be a little bit tricky. Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.nosec`, and `Issues.suppressions`. -::: details Correlated Fields -- `profiles.controls.tags` <-> `Issues.severity` - -- `profiles.controls.tags` <-> `Issues.confidence` - -- `profiles.controls.tags` <-> `Issues.nosec` - -- `profiles.controls.tags` <-> `Issues.suppressions` +::: details Correlated +OHDF | Source Data +-|- +`profiles.controls.tags` | `Issues.severity` +`profiles.controls.tags` | `Issues.confidence` +`profiles.controls.tags` | `Issues.nosec` +`profiles.controls.tags` | `Issues.suppressions` ::: ::: details OHDF Schema Mapping Ver. 3 @@ -620,11 +620,11 @@ It may be tempting to map `Issues.severity` to `impact`; however, it is importan Next, let's look at the fields `Issues.file`, `Issues.line`, and `Issues.column`. ::: details Correlated Fields -- `profiles.controls.results.message` <-> `Issues.file` - -- `profiles.controls.results.message` <-> `Issues.line` - -- `profiles.controls.results.message` <-> `Issues.column` +OHDF | Source Data +-|- +`profiles.controls.results.message` | `Issues.file` +`profiles.controls.results.message` | `Issues.line` +`profiles.controls.results.message` | `Issues.column` ::: ::: details OHDF Schema Mapping Ver. 4 @@ -728,9 +728,10 @@ This is a situation similar to the one `Issues.code` is in. `Issues.file`, `Issu Next, let's look at the fields `Golang errors` and `Stats`. ::: details Correlated Fields -- `passthrough.auxiliary_data` <-> `Golang errors` - -- `passthrough.auxiliary_data` <-> `Stats` +OHDF | Source Data +-|- +`passthrough.auxiliary_data` | `Golang errors` +`passthrough.auxiliary_data` | `Stats` ::: ::: details OHDF Schema Mapping Ver. 5 @@ -818,21 +819,16 @@ For these fields, we can place them in `passthrough` as there are no reasonably Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. ::: details Correlated Fields -- `platform.name` <-> `'Heimdall Tools'` - -- `platform.release` <-> `HeimdallToolsVersion` - -- `version` <-> `HeimdallToolsVersion` - -- `profiles.name` <-> `'Gosec scanner'` - -- `profiles.title` <-> `'gosec'` - -- `profiles.controls.impact` <-> `0.5` - -- `profiles.controls.results.status` <-> `'Failure'` - -- `profiles.status` <-> `'loaded'` +OHDF | Source Data +-|- +`platform.name` | `'Heimdall Tools'` +`platform.release` | `HeimdallToolsVersion` +`version` | `HeimdallToolsVersion` +`profiles.name` | `'Gosec scanner'` +`profiles.title` | `'gosec'` +`profiles.controls.impact` | `0.5` +`profiles.controls.results.status` | `'Failure'` +`profiles.status` | `'loaded'` ::: ::: details OHDF Schema Mapping Ver. 6 @@ -1160,11 +1156,11 @@ We can begin our schema correlation by directly porting over fields from the DbP As in the previous example, note that these mapping are informal and do not need to adhere to any programming syntax. Proper implementation of these mappings will be done later in the course. ::: details Correlated Fields -- `profiles.controls.id` <-> `Check ID` - -- `profiles.controls.results.status` <-> `Result Status` - -- `profiles.controls.results.start_time` <-> `Date` +OHDF | Source Data +-|- +`profiles.controls.id` | `Check ID` +`profiles.controls.results.status` | `Result Status` +`profiles.controls.results.start_time` | `Date` ::: ::: details OHDF Schema Mapping Ver. 1 @@ -1300,13 +1296,12 @@ As in the previous example, note that these mapping are informal and do not need Now let us handle some of the more detailed information about the specific controls, namely `Task`, `Check Category`, `Risk DV`, `Check`, and `Details`. ::: details Correlated Fields -- `profiles.controls.desc` <-> `Task`, `Check Category` - -- `profiles.controls.impact` <-> `Risk DV` - -- `profiles.controls.title` <-> `Check` - -- `profiles.controls.results.code_desc` <-> `Details` +OHDF | Source Data +-|- +`profiles.controls.desc` | `Task`, `Check Category` +`profiles.controls.impact` | `Risk DV` +`profiles.controls.title` | `Check` +`profiles.controls.results.code_desc` | `Details` ::: ::: details OHDF Schema Mapping Ver. 2 @@ -1429,10 +1424,11 @@ Finally, for the details, recall that the `code_desc` is looking for the test ex Finally, we are left with the more general, report-level information from our DbProtect sample file: `Organization`, `Asset Type`, `Check Asset`, `IP Address, Port, Instance`, `Job Name`, `Policy`. Notice that OHDF does not have fields that correspond to some of this additional info, so consider ways to condense this data and encode it into other fields. ::: details Correlated Fields -- `profiles.summary` <-> `Organization`, `Asset`, `Asset Type`, `IP Address, Port, Instance` -- `profiles.title` <-> `Job Name` - -- `profiles.name` <-> `Policy` +OHDF | Source Data +-|- +`profiles.summary` | `Organization`, `Asset`, `Asset Type`, `IP Address, Port, Instance` +`profiles.title` | `Job Name` +`profiles.name` | `Policy` ::: ::: details OHDF Schema Mapping Ver. 3 @@ -1503,11 +1499,6 @@ Finally, we are left with the more general, report-level information from our Db ::: ::: details Reasoning -- `profiles.summary` <-> `Organization`, `Asset`, `Asset Type`, `IP Address, Port, Instance` -- `profiles.title` <-> `Job Name` - -- `profiles.name` <-> `Policy` - As mentioned previously, OHDF does not have a specific place to put information like the `Organization`, `Asset`, or `Asset Type`. However, we do have a summary field for profiles. Recall our goal of preserving as much data as possible from the source. With this in mind, it would be reasonable to map all these fields to the summary for the sake of preservation. The profile name and title fields are a little tricky. Note that the `Policy` field refers to the baseline guidance that the scan tested against. This aligns more with the profile name than the `Job Name`, which is just the a name the customer added for the report. Thus, we map the `Policy` field to the `profiles.name` and the `Job Name` field to the `profiles.title` instead. @@ -1518,17 +1509,14 @@ The profile name and title fields are a little tricky. Note that the `Policy` fi Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. ::: details Correlated Fields -- `platform.name` <-> `'Heimdall Tools'` - -- `platform.release` <-> `HeimdallToolsVersion` - -- `version` <-> `HeimdallToolsVersion` - -- `profiles.controls.tags.nist` <-> `DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS` - -- `profiles.controls.tags.cci` <-> `DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS` - -- `profiles.status` <-> `'loaded'` +OHDF | Source Data +-|- +`platform.name` | `'Heimdall Tools'` +`platform.release` | `HeimdallToolsVersion` +`version` | `HeimdallToolsVersion` +`profiles.controls.tags.nist` | `DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS` +`profiles.controls.tags.cci` | `DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS` +`profiles.status` | `'loaded'` ::: ::: details OHDF Schema Mapping Ver. 4 From 023991f41760ed5d0c11f57aa6c9152162c316a2 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Tue, 25 Jun 2024 16:00:13 -0400 Subject: [PATCH 48/71] Knowledge check Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 18 ++++++++++++++++++ src/courses/mappers/03.md | 2 +- src/courses/mappers/04.md | 10 ++++++++++ src/courses/mappers/06.md | 20 ++++++++++++++++++++ src/courses/mappers/08.md | 2 ++ 5 files changed, 51 insertions(+), 1 deletion(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index afffff516..914acf09d 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -106,3 +106,21 @@ References: ## What Else? You can read more about OHDF [here](https://saf.mitre.org/framework/normalize). + +## Knowledge Check + +:::details What is OHDF? +OHDF is a security data format used to normalize generated data exports from various security tools into a single common data format usable by the SAF tool suite. +::: + +:::details What are some uses of OHDF? +Some uses include: + +- Aggregating security data formats into a single standard format. + +- Facilitating the transformation/transport of data across different processes and technologies. + +- Enhancing security data with relevant compliance standards. + +- And more. +::: diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index 134e08cfc..e77e1d451 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -33,7 +33,7 @@ You can read more about SAF [here](../user/03.md). ## What Is OHDF Converters? -[OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) is a custom data normalization library which leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated in tools such as [Heimdall](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification for systems such as automated build pipelines. +[OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) is a custom data normalization library which hosts and leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated in tools such as [Heimdall](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification for systems such as automated build pipelines. ## What Is the SAF CLI? diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 0f0f3b689..1fdc2ffd1 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -58,3 +58,13 @@ The important thing to note here is that mappers rely on underlying mappings whi An OHDF mapper is a mapper specifically focused on transforming security data to and from OHDF. It consists of a mapping and a number of helper functions which facilitate the actual application of the mapping. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to OHDF (\*-to-OHDF) and vice versa (OHDF-to-\*) using helper functions and utilities provided by the existing conversion infrastructure in OHDF Converters. OHDF mappers are built upon an understanding of the security data format (whether through formal schemas or on-hand export examples) and the OHDF schema, and the mechanics of the mappers revolve around correlating the fields in each as accurately as possible. + +## Knowledge Check + +:::details Where are OHDF mappers located? +OHDF mappers are located in OHDF Converters, which hosts and leverages the mappers to provide mapping services to and from OHDF. +::: + +::: details What is the difference between a mapping and a mapper? +A mapping shows the correlation between fields, while a mapper actually implements the transformation of correlated fields. +::: \ No newline at end of file diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index 9e42a3f83..f6da4deed 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -287,3 +287,23 @@ Here's an example of the additional structures from a converted Twistlock data f } ``` ::: + +## Knowledge Check + +:::details What is the purpose of Profiles, Controls, and Results? +- Profiles provides a high-level overview of the security tool result and the targeted system (i.e., metadata). + +- Controls provides information on the security requirements being applied to the target system. + +- Results provides information on the actual checks to ensure that the target system is compliant with the security requirements. +::: + +:::details What is the relationship between Profiles, Controls, and Results? +- Any given profile contains some number of controls which were tested against the target system during the original security tool run. + +- Any given control contains some number of results which reflect the implemented tests to check if the target system is actually compliant. +::: + +:::details What is `passthrough`? +`passthrough` is used to store extraneous information from the source data that has no equivalent in the OHDF schema. It is also used to store the entire raw source data in the `raw` subfield. +::: diff --git a/src/courses/mappers/08.md b/src/courses/mappers/08.md index 5dd1a2d31..d5efb94b5 100644 --- a/src/courses/mappers/08.md +++ b/src/courses/mappers/08.md @@ -11,6 +11,8 @@ Now that you've familiarized yourself with the formal OHDF schema, let's revisit Here are some key questions to keep note of while reading through these examples: +- How is the source data structured/organized (e.g., by requirement, by target system, by finding)? +- How is the OHDF file structured? - How is the structure of the source data interpreted to fit the OHDF hierarchy? - What groups of fields in the source data correlate to our profiles, controls, and results structures? - Which fields in the source data are used to fill each OHDF field? Is that mapping accurate? From c9b3609444a9f85daf50c3398afde73ec6d5b670 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Tue, 25 Jun 2024 16:15:18 -0400 Subject: [PATCH 49/71] Spelling Signed-off-by: Charles Hu --- src/courses/mappers/13.md | 40 +++++++++++++++++++-------------------- src/courses/mappers/14.md | 8 ++++---- 2 files changed, 24 insertions(+), 24 deletions(-) diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index 4b65d7fa2..19590fd43 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -65,14 +65,14 @@ Let's first start with our GoSec sample, which you should be already familiar wi We can begin our mapping process by identifying the purpose of each field in the source data. This is relatively simple in this case as we have a [formal schema for GoSec](https://github.com/securego/gosec/blob/master/issue/issue.go) that defines many of its fields. While we do this, it's also important that we try to tie back each identified purpose to the three general OHDF schema structures that we learned about earlier; that is, in addition to finding the purpose of each field, we should also ask ourselves the following: -- Is this field recording meta data? +- Is this field recording metadata? - Is this field recording requirements? - Is this field recording requirement testing? To summarize, we should be asking ourselves the following two questions for each field in the source data: - What is the purpose of this field? -- What is this field recording (meta data, requirements, requirement testing)? +- What is this field recording (metadata, requirements, requirement testing)? Let's apply this to our GoSec source data. Try to find the answers to these two questions for each field yourself and then refer back to our annotated solution to check your work. @@ -80,7 +80,7 @@ Let's apply this to our GoSec source data. Try to find the answers to these two ```json { // Purpose: Go compilation errors - // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical "Golang errors": {}, // Purpose: Container for identified security issues // Recording: Requirements - This entity records all identified security issues in a Go source code @@ -125,7 +125,7 @@ Let's apply this to our GoSec source data. Try to find the answers to these two } ], // Purpose: The statistics of the GoSec scan on the source code - // Recording: Meta data - Info on the scan itself + // Recording: Metadata - Info on the scan itself "Stats": { "files": 199, "lines": 12401, @@ -133,7 +133,7 @@ Let's apply this to our GoSec source data. Try to find the answers to these two "found": 7 }, // Purpose: The version of the GoSec instance currently running - // Recording: Meta data - Info on the scan itself + // Recording: Metadata - Info on the scan itself "GosecVersion": "dev" } ``` @@ -314,7 +314,7 @@ OHDF | Source Data ```json { // Purpose: Go compilation errors - // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical "Golang errors": {}, // Purpose: Container for identified security issues // Recording: Requirements - This entity records all identified security issues in a Go source code @@ -347,7 +347,7 @@ OHDF | Source Data } ], // Purpose: The statistics of the GoSec scan on the source code - // Recording: Meta data - Info on the scan itself + // Recording: Metadata - Info on the scan itself "Stats": { "files": 199, "lines": 12401, @@ -359,13 +359,13 @@ OHDF | Source Data ::: ::: details Reasoning -- `version: GosecVersion`: We want to specifically place this in `version` in `profiles` because this is meta data on the actual security tool that generated these results. This is different from `version` on the top level since that refers to the platform, or the tool creating the actual OHDF file itself. +- `version: GosecVersion`: We want to specifically place this in `version` in `profiles` because this is metadata on the actual security tool that generated these results. This is different from `version` on the top level since that refers to the platform, or the tool creating the actual OHDF file itself. - `id: Issues.rule_id`: `rule_id` gives us an ID used by GoSec to identify each failing requirement in the source code. - `title: Issues.details`: The source data doesn't provide a proper title that goes along with the failing requirement. In lieu of this, we can use `Issues.details` which does give us a human readable description of the requirement and repurpose it as a title for our control. -- `tags: {Issues.cwe}`: `Issues.cwe` provides an association of our GoSec security issue with a known vulnerability database. This can be used in `tags` to act as meta data which can used to filter or organize controls created from these GoSec security issues. +- `tags: {Issues.cwe}`: `Issues.cwe` provides an association of our GoSec security issue with a known vulnerability database. This can be used in `tags` to act as metadata which can used to filter or organize controls created from these GoSec security issues. ::: #### Mapping Version 2 @@ -448,7 +448,7 @@ OHDF | Source Data ```json { // Purpose: Go compilation errors - // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical "Golang errors": {}, // Purpose: Container for identified security issues // Recording: Requirements - This entity records all identified security issues in a Go source code @@ -478,7 +478,7 @@ OHDF | Source Data } ], // Purpose: The statistics of the GoSec scan on the source code - // Recording: Meta data - Info on the scan itself + // Recording: Metadata - Info on the scan itself "Stats": { "files": 199, "lines": 12401, @@ -580,7 +580,7 @@ OHDF | Source Data ```json { // Purpose: Go compilation errors - // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical "Golang errors": {}, // Purpose: Container for identified security issues // Recording: Requirements - This entity records all identified security issues in a Go source code @@ -598,7 +598,7 @@ OHDF | Source Data } ], // Purpose: The statistics of the GoSec scan on the source code - // Recording: Meta data - Info on the scan itself + // Recording: Metadata - Info on the scan itself "Stats": { "files": 199, "lines": 12401, @@ -705,10 +705,10 @@ OHDF | Source Data ```json { // Purpose: Go compilation errors - // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical "Golang errors": {}, // Purpose: The statistics of the GoSec scan on the source code - // Recording: Meta data - Info on the scan itself + // Recording: Metadata - Info on the scan itself "Stats": { "files": 199, "lines": 12401, @@ -991,14 +991,14 @@ You may notice that the metadata field maps corresponding keys to each of the va Unlike with GoSec, DbProtect does not have a published schema. Thus, we must empirically reason the mapping based on our sample data. Thus, even more so than the previous example, this process is subjective and your mapping may vary from ours. One thing we can use to inform ourselves about the purpose of each field in place of a schema, however, is the metadata fields at the top of the sample. Recall the three questions we ask ourselves to tie back identified purposes to the three general OHDF schema structures: -- Is this field recording meta data? +- Is this field recording metadata? - Is this field recording requirements? - Is this field recording requirement testing? Also recall that, for each field in the source data, we should be asking ourselves the following two questions: - What is the purpose of this field? -- What is this field recording (meta data, requirements, requirement testing)? +- What is this field recording (metadata, requirements, requirement testing)? Let us now apply this philosophy to our DbProtect source data. Try to find the answers to these two questions for each field yourself and then refer back to our annotated solution to check your work. @@ -1007,7 +1007,7 @@ Let us now apply this philosophy to our DbProtect source data. Try to find the a - + @@ -1236,7 +1236,7 @@ OHDF | Source Data - + ... @@ -1377,7 +1377,7 @@ OHDF | Source Data - + ... diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index 31c15ddb3..20660db3d 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -346,7 +346,7 @@ Here is our developed mapping for GoSec for reference: ```json { // Purpose: Go compilation errors - // Recording: Meta data - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical "Golang errors": {}, // Purpose: Container for identified security issues // Recording: Requirements - This entity records all identified security issues in a Go source code @@ -391,7 +391,7 @@ Here is our developed mapping for GoSec for reference: } ], // Purpose: The statistics of the GoSec scan on the source code - // Recording: Meta data - Info on the scan itself + // Recording: Metadata - Info on the scan itself "Stats": { "files": 199, "lines": 12401, @@ -399,7 +399,7 @@ Here is our developed mapping for GoSec for reference: "found": 7 }, // Purpose: The version of the GoSec instance currently running - // Recording: Meta data - Info on the scan itself + // Recording: Metadata - Info on the scan itself "GosecVersion": "dev" } ``` @@ -1105,7 +1105,7 @@ Here is our developed mapping for DbProtect for reference: - + From d43abe2aa8607e9b5188ee5a0cebfaedd866e885 Mon Sep 17 00:00:00 2001 From: Charles Hu <106095667+charleshu-8@users.noreply.github.com> Date: Wed, 26 Jun 2024 09:25:53 -0400 Subject: [PATCH 50/71] Review change Co-authored-by: Amndeep Singh Mann Signed-off-by: Charles Hu <106095667+charleshu-8@users.noreply.github.com> --- src/courses/mappers/03.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index e77e1d451..0a2bd5639 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -39,7 +39,7 @@ You can read more about SAF [here](../user/03.md). The Security Automation Framework Command Line Interface (SAF CLI) brings together applications, techniques, libraries, and tools developed by MITRE and the security community to streamline security automation for systems and DevOps pipelines. -An example of a typical use case of the SAF CLI is for security automation support for CI/CD. This process utilizes the `saf convert` command, which allows for the conversion of data between OHDF and several supported security tool data formats. The SAF CLI is set up to automatically ingest security reports generated from the build pipeline and can forward the newly generated OHDF files to a visualizer such as Heimdall which allows a security assessor to review the state of the current software build. +An example use case of the SAF CLI is for automating certain security processes in a CI/CD pipeline. One process would be normalizing security data into OHDF using the `saf convert` command. One can set up the SAF CLI to automatically ingest security reports generated from the build pipeline, and then forward the newly generated OHDF files to a visualization tool such as Heimdall that allows a security assessor to review the state of the current software build. ![SAF CLI Utility Overview](./img/saf_cli_features.png) From ea5fcb7cff947b1c06320c521e18819a80ebfd0b Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 26 Jun 2024 09:27:26 -0400 Subject: [PATCH 51/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 914acf09d..ff21e9244 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -9,7 +9,7 @@ author: Charles Hu OASIS Heimdall Data Format (OHDF) is a security data format used to normalize generated data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security validation profiles, controls, and results. -OASIS Open is an international standards body that works on the development and advancement of open source technological standards. OHDF is currently in the process of becoming an OASIS Open standard. For more information on the OHDF charter for OASIS Open, [refer here](https://groups.oasis-open.org/communities/tc-community-home2?CommunityKey=f8888caa-8401-46f8-bf10-018dc7d3f577). +[OASIS Open](https://www.oasis-open.org/) is an international standards body that works on the development and advancement of open source technological standards. OHDF is currently in the process of becoming an OASIS Open standard. For more information on the OHDF charter for OASIS Open, [refer here](https://groups.oasis-open.org/communities/tc-community-home2?CommunityKey=f8888caa-8401-46f8-bf10-018dc7d3f577). ## Why OHDF? @@ -57,23 +57,23 @@ See below for an example of how *some* fields in a source file are mapped to OHD The aforementioned terms are all security compliance related guidelines, frameworks, or implementations. The following are explanations on terms that are commonly used in this course: :::details NIST -The National Institute of Standards and Technology (NIST) is a U.S. agency that promotes U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve quality of life. +The National Institute of Standards and Technology (NIST) is a U.S. agency that "promotes U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve quality of life." -More information can be found (here) [https://www.nist.gov/]. +More information can be found [here](https://www.nist.gov/). ::: :::details NIST RMF -The NIST Risk Management Framework (NIST RMF) provides a process that integrates security, privacy, and cyber supply chain risk management activities into the system development life cycle. +The NIST Risk Management Framework (NIST RMF) provides "a process that integrates security, privacy, and cyber supply chain risk management activities into the system development life cycle." More information can be found [here](https://csrc.nist.gov/projects/risk-management/about-rmf). ::: :::::details NIST SP 800-53 -- The NIST Special Publication 800-53 (**NIST SP 800-53**) provides a catalog of security and privacy controls for information systems and organizations to protect organizational operations and assets, individuals, other organizations, and the Nation from a diverse set of threats and risks. +- The NIST Special Publication 800-53 (**NIST SP 800-53**) "provides a catalog of security and privacy controls for information systems and organizations to protect organizational operations and assets, individuals, other organizations, and the Nation from a diverse set of threats and risks." More information can be found [here](https://csrc.nist.gov/pubs/sp/800/53/r5/upd1/final). -:::details NIST SP 800-53 Example +:::details NIST SP 800-53 Excerpt AC-12: Session Termination Automatically terminate a user session after [Assignment: organization-defined conditions, or trigger events requiring session disconnect]. @@ -81,17 +81,17 @@ Automatically terminate a user session after [Assignment: organization-defined c ::::: :::details DISA -The Defense Information Systems Agency is a U.S. agency conducting DODIN (Department of Defense information networks) operations to enable lethality across all warfighting domains in defense of our nation. +The Defense Information Systems Agency (DISA) is a U.S. agency conducting "DODIN (Department of Defense information networks) operations to enable lethality across all warfighting domains in defense of our nation." More information can be found [here](https://www.disa.mil/). ::: :::::details CCIs -Control Correlation Identifiers (**CCIs**) are standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements. They are analogous to NIST SP 800-53s in that they both provide security and privacy controls; however, CCIs also provide specific technical implementations for those controls as well. +Control Correlation Identifiers (**CCIs**) are "standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements." They are analogous to NIST SP 800-53s in that they both provide security and privacy controls; however, CCIs also provide specific technical implementations for those controls as well. More information can be found [here](https://public.cyber.mil/stigs/cci/). -:::details CCI Example +:::details CCI Excerpt CCI-000002: Disseminate the organization-level; mission/business process-level; and/or system-level access control policy that addresses purpose, scope, roles, responsibilities, management commitment, coordination among organizational entities, and compliance to organization-defined personnel or roles. References: From 475109687bf1cb8d70efb29625b5a7c2adab3af9 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 26 Jun 2024 10:22:11 -0400 Subject: [PATCH 52/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 10 ++++++---- src/courses/mappers/03.md | 12 +++++++++++- 2 files changed, 17 insertions(+), 5 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index ff21e9244..cc9aeb1fa 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -74,9 +74,11 @@ More information can be found [here](https://csrc.nist.gov/projects/risk-managem More information can be found [here](https://csrc.nist.gov/pubs/sp/800/53/r5/upd1/final). :::details NIST SP 800-53 Excerpt -AC-12: Session Termination - -Automatically terminate a user session after [Assignment: organization-defined conditions, or trigger events requiring session disconnect]. +AC-17 REMOTE ACCESS +Control: +a. Establish and document usage restrictions, configuration/connection requirements, and +implementation guidance for each type of remote access allowed; and +b. Authorize each type of remote access to the system prior to allowing such connections. ::: ::::: @@ -87,7 +89,7 @@ More information can be found [here](https://www.disa.mil/). ::: :::::details CCIs -Control Correlation Identifiers (**CCIs**) are "standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements." They are analogous to NIST SP 800-53s in that they both provide security and privacy controls; however, CCIs also provide specific technical implementations for those controls as well. +Control Correlation Identifiers (**CCIs**) are "standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements." They are analogous to NIST SP 800-53s in that they both provide security and privacy controls. More information can be found [here](https://public.cyber.mil/stigs/cci/). diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index 0a2bd5639..0e245fa97 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -11,7 +11,17 @@ OHDF is a cornerstone of the Security Automation Framework and is officially imp ## What Is the Security Automation Framework? -The Security Automation Framework (SAF) is a DevSecOps framework which provides a suite of tools for assessing, applying, and managing the security compliance of computer systems. SAF has five core capabilities, of which OHDF is involved in varying degrees: +The Security Automation Framework (SAF) is a suite of open-source security automation tools that facilitate the development, collection, and standardization of content for use by government and industry organizations to​: + +- Accelerate ATO. + +- Establish security requirements. + +- Build security in. + +- Assess/monitor vulnerabilities. + +SAF has five core capabilities, of which OHDF is involved in varying degrees: - **Plan**: OHDF is defined such that it includes all information described in the guidance, as well as relevant metadata. Thus, the information provided by the guidance is incorporated with the security tool results. From 23a9ccb98ed27f8455373020770aba7449462646 Mon Sep 17 00:00:00 2001 From: Ryan Lin Date: Wed, 26 Jun 2024 11:13:07 -0700 Subject: [PATCH 53/71] Changes to overview section Signed-off-by: Ryan Lin --- src/courses/mappers/09.md | 44 ++++++++++++++++++++++++++++++++------- src/courses/mappers/10.md | 2 +- 2 files changed, 37 insertions(+), 9 deletions(-) diff --git a/src/courses/mappers/09.md b/src/courses/mappers/09.md index 958bc0cbb..2a2549dbe 100644 --- a/src/courses/mappers/09.md +++ b/src/courses/mappers/09.md @@ -19,7 +19,7 @@ OHDF Converters is the library that hosts and provides OHDF mappers to other app base-converter is an underlying class which enables \*-to-HDF mapping in OHDF Converters. It defines \*-to-HDF mappers and provides critical tools in the form of keywords which allow for the construction of such mappers. All \*-to-HDF mappers inherit from this class and therefore have access to the keywords that this class provides. You should aim to utilize these keywords to their fullest potential to ease and simplify mapper development. The provided tools are as follows: -- `path`: Define JSON object path to go to. Paths are found recursively. +- `path`: Define JSON object path to go to. Paths are found recursively (for example, if a top-level field has the path `result`, then all fields below it will only see the `result` field of the source file). To escape this recursion, we can make use of the `$` symbol at the beginning of the path. - Use: ```typescript path: PATH_AS_STRING @@ -29,8 +29,26 @@ OHDF Converters is the library that hosts and provides OHDF mappers to other app // Attribute 'id' will be set as whatever JSON object attribute 'vulnerability.id' is id: {path: 'vulnerability.id'} ``` + - Example of recursion: + ```typescript + controls: [ + { + path: 'result', + id: {path: 'id'} // This is grabbing from the path 'result.id', not just 'id' + } + ] + ``` + - Example of escaping from recursion: + ```typescript + controls: [ + { + path: 'result', + id: {path: '$id'} // This is grabbing from the top-level path 'id' + } + ] + ``` -- `transformer`: Execute given code sequence; operates similar to an anonymous function. +- `transformer`: Sometimes, source data is not formatted in the way we desire. To remedy this, we can make use of the `base-converter` `transformer` functionality. The `transformer` accepts a function as a parameter. This can either be an anonymous funciton or a normal, named function. This transformer acts as a callback function that will go to the specified path location and modify the data accordingly. See the following example, where we apply a transformer that maps nist tags to CCI tags. - Use: ```typescript transformer: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} @@ -44,16 +62,26 @@ OHDF Converters is the library that hosts and provides OHDF mappers to other app } ``` -- `arrayTransformer`: Execute given code sequence on a given array; primarily used when in an attribute that is an array of objects. +- `arrayTransformer`: The `arrayTransformer` works similarly to the `transformer` in that it takes our in-progress mapping for the array structure, accepts a function that returns an array, and transforms the array accordingly (whether it be filtering out some items, passing in some additional data, or otherwise). + + + +Again, explain your example more clearly and provide more text and code context. What is happening in your example is that the arraytransformer func was used in the controls array. we created a control per every item in the source file's site.alerts array, but that array contains duplicate items. because our controls array requires the id for each control to be unique (building off of prior explained knowledge of the hdf schema), we need to de-duplicate them by consolidating any controls that have the same id. we then return the array of controls which now will contain fewer items. - Use: ```typescript - arrayTransformer: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} + arrayTransformer: (PARAMETER: TYPE[]): OUTPUT_TYPE[] => {CODE_TO_EXECUTE} ``` - Example: ```typescript - // The function 'deduplicateId' will run against all items in the current array that the 'arrayTransformer' was called inside - arrayTransformer: deduplicateId + controls: [ + { + path: '...', // Some path to the array in the source file + // The function 'deduplicateId' will run against all items in the current array that the 'arrayTransformer' was called inside + arrayTransformer: deduplicateId + } + ] ``` +In the above code block, the `arrayTransformer` is used in the controls array of the mapping, which creates a control for every item in the source file's specified path location. However, this array may contain duplicate items (with the same IDs). Thus, the `arrayTransformer` is being leveraged to de-duplicate items with the same ID and collapse them into one element. - `pathTransform`: Converts the JSON object path structure. - Use: @@ -66,7 +94,7 @@ OHDF Converters is the library that hosts and provides OHDF mappers to other app pathTransform: (value) => (Array.isArray(value) ? value : []), ``` -- `key`: Used by base-converter to sort an array of objects by +- `key`: Used by base-converter to sort an array of objects by. Currently, this is only used in the `controls` array area to automatically de-duplicate elements with the same key to ensure that they are unique. Thus, we have only ever been passing `id` as a `key`. When calling the constructor for the mapper, we can set `collapseResults=true` to make use of this automatic deduplication function. - Use: ```typescript key: KEY_AS_STRING @@ -79,7 +107,7 @@ OHDF Converters is the library that hosts and provides OHDF mappers to other app ### Directory Structure -The following is a simplified depiction of the directory tree for the HDF Converter. Only noteworthy and potentially useful files and directories are included. It is not imperative to memorize the structure, but it is useful to familiarize yourself with it to better understand what exists where within the HDF Converter for future reference. +The following is a simplified depiction of the directory tree for the HDF Converters. Only noteworthy and potentially useful files and directories are included. It is not imperative to memorize the structure, but it is useful to familiarize yourself with it to better understand what exists where within the library for future reference. ``` hdf-converters diff --git a/src/courses/mappers/10.md b/src/courses/mappers/10.md index 83a3db61f..616a1b198 100644 --- a/src/courses/mappers/10.md +++ b/src/courses/mappers/10.md @@ -7,7 +7,7 @@ author: Charles Hu ## The Art of Mapper Making -Mapper creation is an inherently tricky process as every situation demands a unique and tailored solution. As a result, there is no one objective best template or process to follow as field translations will always be designed on a case-by-case basis. +Mapper creation is a nuanced process as every situation demands a unique and tailored solution. As a result, there is no one objective best template or process to follow as field translations will always be designed on a case-by-case basis. But don't fret! Mapper making, like many forms of development, is a skill you have to cultivate and improve at. So while there is no one-size-fits-all solution, you can still train yourself to produce mappers that are the best for your needs and uses. From 33593120d95a58d32cdd83b649366e96e501867f Mon Sep 17 00:00:00 2001 From: Ryan Lin Date: Wed, 26 Jun 2024 11:17:19 -0700 Subject: [PATCH 54/71] cleanup Signed-off-by: Ryan Lin --- src/courses/mappers/09.md | 4 ---- 1 file changed, 4 deletions(-) diff --git a/src/courses/mappers/09.md b/src/courses/mappers/09.md index 2a2549dbe..4fe114973 100644 --- a/src/courses/mappers/09.md +++ b/src/courses/mappers/09.md @@ -63,10 +63,6 @@ OHDF Converters is the library that hosts and provides OHDF mappers to other app ``` - `arrayTransformer`: The `arrayTransformer` works similarly to the `transformer` in that it takes our in-progress mapping for the array structure, accepts a function that returns an array, and transforms the array accordingly (whether it be filtering out some items, passing in some additional data, or otherwise). - - - -Again, explain your example more clearly and provide more text and code context. What is happening in your example is that the arraytransformer func was used in the controls array. we created a control per every item in the source file's site.alerts array, but that array contains duplicate items. because our controls array requires the id for each control to be unique (building off of prior explained knowledge of the hdf schema), we need to de-duplicate them by consolidating any controls that have the same id. we then return the array of controls which now will contain fewer items. - Use: ```typescript arrayTransformer: (PARAMETER: TYPE[]): OUTPUT_TYPE[] => {CODE_TO_EXECUTE} From 1a6bd612f6985b2ba19b87150ff3d0d4e84c2345 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 26 Jun 2024 16:05:04 -0400 Subject: [PATCH 55/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/03.md | 6 +- src/courses/mappers/05.md | 50 +++++---- src/courses/mappers/06.md | 219 +++++++++++++++----------------------- 3 files changed, 114 insertions(+), 161 deletions(-) diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index 0e245fa97..bf11e8639 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -33,7 +33,7 @@ SAF has five core capabilities, of which OHDF is involved in varying degrees: - **Visualize**: OHDF is ingested by a variety of tools and transformed in many different ways. For example, a results file can be turned into a threshold file for pipeline use, turned into a POAM for ingestion by eMASS, or ingested by Heimdall directly for display purposes. -![](./img/saf_security_validation_lifecycle.png) +![SAF has five core capabilities, which we have developed/identified tooling and scripts to address.](./img/saf_security_validation_lifecycle.png) You can read more about SAF [here](../user/03.md). @@ -51,10 +51,10 @@ The Security Automation Framework Command Line Interface (SAF CLI) brings togeth An example use case of the SAF CLI is for automating certain security processes in a CI/CD pipeline. One process would be normalizing security data into OHDF using the `saf convert` command. One can set up the SAF CLI to automatically ingest security reports generated from the build pipeline, and then forward the newly generated OHDF files to a visualization tool such as Heimdall that allows a security assessor to review the state of the current software build. -![SAF CLI Utility Overview](./img/saf_cli_features.png) +![SAF CLI utility overview: Attest, Convert, View, Validate, and Generate](./img/saf_cli_features.png) ## What Is Heimdall? [Heimdall](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. Data that is imported into Heimdall is automatically converted to OHDF through OHDF Converters, which serves as the underlying library that services data format conversion requests in Heimdall. -![An instance of Heimdall visualizing a security result set](./img/heimdall_view.png) +![An instance of Heimdall visualizing a security result set. Results are displayed with figures, charts, and compliance level percentages to quickly convey important takeaways at a glance.](./img/heimdall_view.png) diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index ef9e6cc01..0edc2d600 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -9,39 +9,45 @@ author: Charles Hu In order to make an OHDF mapper, it is important to understand the specifics of how OHDF is actually structured through the OHDF schema. -The OHDF schema is designed to provide a simple, structured, and hierarchal view of security tool results. Any file or object that implements the schema can be broken down into a hierarchy of three structures. These structures are: +The OHDF schema is designed to provide a simple, structured, and hierarchal view of security tool results. OHDF actually consists of several related schema formats; however, the Exec JSON format is the most common and is typically the one being referred to when speaking of the OHDF schema. Any file or object that implements the schema can be broken down into a hierarchy of four main structures. These structures are: -### 1. **Profiles** +### 1. **Exec JSON** -This structure contains metadata on the target system of the original security tool export and on the specific run performed by the security tool. Profiles provide a high-level overview of the security tool result and the targeted system, which are formatted in a manner which is digestible and immediately accessible to the assessor. +This is the top level structure that contains both the security data (which is stored in the Profiles structure) and relevant metadata on the tool used to generate the OHDF file (stored in structures such as Platform, Statistics, and Version). -### 2. **Controls** +### 2. **Profiles** + +This structure contains metadata on the target system of the original security tool export and on the specific run performed by the security tool. Profiles provide a high-level overview of the security tool result and the targeted system, which are formatted in a manner which is digestible and immediately accessible to the assessor. There is typically only one profiles structure. Further instances of profiles are additional overlays. + +### 3. **Controls** Controls are security requirements that are used to prevent, mitigate, and address various security risks to sensitive information and infrastructure. In the case of OHDF, the controls structure is a collection of requirements tested for by an external security tool to ensure that the target complies with vulnerability and weakness prevention standards. Any given profile contains some number of controls which were tested against the target system during the original security tool run. -### 3. **Results** +### 4. **Results** -The results structure contains information on the results of specific tests ran by the security tool on the target system against a security requirement/control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses exist but are rare) which cumulatively influence the determined compliance level of the target system for some set of requirements/controls. Any given control contains some number of results which reflect the implemented tests to check if the target system is actually compliant. +The results structure contains information on the results of specific tests ran by the security tool on the target system against a security requirement/control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses include `skipped` and `error`) which cumulatively influence the determined compliance level of the target system for some set of requirements/controls. Any given control contains some number of results which reflect the implemented tests to check if the target system is actually compliant. ## Overall Hierarchy -These aforementioned structures cumulatively result in the following generalized structure: +These aforementioned main structures cumulatively result in the following generalized structure: ```json // Data fields have been removed for the sake of demonstration -profiles: [ - 0: { - controls: [ - 0: { - results: [ - 0: { - }, - ... - ] - }, - ... - ] - }, - ... -] +execjson: { + profiles: [ + 0: { + controls: [ + 0: { + results: [ + 0: { + }, + ... + ] + }, + ... + ] + }, + ... + ] +} ``` diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index f6da4deed..03529443b 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -10,52 +10,49 @@ author: Charles Hu We can break down the formal OHDF schema in the same manner as before by observing each structure in the hierarchy from a top-down view. ::: note Full OHDF Schema -The following section contains a breakdown of a streamlined version of the OHDF schema. For the full and up-to-date version, see [here](https://saf.mitre.org/framework/normalize/ohdf-schema). +The following section contains a breakdown of a streamlined version of the OHDF schema. For the full and up-to-date version, see [here](https://saf.mitre.org/framework/normalize/ohdf-schema). Visit [here](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts) for the technical implementation of the schema. ::: -### 1. **Profiles** - -::: details Profiles Schema -```json -profiles: [ - 0: { - name, - version, - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls, - status - }, - ... // More items may exist if the security service produces multiple profiles per export -] -``` -::: - -- `name`: Name of profile, usually the original security service tool; should be unique. -- `version`: Version of security service tool. -- `sha256`: Checksum of the profile (NOTE: AUTOMATICALLY GENERATED BY HDF CONVERTERS, DO NOT POPULATE). -- `title`: Title of security service scan; should be human readable. -- `maintainer`: Maintainer. -- `summary`: Summary of security service export (e.g., the STIG header). -- `license`: Copyright license. -- `copyright`: Copyright holder. -- `copyright_email`: Copyright holder's email. -- `supports`: Supported platform targets. -- `attributes`: Inputs/attributes used in scan. -- `groups`: Set of descriptions for the control groups (e.g., control IDs). -- `controls`: Controls substructure (see below). -- `status`: Status of profile (typically 'loaded'). +### 1. Exec JSON + +Field Name | Definition +-|- +`platform` | Platform substructure (see `Additional Structures`). +`profiles` | Profiles substructure (see below). +`statistics` | Statistics substructure (see below). +`version` | Version of tool generating the file. + +### 2. **Profiles** + +Field Name | Definition +-|- +`name` | Name of profile, usually the original security tool; must be unique. +`version` | Version of security tool. +`sha256` | Checksum of the profile (NOTE: AUTOMATICALLY GENERATED BY HDF CONVERTERS, DO NOT POPULATE). +`title` | Title of security tool; must be human readable. +`maintainer` | Maintainer(s). +`summary` | Summary of security data (e.g., the STIG header). +`license` | Copyright license. +`copyright` | Copyright holder. +`copyright_email` | Copyright holder's email. +`supports` | Supported platform targets. +`attributes` | Inputs/attributes used in scan. +`groups` | Set of descriptions for the control groups (e.g., control IDs). +`controls` | Controls substructure (see below). +`status` | Status of profile (typically 'loaded'). +`status_message` | Reason for the status. +`skip_message` | Reason for skipping this profile if skipped. +`depends` | Set of dependencies this profile depends on (e.g., an overlay profile is dependent on another profile). +`parent_profile` | Name of the parent profile if this profile is a dependency of another profile. +`description` | Description of profile; should be more detailed than summary. +`inspec_version` | The version of the Inspec tool used to generate this profile. #### Example +:::note Required Fields +Not all fields are required. This will be expanded upon in the next section. +::: + Here's an example of a profiles section from a converted GoSec data file: ::: details OHDF Converted GoSec Data @@ -78,38 +75,21 @@ Here's an example of a profiles section from a converted GoSec data file: ``` ::: -### 2. **Controls** - -::: details Controls Schema -```json -controls: [ - 0: { - id, - title, - desc, - descriptions, - impact, - refs, - tags, - code, - source_location, - results - }, - ... // More items may exist if there are multiple controls reported per profile -] -``` -::: - -- `id`: ID of control, used for sorting; should be unique for each unique control. -- `title`: Title of control. -- `desc`: Description of the control. -- `descriptions`: Additional descriptions; usually 'check' and 'fix' text for control. -- `impact`: Security severity of control. On a scale of 0.1 to 1. This metric is aligned with the [Common Vulnerability Scoring System (CVSS)](https://www.first.org/cvss/). -- `refs`: References to external control documentation. -- `tags`: Control tags; typically correlate to existing vulnerability/weakness database (e.g., NIST, CVE, CWE). -- `code`: Control source code for code preservation. -- `source_location`: Location of control within source code. -- `results`: Results substructure (see below). +### 3. **Controls** +Field Name | Definition +-|- +`id` | ID of control, used for sorting. +`title` | Title of control. +`desc` | The overarching description of the control. +`descriptions` | Additional descriptions; usually 'check' and 'fix' text for control. +`impact` | Security severity of control. On a scale of 0 to 1. This metric is aligned with the [Common Vulnerability Scoring System (CVSS)](https://www.first.org/cvss/). +`refs` | References to external control documentation. +`tags` | Control tags; typically correlate to existing vulnerability/weakness database (e.g., NIST, CVE, CWE). +`code` | Control source code for code preservation. +`source_location` | Location of control within source code. +`results` | Results substructure (see below). +`waiver_data` | Information on waiver if applicable. +`attestation_data` | Information on attestation if applicable. #### Example @@ -144,28 +124,20 @@ Here's an example of a controls section from a converted GoSec data file: ``` ::: -### 3. **Results** - -::: details Results Schema -```json -results: [ - 0: { - status, - code_desc, - message, - run_time, - start_time - }, - ... // More items may exist if there are multiple results tested per control -] -``` -::: - -- `status`: Pass/fail status of test (other statuses exist but are rare). -- `code_desc`: Test expectations as defined by control. -- `message`: Demonstration of expected and actual result of test to justify test status. -- `run_time`: Overall runtime of test. -- `start_time`: Starting time of test. +### 4. **Results** + +Field Name | Definition +-|- +`status` | `passed`/`failed` status of test (other status include `skipped` and `error`). +`skip_message` | Reasoning for if test has `skipped` status. +`code_desc` | Test expectations as defined by control. +`exception` | Type of exception if one was thrown. +`backtrace` | Backtrace of exception if one was thrown. +`message` | Explanation of test status; typically in the form of expected and actual results. +`resource` | Resources used in the test (e.g., Inspec). +`resource_id` | The unique ID of the used resources. +`run_time` | Overall runtime of test. +`start_time` | Starting time of test. #### Example @@ -184,50 +156,25 @@ Here's an example of a results section from a converted Twistlock data fi ``` ::: -### 4. Additional Structures +### 5. Additional Structures There are additional structures in the OHDF schema which are used for metadata/extraneous information storage. These exist alongside the profiles structure on the top level of the HDF schema. The general structure for the top level of the HDF schema is as follows: -::: details Additional Schema -```json -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles, - passthrough: { - auxiliary_data: [ - 0: { - name, - data - }, - ... // More items may exist if there are multiple auxiliary data sources available - ], - raw - } -} -``` -::: - -- `platform`: Information on the platform producing the export. - - `name`: Name of platform export was run on. - - `release`: Platform version. - - `target_id`: Platform target ID (i.e., further identifying information on platform). -- `version`: Platform version. -- `statistics`: Statistics relating to target scan run. - - `duration`: Duration of run. -- `profiles`: Profiles structure. -- `passthrough`: Extraneous information storage. - - `auxiliary_data`: Storage for unused data from the sample file. - - `name`: Name of auxiliary data source. - - `data`: Auxiliary data. - - `raw`: Raw data dump of input security service export. +Field Name | Definition +-|- +`platform` | Information on the platform producing the export. +`platform.name` | Name of platform export was run on. +`platform.release` | Platform version. +`platform.target_id` | Platform target ID (i.e., further identifying information on platform). +`statistics` | Statistics relating to target scan run. +`statistics.controls` | Break down of control statistics by result status. +`statistics.duration` | Duration of run (in seconds). +`profiles` | Profiles structure. +`passthrough` | Extraneous information storage. +`passthrough.auxiliary_data` | Storage for unused data from the sample file. +`passthrough.auxiliary_data.name` | Name of auxiliary data source. +`passthrough.auxiliary_data.data` | Auxiliary data. +`passthrough.raw` | Raw data dump of input security service export. #### Example From e812273404c25b30a17a7f2f0ed68b3326dd04a2 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 26 Jun 2024 16:53:46 -0400 Subject: [PATCH 56/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/06.md | 215 +++++++++++++++++++++++++++----------- src/courses/mappers/08.md | 3 + 2 files changed, 156 insertions(+), 62 deletions(-) diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index 03529443b..b18f360d7 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -13,6 +13,10 @@ We can break down the formal OHDF schema in the same manner as before by observi The following section contains a breakdown of a streamlined version of the OHDF schema. For the full and up-to-date version, see [here](https://saf.mitre.org/framework/normalize/ohdf-schema). Visit [here](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts) for the technical implementation of the schema. ::: +:::note Required Fields +Not all fields are required. This will be expanded upon in the next section. +::: + ### 1. Exec JSON Field Name | Definition @@ -47,13 +51,42 @@ Field Name | Definition `description` | Description of profile; should be more detailed than summary. `inspec_version` | The version of the Inspec tool used to generate this profile. -#### Example +#### Knowledge Check -:::note Required Fields -Not all fields are required. This will be expanded upon in the next section. -::: +Given a snippet of GoSec data, try and identify what information is applicable to the **Profiles** structure and which field they would correlate with. -Here's an example of a profiles section from a converted GoSec data file: +::: details GoSec Source Data +```json +{ + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + "GosecVersion": "dev" +} +``` +::: ::: details OHDF Converted GoSec Data ```json @@ -91,9 +124,42 @@ Field Name | Definition `waiver_data` | Information on waiver if applicable. `attestation_data` | Information on attestation if applicable. -#### Example +#### Knowledge Check -Here's an example of a controls section from a converted GoSec data file: +Given a snippet of GoSec data, try and identify what information is applicable to the **Controls** structure and which field they would correlate with. + +::: details GoSec Source Data +```json +{ + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + "GosecVersion": "dev" +} +``` +::: ::: details OHDF Converted GoSec Data ```json @@ -139,18 +205,51 @@ Field Name | Definition `run_time` | Overall runtime of test. `start_time` | Starting time of test. -#### Example +#### Knowledge Check -Here's an example of a results section from a converted Twistlock data file: +Given a snippet of GoSec data, try and identify what information is applicable to the **Results** structure and which field they would correlate with. -::: details OHDF Converted Twistlock Data +::: details GoSec Source Data +```json +{ + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + "GosecVersion": "dev" +} +``` +::: + +::: details OHDF Converted GoSec Data ```json "results": [ { "status": "failed", - "code_desc": "Package \"nss-util\" should be updated to latest version above impacted versions [\"*\"]", - "message": "Expected latest version of \"nss-util\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-util\"", - "start_time": "2022-05-18T12:24:22Z" + "code_desc": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "message": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go, line:83, column:14", + "start_time": "" } ] ``` @@ -176,60 +275,52 @@ Field Name | Definition `passthrough.auxiliary_data.data` | Auxiliary data. `passthrough.raw` | Raw data dump of input security service export. -#### Example +#### Knowledge Check -Here's an example of the additional structures from a converted Twistlock data file: +Given a snippet of GoSec data, try and identify what information is applicable to the additional structures and which field they would correlate with. -::: details OHDF Converted Twistlock Data +::: details GoSec Source Data ```json { - "platform": { - "name": "Heimdall Tools", - "release": "2.10.8", - "target_id": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a" + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 }, + "GosecVersion": "dev" +} +``` +::: + +::: details OHDF Converted GoSec Data +```json +{ + "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, "version": "2.10.8", "statistics": {}, - "profiles": [ - ... - ], + "profiles": [], "passthrough": { - "auxiliary_data": [ - { - "name": "Twistlock", - "data": { - "results": [ - { - "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", - "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", - "distroRelease": "RHEL8", - "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", - "packages": [ - { - "type": "os", - "name": "nss-util", - "version": "3.67.0-7.el8_5", - "licenses": ["MPLv2.0"] - } - ], - "applications": [ - { - "name": ".net-core", - "version": "5.0.17", - "path": "/usr/lib64/dotnet/dotnet" - } - ], - "complianceScanPassed": true, - "vulnerabilityScanPassed": true, - "history": [{ "created": "2022-05-03T08:38:31Z" }], - "scanTime": "2022-05-18T12:24:32.855444532Z", - "scanID": "6284e580d9600f8d0db159e2" - } - ], - "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" - } - } - ] + "auxiliary_data": [{ "name": "Gosec", "data": { "Golang errors": {} } }] } } ``` @@ -246,11 +337,11 @@ Here's an example of the additional structures from a converted Twistlock data f ::: :::details What is the relationship between Profiles, Controls, and Results? -- Any given profile contains some number of controls which were tested against the target system during the original security tool run. +- The profile contains some number of controls which were tested against the target system during the original security tool run. - Any given control contains some number of results which reflect the implemented tests to check if the target system is actually compliant. ::: -:::details What is `passthrough`? -`passthrough` is used to store extraneous information from the source data that has no equivalent in the OHDF schema. It is also used to store the entire raw source data in the `raw` subfield. +:::details What is the purpose of `passthrough`? +`passthrough` is used to store extraneous information from the source data that has no equivalent in the OHDF schema. It is also used to store the entire raw source data in the `raw` subfield. The overall goal is to preserve data as thoroughly as possible. ::: diff --git a/src/courses/mappers/08.md b/src/courses/mappers/08.md index d5efb94b5..cdab18b46 100644 --- a/src/courses/mappers/08.md +++ b/src/courses/mappers/08.md @@ -13,6 +13,9 @@ Here are some key questions to keep note of while reading through these examples - How is the source data structured/organized (e.g., by requirement, by target system, by finding)? - How is the OHDF file structured? +- What should we do when multiple source data fields correspond to the same OHDF field? +- How should we handle a source data field that contains information correlating to multiple oHDF fields? +- How should we handle source data fields that don't fit into the OHDF schema? - How is the structure of the source data interpreted to fit the OHDF hierarchy? - What groups of fields in the source data correlate to our profiles, controls, and results structures? - Which fields in the source data are used to fill each OHDF field? Is that mapping accurate? From 2744ced5a02481b934e5176b7387ec3c0b2663c5 Mon Sep 17 00:00:00 2001 From: Ryan Lin Date: Thu, 27 Jun 2024 08:46:24 -0700 Subject: [PATCH 57/71] Minor wording changes and clarity fixes Signed-off-by: Ryan Lin --- src/courses/mappers/09.md | 3 ++- src/courses/mappers/13.md | 33 ++++++++++++++------------------- src/courses/mappers/14.md | 17 +++++++++-------- src/courses/mappers/15.md | 4 +++- src/courses/mappers/18.md | 2 +- 5 files changed, 29 insertions(+), 30 deletions(-) diff --git a/src/courses/mappers/09.md b/src/courses/mappers/09.md index 4fe114973..939aa989b 100644 --- a/src/courses/mappers/09.md +++ b/src/courses/mappers/09.md @@ -79,7 +79,8 @@ OHDF Converters is the library that hosts and provides OHDF mappers to other app ``` In the above code block, the `arrayTransformer` is used in the controls array of the mapping, which creates a control for every item in the source file's specified path location. However, this array may contain duplicate items (with the same IDs). Thus, the `arrayTransformer` is being leveraged to de-duplicate items with the same ID and collapse them into one element. -- `pathTransform`: Converts the JSON object path structure. +- `pathTransform`: Converts the JSON object path structure. This preprocesses the source file before *any* of the other keywords are run. We only use this as a last resort if the source file needs to be drastically reworked. Using the `pathTransform` can be difficult to work through, since the intermediate format generated by it is not saved to disk anywhere. + - Use: ```typescript pathTransform: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index 19590fd43..6491ce3ab 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -21,7 +21,7 @@ We begin the creation of every OHDF mapper by first planning out how we want cor As we develop the mappings in the following examples, note that we will break down and analyze the fields according to the OHDF schema structures we previously learned about (profiles, controls, and results). This is not necessarily the only or the best way to do this and you are encouraged to develop your own methods for correlating fields that work best for you. ::: note Use of Exported Security Tool Data -The following examples will use generated instances of exported security tool data that do not reflect the entirety of the schemas they are based on. Ideally, you will want to use the full schema when creating a mapping; however, the full schema is typically not readily available. To reflect this, we will be using generated export data and will fill in missing schema data when possible. +The following examples will use generated instances of exported security tool data that do not reflect the entirety of the schemas they are based on. Ideally, you will want to use the full schema when creating a mapping; however, the full schema is always not readily available. To reflect this, we will be using generated export data and will fill in missing schema data when possible. ::: ## Mapping Demo - GoSec @@ -69,11 +69,6 @@ We can begin our mapping process by identifying the purpose of each field in the - Is this field recording requirements? - Is this field recording requirement testing? -To summarize, we should be asking ourselves the following two questions for each field in the source data: - -- What is the purpose of this field? -- What is this field recording (metadata, requirements, requirement testing)? - Let's apply this to our GoSec source data. Try to find the answers to these two questions for each field yourself and then refer back to our annotated solution to check your work. ::: details GoSec Annotated Source Data @@ -147,7 +142,7 @@ The purpose of this annotation is to understand the intention of the security to Now that we're familiar with the specifics of the GoSec schema, we can begin to map these fields to the OHDF schema. We'll do this by taking a field in the source data and correlating it to the most applicable OHDF schema field. While performing these correlations, it is important to account for the intention and structure of the source data schema. -These mapping are informal and do not need to adhere to any programming syntax. The mapping process entails taking the full field path from the source data and placing it as the corresponding value for the OHDF schema field. Proper implementation of these mappings will be done later in the course. An example of such mapping is as follows: +This initial mapping is informal and does not need to adhere to any programming syntax since you're probably annotating the documents by hand. The mapping process entails taking the full field path from the source data and placing it as the corresponding value for the OHDF schema field. Proper implementation of these mappings will be done later in the course. An example of such mapping is as follows: ```typescript { profiles: [ @@ -497,7 +492,7 @@ OHDF | Source Data Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.nosec`, and `Issues.suppressions`. -::: details Correlated +::: details Correlated Fields OHDF | Source Data -|- `profiles.controls.tags` | `Issues.severity` @@ -674,7 +669,7 @@ OHDF | Source Data { status, code_desc: Issues.code, // The code for the requirement test - message: { // All materials describing where the issue occured + message: { // All materials describing where the issue occurred Issues.file, Issues.line, Issues.column @@ -781,7 +776,7 @@ OHDF | Source Data { status, code_desc: Issues.code, // The code for the requirement test - message: { // All materials describing where the issue occured + message: { // All materials describing where the issue occurred Issues.file, Issues.line, Issues.column @@ -811,7 +806,7 @@ OHDF | Source Data ::: details Reasoning For these fields, we can place them in `passthrough` as there are no reasonably applicable fields in the OHDF schema to place them in. -`Golang errors` is not used anywhere in `controls` as it is a description of compilation errors which would've already been flagged by GoSec as security issues if they already occured. Thus, to avoid duplication, `Golang errors` is omitted from the main OHDF structures. +`Golang errors` is not used anywhere in `controls` as it is a description of compilation errors which would've already been flagged by GoSec as security issues if they already occurred. Thus, to avoid duplication, `Golang errors` is omitted from the main OHDF structures. ::: #### Mapping Version 6 @@ -866,9 +861,9 @@ OHDF | Source Data source_location: {}, // Not enough info to fill results: [ { - status: 'Failure', // The security scan only reports failed requirements, so all findings we receive get fail statuses + status: 'failed', // The security scan only reports failed requirements, so all findings we receive get fail statuses code_desc: Issues.code, // The code failing the requirement test - message: { // All materials describing where the issue occured + message: { // All materials describing where the issue occurred Issues.file, Issues.line, Issues.column @@ -911,7 +906,7 @@ The reasoning for the filled fields are as follows: - `impact: 0.5`: We use a default value of `0.5` since we do not have a direct mapping set up to convert the `Issues.severity` field. -- `status: 'Failure'`: GoSec only reports security vulnerabilities if it finds that the scanned source code has such security issues present. As such, every reported issue in a GoSec scan will always be a result of a failed security test. +- `status: 'failed'`: GoSec only reports security vulnerabilities if it finds that the scanned source code has such security issues present. As such, every reported issue in a GoSec scan will always be a result of a failed security test. - `status: 'loaded'`: The status of a profile is typically `loaded` since it has been ingested and converted to OHDF. ::: @@ -989,7 +984,7 @@ Let's first start with our DbProtect sample. You may notice that the metadata field maps corresponding keys to each of the values in a row of the data field. Consider ways you might try to restructure this data, but focus mainly on the purpose of each of the values for now. We will handle data restructuring in a later portion. -Unlike with GoSec, DbProtect does not have a published schema. Thus, we must empirically reason the mapping based on our sample data. Thus, even more so than the previous example, this process is subjective and your mapping may vary from ours. One thing we can use to inform ourselves about the purpose of each field in place of a schema, however, is the metadata fields at the top of the sample. Recall the three questions we ask ourselves to tie back identified purposes to the three general OHDF schema structures: +Unlike with GoSec, DbProtect does not have a published schema. Thus, we must empirically reason the mapping based on our sample data. Because we are reasoning solely off of sample data, even more so than the previous example, this process is subjective and your mapping may vary from ours. One thing we can use to inform ourselves about the purpose of each field in place of a schema, however, is the metadata fields at the top of the sample. Recall the three questions we ask ourselves to tie back identified purposes to the three general OHDF schema structures: - Is this field recording metadata? - Is this field recording requirements? @@ -1032,7 +1027,7 @@ Let us now apply this philosophy to our DbProtect source data. Try to find the a Audit - + Microsoft SQL Server @@ -1248,7 +1243,7 @@ OHDF | Source Data Audit - + Microsoft SQL Server @@ -1386,7 +1381,7 @@ OHDF | Source Data TEST ORGANIZATION (Local DBP server) - + Microsoft SQL Server @@ -1501,7 +1496,7 @@ OHDF | Source Data ::: details Reasoning As mentioned previously, OHDF does not have a specific place to put information like the `Organization`, `Asset`, or `Asset Type`. However, we do have a summary field for profiles. Recall our goal of preserving as much data as possible from the source. With this in mind, it would be reasonable to map all these fields to the summary for the sake of preservation. -The profile name and title fields are a little tricky. Note that the `Policy` field refers to the baseline guidance that the scan tested against. This aligns more with the profile name than the `Job Name`, which is just the a name the customer added for the report. Thus, we map the `Policy` field to the `profiles.name` and the `Job Name` field to the `profiles.title` instead. +The profile name and title fields are a little tricky. Note that the `Policy` field refers to the baseline guidance that the scan tested against. This aligns more with the profile name than the `Job Name`, which is just a name the customer added for the report. Thus, we map the `Policy` field to the `profiles.name` and the `Job Name` field to the `profiles.title` instead. ::: #### Mapping Version 4 diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index 20660db3d..92319488c 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -266,10 +266,11 @@ With the necessary files now set up, we can begin the actual creation of the OHD Certain security services produce exports which are not immediately usable by the skeleton mapper. In such case, pre-processing on the export and or post-processing on the generated OHDF file is necessary in order to ensure compatibility. ::: -While developing the mapper, it's useful to occassionally check on the outputed OHDF file to check that the mapper is working as intended. You can do this by starting a local instance of Heimdall2 with the following command: +While developing the mapper, it's useful to occasionally check on the generated OHDF file to check that the mapper is working as intended. You can do this by starting a local instance of Heimdall with the following command: ```shell yarn start:dev ``` +Note that the `yarn start:dev` command will dynamically rebuild the application upon changes to the Heimdall frontend. However, if you make any changes to OHDF-Converters, you will have to restart the command entirely. Import your source data and then export it as an OHDF JSON to check what your mapper is actually mapping. @@ -314,9 +315,9 @@ Here is our developed mapping for GoSec for reference: source_location: {}, // Not enough info to fill results: [ { - status: 'Failure', // The security scan only reports failed requirements, so all findings we receive get fail statuses + status: 'failed', // The security scan only reports failed requirements, so all findings we receive get fail statuses code_desc: Issues.code, // The code failing the requirement test - message: { // All materials describing where the issue occured + message: { // All materials describing where the issue occurred Issues.file, Issues.line, Issues.column @@ -510,7 +511,7 @@ export class GoSecMapper extends BaseConverter { results: [ { code_desc: Issues.code, // The code failing the requirement test - message: { // All materials describing where the issue occured + message: { // All materials describing where the issue occurred Issues.file, Issues.line, Issues.column @@ -638,7 +639,7 @@ export class GoSecMapper extends BaseConverter { { results: [ { - message: { // All materials describing where the issue occured + message: { // All materials describing where the issue occurred Issues.file, Issues.line, Issues.column @@ -1130,7 +1131,7 @@ Here is our developed mapping for DbProtect for reference: Audit - + Microsoft SQL Server @@ -1331,7 +1332,7 @@ Next, let's look at the fields which can be just simply be directly ported over ```typescript name: {path: 'data.[0].Policy'} ``` -Note that in this example, we must call the path with `data.[0]`, since even though the Policy is the same fo all data rows, we still must specify an element to extract the data from. +Note that in this example, we must call the path with `data.[0]`, since even though the Policy is the same for all data rows, we still must specify an element to extract the data from. Let's put this into practice and start implementing the mappings for simple fields that don't require transformation or processing: @@ -1473,7 +1474,7 @@ export class DBProtectMapper extends BaseConverter { #### Transformed/Processed Fields -As in the previous example, there are several fields that need to be processed further. To do so, we can make use of the `transformer` field supported by the OHDF Converters library. Firstly, some simple transformes include casting the `id` field to a string, and mapping the `impact` fields properly (by creating a mapping and passing it into the `impactMapping` function in `base-converter`): +As in the previous example, there are several fields that need to be processed further. To do so, we can make use of the `transformer` field supported by the OHDF Converters library. Some simple transformers include casting the `id` field to a string, and mapping the `impact` fields properly (by creating a mapping and passing it into the `impactMapping` function in `base-converter`): ```typescript const IMPACT_MAPPING: Map = new Map([ diff --git a/src/courses/mappers/15.md b/src/courses/mappers/15.md index de902ef80..2de68883a 100644 --- a/src/courses/mappers/15.md +++ b/src/courses/mappers/15.md @@ -11,6 +11,8 @@ Now that we have a mapper developed that can convert files from *-to-OHDF, we ne ### Using Regression Testing +Regression testing is extremely useful, as we make changes and improvements to mappers over time (for example, if we have new sample files or if the schema of a source format changes). Moreover, internal library changes, like an update to `base-converter`, or major dependency updates could change the behavior of a mapper significantly. If a particular change affects a mapping, we will need to regenerate the sample file through the following process: + First, we have to activate the regression testing suite that we created earlier to actually be able to automatically run and review your mapper. 1. Uncomment out the commented out lines in the `{YOUR-SAMPLE-EXPORT}-hdf.json` file. This will allow the regression tests to automatically generate an OHDF output file whenever you run the tests. These files are needed for the tests to check the output of your mappers. The commented out lines should look similar to the following: @@ -21,7 +23,7 @@ First, we have to activate the regression testing suite that we created earlier // ); ``` -2. Using the terminal, `cd` into the `hdf-converters` directory and run the following command. This command will run your mapper against the sample export file in `sample_jsons` and test to see if the output is generated as expected. This intial run, however, will be to create a baseline OHDF file for future regression tests to run against. +2. Using the terminal, `cd` into the `hdf-converters` directory and run the following command. This command will run your mapper against the sample export file in `sample_jsons` and tests to see if the output is generated as expected. However, this initial run will be used to create a baseline OHDF file for manual inspection to validate that we wrote the mapper properly and thereafter will be the comparison target for future runs to confirm that no regressions in the mapping occurred. ```shell yarn run test --verbose --silent=false ./test/mappers/forward/{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts ``` diff --git a/src/courses/mappers/18.md b/src/courses/mappers/18.md index 1f0c2368f..ab5aa4760 100644 --- a/src/courses/mappers/18.md +++ b/src/courses/mappers/18.md @@ -6,7 +6,7 @@ author: Charles Hu ## SAF CLI Integration -The following is a supplemental lesson on how to integrate your developed mapper with the SAF CLI. Integration with the SAF CLI will allow your mapper to be used in a command line environment, independent of Heimdall2. +The following is a supplemental lesson on how to integrate your developed mapper with the SAF CLI. Integration with the SAF CLI will allow your mapper to be used in a command line environment, independent of Heimdall2 throughout. If you have not yet created a mapper, please follow the primary course and do so. Once completed, you will be able to continue with this lesson. From fc9acaaae19d96e217227efd1cf3f70a9ba1d39d Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Thu, 27 Jun 2024 12:14:24 -0400 Subject: [PATCH 58/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 12 ++++++++---- src/courses/mappers/10.md | 2 +- src/courses/mappers/11.md | 2 +- 3 files changed, 10 insertions(+), 6 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index cc9aeb1fa..943d0d740 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -73,13 +73,15 @@ More information can be found [here](https://csrc.nist.gov/projects/risk-managem More information can be found [here](https://csrc.nist.gov/pubs/sp/800/53/r5/upd1/final). -:::details NIST SP 800-53 Excerpt +- NIST SP 800-53 excerpt: + +``` AC-17 REMOTE ACCESS Control: a. Establish and document usage restrictions, configuration/connection requirements, and implementation guidance for each type of remote access allowed; and b. Authorize each type of remote access to the system prior to allowing such connections. -::: +``` ::::: :::details DISA @@ -93,7 +95,9 @@ Control Correlation Identifiers (**CCIs**) are "standard identifiers and descrip More information can be found [here](https://public.cyber.mil/stigs/cci/). -:::details CCI Excerpt +- CCI excerpt: + +``` CCI-000002: Disseminate the organization-level; mission/business process-level; and/or system-level access control policy that addresses purpose, scope, roles, responsibilities, management commitment, coordination among organizational entities, and compliance to organization-defined personnel or roles. References: @@ -101,7 +105,7 @@ References: - NIST: NIST SP 800-53 Revision 4 (v4): AC-1 a 1 - NIST: NIST SP 800-53 Revision 5 (v5): AC-1 a 1 (a) - NIST: NIST SP 800-53A (v1): AC-1.1 (iii) -::: +``` ::::: ::::::: diff --git a/src/courses/mappers/10.md b/src/courses/mappers/10.md index 616a1b198..68062b32c 100644 --- a/src/courses/mappers/10.md +++ b/src/courses/mappers/10.md @@ -39,7 +39,7 @@ These answers will help ensure that the intent of the data isn't skewed by the m ### 4. Use a Detailed Sample ::: note APIs -If your security tool provides an API instead of a security data export, contact the SAF team for further guidance in creating a specialized mapper that works with that API. +If your security tool provides an API instead of a security data export, you will need to explore the API to determine what information may need to be collected and collated for use within the mapper. Even without an explicit results file from the vendor, you should have a thorough understanding of the security data that needs to be mapped to OHDF. We recommend contacting the SAF team for further guidance in creating a specialized mapper that works with that API. ::: Build your mapper around a sample output that is the most detailed the tool can provide, and try to obtain the data in any machine-readable format (e.g., JSON, XML, CSV) that is natively available. Also try to sanitize your data sample so that it is safe for public release in the OHDF Converters GitHub repository. diff --git a/src/courses/mappers/11.md b/src/courses/mappers/11.md index fc66fd4a4..aa13e09e6 100644 --- a/src/courses/mappers/11.md +++ b/src/courses/mappers/11.md @@ -7,7 +7,7 @@ author: Charles Hu ## Environment Set Up -Node.js (a runtime environment for JavaScript/TypeScript) and Yarn (a package manager for JavaScript/TypeScript) are external utilities which are utilized extensively within this guide. The following section details their installation process. +Node.js (a runtime environment for JavaScript) and Yarn (a package manager for JavaScript/TypeScript) are external utilities which are utilized extensively within this guide. The following section details their installation process. Linux/Mac OS: From e02e7cd4559b61252536d993e3abbe4320d4ead6 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Thu, 27 Jun 2024 15:41:42 -0400 Subject: [PATCH 59/71] Review change Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 8 ++++---- src/courses/mappers/06.md | 2 +- src/courses/mappers/README.md | 2 +- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 943d0d740..d957688e7 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -7,7 +7,7 @@ author: Charles Hu ## What is OHDF? -OASIS Heimdall Data Format (OHDF) is a security data format used to normalize generated data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security validation profiles, controls, and results. +OASIS Heimdall Data Format (OHDF) is a security data format used to normalize generated data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security data context, requirements, and measures. [OASIS Open](https://www.oasis-open.org/) is an international standards body that works on the development and advancement of open source technological standards. OHDF is currently in the process of becoming an OASIS Open standard. For more information on the OHDF charter for OASIS Open, [refer here](https://groups.oasis-open.org/communities/tc-community-home2?CommunityKey=f8888caa-8401-46f8-bf10-018dc7d3f577). @@ -68,8 +68,8 @@ The NIST Risk Management Framework (NIST RMF) provides "a process that integrate More information can be found [here](https://csrc.nist.gov/projects/risk-management/about-rmf). ::: -:::::details NIST SP 800-53 -- The NIST Special Publication 800-53 (**NIST SP 800-53**) "provides a catalog of security and privacy controls for information systems and organizations to protect organizational operations and assets, individuals, other organizations, and the Nation from a diverse set of threats and risks." +:::::details NIST SP 800-53 Controls/Requirements +- NIST Special Publication 800-53 (**NIST SP 800-53**) "provides a catalog of security and privacy controls for information systems and organizations to protect organizational operations and assets, individuals, other organizations, and the Nation from a diverse set of threats and risks." More information can be found [here](https://csrc.nist.gov/pubs/sp/800/53/r5/upd1/final). @@ -91,7 +91,7 @@ More information can be found [here](https://www.disa.mil/). ::: :::::details CCIs -Control Correlation Identifiers (**CCIs**) are "standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements." They are analogous to NIST SP 800-53s in that they both provide security and privacy controls. +Control Correlation Identifiers (**CCIs**) are "standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements." They are analogous to NIST SP 800-53 controls in that they both provide security and privacy controls. More information can be found [here](https://public.cyber.mil/stigs/cci/). diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index b18f360d7..91ed5323b 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -111,7 +111,7 @@ Given a snippet of GoSec data, try and identify what information is applicable t ### 3. **Controls** Field Name | Definition -|- -`id` | ID of control, used for sorting. +`id` | ID of control, used for sorting. Must be unique. `title` | Title of control. `desc` | The overarching description of the control. `descriptions` | Additional descriptions; usually 'check' and 'fix' text for control. diff --git a/src/courses/mappers/README.md b/src/courses/mappers/README.md index e0b231ffa..f5affe813 100644 --- a/src/courses/mappers/README.md +++ b/src/courses/mappers/README.md @@ -9,7 +9,7 @@ author: Charles Hu The purpose of this class is to provide you with the foundational knowledge needed to create data format mappers for mapping data to the [OASIS Heimdall Data Format (OHDF)](https://saf.mitre.org/framework/normalize). In the following course, you will be taught the art and science of schema translation through a combination of both guided explanations and hands-on demonstrations. -The class is split into 2 sections. The first portion will introduce you to the OHDF schema and its specificities, while the second portion will show you how to apply the OHDF schema to mappers for conversions from any security tool data format to OHDF. +The class is split into 2 sections. The first portion will introduce you to the OHDF schema and its specificities, while the second portion will show you how to apply the OHDF schema to mappers for conversions from any security data format to OHDF. ### Objectives From c915fa97cf194c314d7e06b763c2900b2103c92a Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Thu, 27 Jun 2024 16:14:59 -0400 Subject: [PATCH 60/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 10 +++++----- src/courses/mappers/03.md | 4 ++-- src/courses/mappers/05.md | 2 +- src/courses/mappers/06.md | 4 ++-- 4 files changed, 10 insertions(+), 10 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index d957688e7..d86edb1f8 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -13,9 +13,9 @@ OASIS Heimdall Data Format (OHDF) is a security data format used to normalize ge ## Why OHDF? -- Many security tools do not provide context to relevant compliance standards for comparison across security tools.​ +- Many security tools do not provide context to relevant categorization standards for comparison across security tools.​ - Security tools typically generate data in unique formats that require multiple dashboards and utilities to process.​ -- OHDF reduces the time it takes to process security assessments, data in disparate locations, and inconsistent semantics of a data element between formats.​ +- OHDF reduces the time it takes to process security data types, data in disparate locations, and inconsistent semantics of a data element between formats.​ ## Features @@ -50,11 +50,11 @@ See below for an example of how *some* fields in a source file are mapped to OHD ### 5. Allowing for the mapping and enrichment of security data to relevant compliance standards (GDPR, NIST SP 800-53, CCIs, PCI-DSS, etc.). -- Uses mappers which provide and append relevant compliance standards to converted security tool data. +- Uses mappers which provide and append relevant categorization standards to converted security tool data. :::::::note What Are All These Abbreviations? -The aforementioned terms are all security compliance related guidelines, frameworks, or implementations. The following are explanations on terms that are commonly used in this course: +The aforementioned terms are all security related guidelines, frameworks, or implementations. The following are explanations on terms that are commonly used in this course: :::details NIST The National Institute of Standards and Technology (NIST) is a U.S. agency that "promotes U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve quality of life." @@ -126,7 +126,7 @@ Some uses include: - Facilitating the transformation/transport of data across different processes and technologies. -- Enhancing security data with relevant compliance standards. +- Enhancing security data with relevant security standards. - And more. ::: diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index bf11e8639..c6d5f0d36 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -39,11 +39,11 @@ You can read more about SAF [here](../user/03.md). ## What Is InspecJS? -[InspecJS](https://github.com/mitre/heimdall2/tree/master/libs/inspecjs) is a library that provides schema definitions, classes, and utilities for OHDF file handling. InspecJS plays a pivotal role in the contextualization process where it performs tasks such as converting the individual statuses for each finding into an overall status for the control. +[InspecJS](https://github.com/mitre/heimdall2/tree/master/libs/inspecjs) is a library that provides schema definitions, classes, and utilities for OHDF file handling. InspecJS plays a pivotal role in the contextualization process where it performs tasks such as converting the individual statuses for each finding into an overall status for the requirement/control. ## What Is OHDF Converters? -[OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) is a custom data normalization library which hosts and leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated in tools such as [Heimdall](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security compliance testing and verification for systems such as automated build pipelines. +[OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) is a custom data normalization library which hosts and leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated in tools such as [Heimdall](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security testing and verification for systems such as automated build pipelines. ## What Is the SAF CLI? diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index 0edc2d600..de4664d41 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -25,7 +25,7 @@ Controls are security requirements that are used to prevent, mitigate, and addre ### 4. **Results** -The results structure contains information on the results of specific tests ran by the security tool on the target system against a security requirement/control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses include `skipped` and `error`) which cumulatively influence the determined compliance level of the target system for some set of requirements/controls. Any given control contains some number of results which reflect the implemented tests to check if the target system is actually compliant. +The results structure contains information on the results of specific tests ran by the security tool on the target system against a security requirement/control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses include `skipped` and `error`) which cumulatively influence the determined compliance level of the target system for some set of requirements/controls. Any given control contains some number of results which reflect the implemented tests to check if the target system is actually meeting the overall requirement/control. ## Overall Hierarchy diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index 91ed5323b..2c604f471 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -333,13 +333,13 @@ Given a snippet of GoSec data, try and identify what information is applicable t - Controls provides information on the security requirements being applied to the target system. -- Results provides information on the actual checks to ensure that the target system is compliant with the security requirements. +- Results provides information on the actual checks to ensure that the target system is meeting the security requirements. ::: :::details What is the relationship between Profiles, Controls, and Results? - The profile contains some number of controls which were tested against the target system during the original security tool run. -- Any given control contains some number of results which reflect the implemented tests to check if the target system is actually compliant. +- Any given control contains some number of results which reflect the implemented tests to check if the target system is actually meeting the security requirement. ::: :::details What is the purpose of `passthrough`? From 694e954072d1e4cfe1e5247956ba179b4c3b7d73 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Fri, 28 Jun 2024 13:55:39 -0400 Subject: [PATCH 61/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 26 ++++++++++++++++++++++++++ 1 file changed, 26 insertions(+) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index d86edb1f8..7cfe101c5 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -11,10 +11,18 @@ OASIS Heimdall Data Format (OHDF) is a security data format used to normalize ge [OASIS Open](https://www.oasis-open.org/) is an international standards body that works on the development and advancement of open source technological standards. OHDF is currently in the process of becoming an OASIS Open standard. For more information on the OHDF charter for OASIS Open, [refer here](https://groups.oasis-open.org/communities/tc-community-home2?CommunityKey=f8888caa-8401-46f8-bf10-018dc7d3f577). +OHDF's goal is to provide: + +- Standardization: Defining data elements in a consistent and contextualized manner. + +- Normalization: is the process for mapping a format's data elements into another format's data elements + ## Why OHDF? - Many security tools do not provide context to relevant categorization standards for comparison across security tools.​ + - Security tools typically generate data in unique formats that require multiple dashboards and utilities to process.​ + - OHDF reduces the time it takes to process security data types, data in disparate locations, and inconsistent semantics of a data element between formats.​ ## Features @@ -109,6 +117,24 @@ References: ::::: ::::::: +## Benefits + +- For Commercial and Vendor Cybersecurity Partners, OHDF defines a standardized, interoperable target format that vendor tools can consume across their customer base consistently and that is easily managed within the product lifecycle. + +- For the Open Source Community, OHDF enables easy integration with commercial solutions without the need for direct partnerships. + +- For Government Agencies, OHDF can streamline business processes by having a standard, open source, machine-readable format for all security data. + +- For Academia, OHDF offers a structured way to communicate and enhance research findings throughout the security community. + +- For Corporate and Federal CISOs/CIOs, OHDF can increase visibility across the enterprise by taking advantage of normalized security data in a standard format that supports risk information interoperability from a broad range of inputs to support security risk decision-making. + +- For Security Engineers, OHDF can reduce resource requirements for multiple security data types by standardizing formatting across disparate security tools. + +- For Risk Managers, OHDF can improve decision making by using a standardized format to facilitate automation, standardize communication requirements, and inform risk-based analysis. + +- For DevSecOps/Software Engineers, OHDF can streamline CI/CD processes by leveraging a standardized format to collate/aggregate normalized security data to support automated and continuous security processes. + ## What Else? You can read more about OHDF [here](https://saf.mitre.org/framework/normalize). From 61c51c4cac588d70ad97859b42a6801c9d52b0ed Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Mon, 1 Jul 2024 12:28:39 -0400 Subject: [PATCH 62/71] Review changes Signed-off-by: Charles Hu --- src/courses/mappers/02.md | 2 +- src/courses/mappers/13.md | 33 ++++++----------- src/courses/mappers/14.md | 25 ++----------- src/courses/mappers/16.md | 76 +++++++++++++++++++++++++++++++++++++++ src/courses/mappers/18.md | 8 +++++ 5 files changed, 98 insertions(+), 46 deletions(-) diff --git a/src/courses/mappers/02.md b/src/courses/mappers/02.md index 7cfe101c5..008ba90b4 100644 --- a/src/courses/mappers/02.md +++ b/src/courses/mappers/02.md @@ -99,7 +99,7 @@ More information can be found [here](https://www.disa.mil/). ::: :::::details CCIs -Control Correlation Identifiers (**CCIs**) are "standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements." They are analogous to NIST SP 800-53 controls in that they both provide security and privacy controls. +Control Correlation Identifiers (**CCIs**) are "standard identifiers and descriptions by DISA that aim to correlate high-level policy expressions and low-level technical implementations of security requirements." They are analogous to NIST SP 800-53 controls in that they both provide security and privacy controls. CCIs specifically address a single requirement and collate corresponding NIST SP 800-53 controls. More information can be found [here](https://public.cyber.mil/stigs/cci/). diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index 6491ce3ab..961dde881 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -158,7 +158,7 @@ This initial mapping is informal and does not need to adhere to any programming ``` This shows us a mapping of the field `Issues.details` from the source data to the field `profiles.controls.title` in OHDF. -Note that since we used an export from GoSec and are not basing our mapping off the full schema, we will inevitably miss some fields. We can rectify this by adding them into our mapping post hoc whenever needed; however, we can still capture these missed fields without manual intervention by using our `passthrough` field to capture unmapped data. +Note that sometimes every relevant field within the OHDF schema is addressed, but the source data still contains unmapped data. In such an event, it is good practice to ensure that such data is still passed through to and recorded somewhere within the OHDF schema for data preservation. In most cases, you should place such data in the `passthrough` field. Let's first start with an empty OHDF schema as follows: @@ -607,7 +607,7 @@ OHDF | Source Data ::: details Reasoning We map these fields to `tags` in the OHDF schema due to each of these fields acting as descriptive traits of the control which we can categorize and sort the controls by. -It may be tempting to map `Issues.severity` to `impact`; however, it is important to note that `severity` is not the same as `impact`. These two fields are separate and distinct metrics, and while conversion is possible, it is not performed in this case due to uncertainty on how to translate the two metrics properly. +It may be tempting to map `Issues.severity` to `impact`; however, it is important to note that `severity` is not the same as `impact`. These two fields are related but distinct metrics, and while conversion is possible, it is not performed in this case due to uncertainty on how to translate the two metrics properly. ::: #### Mapping Version 4 @@ -669,11 +669,7 @@ OHDF | Source Data { status, code_desc: Issues.code, // The code for the requirement test - message: { // All materials describing where the issue occurred - Issues.file, - Issues.line, - Issues.column - }, + message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred run_time, start_time } @@ -776,11 +772,7 @@ OHDF | Source Data { status, code_desc: Issues.code, // The code for the requirement test - message: { // All materials describing where the issue occurred - Issues.file, - Issues.line, - Issues.column - }, + message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred run_time, start_time } @@ -863,11 +855,7 @@ OHDF | Source Data { status: 'failed', // The security scan only reports failed requirements, so all findings we receive get fail statuses code_desc: Issues.code, // The code failing the requirement test - message: { // All materials describing where the issue occurred - Issues.file, - Issues.line, - Issues.column - }, + message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred start_time // Not enough info to fill } ] @@ -984,16 +972,15 @@ Let's first start with our DbProtect sample. You may notice that the metadata field maps corresponding keys to each of the values in a row of the data field. Consider ways you might try to restructure this data, but focus mainly on the purpose of each of the values for now. We will handle data restructuring in a later portion. -Unlike with GoSec, DbProtect does not have a published schema. Thus, we must empirically reason the mapping based on our sample data. Because we are reasoning solely off of sample data, even more so than the previous example, this process is subjective and your mapping may vary from ours. One thing we can use to inform ourselves about the purpose of each field in place of a schema, however, is the metadata fields at the top of the sample. Recall the three questions we ask ourselves to tie back identified purposes to the three general OHDF schema structures: +Unlike with GoSec, DbProtect does not have a published schema. Thus, we must empirically reason the mapping based on our sample data. Because we are reasoning solely off of sample data, even more so than the previous example, this process is subjective and your mapping may vary from ours. One thing we can use to inform ourselves about the purpose of each field in place of a schema, however, is the metadata fields at the top of the sample. -- Is this field recording metadata? -- Is this field recording requirements? -- Is this field recording requirement testing? - -Also recall that, for each field in the source data, we should be asking ourselves the following two questions: +#### Knowledge Check +::: details What questions do we ask ourselves when analyzing security data fields? - What is the purpose of this field? + - What is this field recording (metadata, requirements, requirement testing)? +::: Let us now apply this philosophy to our DbProtect source data. Try to find the answers to these two questions for each field yourself and then refer back to our annotated solution to check your work. diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index 92319488c..16e7918e9 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -44,13 +44,6 @@ import { MappedTransform } from './base-converter'; -const IMPACT_MAPPING: Map = new Map([ - ['critical', 0.9], - ['high', 0.7], - ['medium', 0.5], - ['low', 0.3] -]); - export class SKELETONMapper extends BaseConverter { withRaw: boolean; @@ -317,11 +310,7 @@ Here is our developed mapping for GoSec for reference: { status: 'failed', // The security scan only reports failed requirements, so all findings we receive get fail statuses code_desc: Issues.code, // The code failing the requirement test - message: { // All materials describing where the issue occurred - Issues.file, - Issues.line, - Issues.column - }, + message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred start_time // Not enough info to fill } ] @@ -511,11 +500,7 @@ export class GoSecMapper extends BaseConverter { results: [ { code_desc: Issues.code, // The code failing the requirement test - message: { // All materials describing where the issue occurred - Issues.file, - Issues.line, - Issues.column - } + message: Issues.file + Issues.line + Issues.column // All materials describing where the issue occurred } ] }, @@ -639,11 +624,7 @@ export class GoSecMapper extends BaseConverter { { results: [ { - message: { // All materials describing where the issue occurred - Issues.file, - Issues.line, - Issues.column - } + message: Issues.file + Issues.line + Issues.column // All materials describing where the issue occurred } ] }, diff --git a/src/courses/mappers/16.md b/src/courses/mappers/16.md index b36115534..6c4b6ec51 100644 --- a/src/courses/mappers/16.md +++ b/src/courses/mappers/16.md @@ -7,6 +7,82 @@ author: Charles Hu The following are some practice source data sets to create mappers with. +Before you begin, recall the steps we took previously to develop our GoSec and DBProtect mappers: + +1. Examine and break down the security data format. Remember to ask yourself the following questions while analyzing the fields of your security data: + +- What is the purpose of this field? + +- What is this field recording (i.e., metadata, requirements, requirement testing)? + +2. Correlate your security data to the OHDF schema. Focus on correlating fields from order of obvious to less obvious. + +::: details Empty OHDF Schema +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id, + title, + desc, + descriptions, + impact, + refs, + tags, + code, + source_location, + results: [ + { + status, + code_desc, + message, + run_time, + start_time + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +3. Implement your mapping using the tools and resources provided in the [previous section](./14.md). + ## JFrog Xray [Based on this mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/jfrog-xray-mapper.ts). diff --git a/src/courses/mappers/18.md b/src/courses/mappers/18.md index ab5aa4760..08e6adfaa 100644 --- a/src/courses/mappers/18.md +++ b/src/courses/mappers/18.md @@ -47,8 +47,16 @@ First, we need set up the necessary files to begin integrating your mapper with ### Integration +::: note APIs +If your security tool provides an API instead of a security data export, you will need to explore the API to determine what information may need to be collected and collated for use in the `convert` command. For further guidance, refer to [previous API-based command implementations](https://github.com/mitre/saf/tree/main/src/commands/convert) or contact the SAF team for help. +::: + With file set up out of the way, we can begin filling out the necessary files to create a `saf convert` command for our mapper. +::: info +For further guidance on writing good usage strings for command line interfaces, refer [here](http://docopt.org/). +::: + 1. Insert the skeleton convert command file (see below) in the file `{YOUR-EXPORT-NAME-HERE}2hdf.ts` which you created earlier. Replace names (`SKELETON` by default) as necessary. ::: details Skeleton Convert Command File From 2f3704a566aeef38a0490d153b06220d8d6ce78c Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Thu, 1 Aug 2024 07:17:24 -0400 Subject: [PATCH 63/71] Survey Signed-off-by: Charles Hu --- src/courses/mappers/17.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/src/courses/mappers/17.md b/src/courses/mappers/17.md index 805d205e0..42dcfd1de 100644 --- a/src/courses/mappers/17.md +++ b/src/courses/mappers/17.md @@ -7,6 +7,10 @@ author: Charles Hu ## Next Steps +### Take Our Survey + +Take our brief, anonymous [survey](https://forms.office.com/g/6JnMN8tYnD) to help improve the class. + ### Take Our Other Security Automation Framework Classes This class is part of a series of security automation content classes offered by the MITRE SAF team. If you found this content interesting and want to learn about more topics, like writing InSpec resources, we encourage you to check out the other classes provided (shown in the side bar on the left). From 6b4a6d810d43675afdf8a21f00399eabc44340f1 Mon Sep 17 00:00:00 2001 From: "Ryan Y. Lin" Date: Thu, 15 Aug 2024 11:02:11 -0700 Subject: [PATCH 64/71] Added Jfrog to mapper demo section Signed-off-by: Ryan Y. Lin --- src/courses/mappers/14.md | 439 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 439 insertions(+) diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index 16e7918e9..971f60a29 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -1677,3 +1677,442 @@ export class DBProtectMapper extends BaseConverter { ::: Now we have a fully implemented DbProtect-to-OHDF mapper. + +### Mapper Demo - JFrog + +This section is yet another example of implementing an OHDF mapper, namely the JFrog-Xray mapper. Again, we will assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. Because we have already gone through several examples, this section will not explain too many things in detail. The goal is to simply provide more examples for reference. + +Here is our developed mapping for JFrog-Xray for reference: + +::: details JFrog-to-OHDF Mapping +```typescript +{ + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id + }, + version: HeimdallToolsVersion, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'data.id', // If ID empty, hash the summary + title: 'data.summary', + desc: 'component_versions.more_details', + descriptions, + impact: 'data.severity', + refs, + tags: { + nist: 'data.component_versions.more_details.cves[0].cwe', // Map to NIST + cci: 'data.component_versions.more_details.cves[0].cwe', // Map to CCI + cweid: 'data.component_versions.more_details.cves[0].cwe' + }, + code, + source_location, + results: [ + { + status: 'Failed', // All reported findings are failures + code_desc: ['data.source_comp_id', 'data.component_versions.vulnerable_versions', 'data.component_versions.fixed_versions', 'data.issue_type', 'data.provider'], + message, + run_time, + start_time + } + ] + }, + ], + status: 'loaded' + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +::: details JFrog Source Data +```json +{ + "total_count": 30, + "data": [ + { + "id": "", + "severity": "High", + "summary": "Acorn regexp.js Regular Expression Validation UTF-16 Surrogate Handling Infinite Loop DoS", + "issue_type": "security", + "provider": "JFrog", + "component": "acorn", + "source_id": "npm://acorn", + "source_comp_id": "npm://acorn:5.7.3", + "component_versions": { + "id": "acorn", + "vulnerable_versions": [ + "5.5.0 ≤ Version < 5.7.4", + "6.0.0 ≤ Version < 6.4.1", + "7.0.0", + "7.1.0" + ], + "fixed_versions": [ + "5.7.4", + "6.4.1", + "7.1.1" + ], + "more_details": { + "cves": [ + { + "cvss_v2": "7.1/AV:N/AC:M/Au:N/C:N/I:N/A:C", + "cvss_v3": "7.5/CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H" + } + ], + "description": "Acorn contains an infinite loop condition in regexp.js that is triggered when handling UTF_16 surrogates while validating regular expressions. This may allow a context-dependent attacker to hang a process using the library.", + "provider": "JFrog" + } + }, + "edited": "2020-11-03T19:30:42-05:00" + }, + ] +} +``` +::: + +We will now go over the mapper code that allows us to shape this data properly. Firstly, let us handle the ID. Sometimes, JFrog source files will not have an ID field. In this case, it is appropriate to generate a hash based on the `summary` as follows: + +```typescript +function hashId(vulnerability: unknown): string { + if (_.get(vulnerability, 'id') === '') { + return generateHash( + (_.get(vulnerability, 'summary') as unknown as string).toString(), + 'md5' + ); + } else { + return _.get(vulnerability, 'id') as unknown as string; + } +} +``` + +As with most mappers, we must also define an impact mapping: + +```typescript +const IMPACT_MAPPING: Map = new Map([ + ['high', 0.7], + ['medium', 0.5], + ['low', 0.3] +]); +``` + +Recall that we wanted to format the `desc` field based on the data in the source file's `component_versions.more_details`. We can write a simple transformer function to concatenate all these keys: +```typescript +function formatDesc(vulnerability: unknown): string { + const text = []; + if (_.has(vulnerability, 'description')) { + text.push( + (_.get(vulnerability, 'description') as unknown as string).toString() + ); + } + if (_.has(vulnerability, 'cves')) { + const re1 = /":/gi; + const re2 = /,/gi; + text.push( + `cves: ${JSON.stringify(_.get(vulnerability, 'cves')) + .replace(re1, '"=>') + .replace(re2, ', ')}` + ); + } + return text.join('
'); +} +``` + +We also must properly handle the mappings to NIST and CCI tags. Luckily, we can make use of the library's existing mappings, as well as an existing global function called `getCCIsForNISTTags()` in `global.ts`. +```typescript +const CWE_PATH = 'component_versions.more_details.cves[0].cwe'; +const CWE_NIST_MAPPING = new CweNistMapping(); + +function nistTag(identifier: Record): string[] { + const identifiers: string[] = []; + if (Array.isArray(identifier)) { + identifier.forEach((element) => { + if (element.split('CWE-')[1]) { + identifiers.push(element.split('CWE-')[1]); + } + }); + } + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} +``` + +Finally, we can implement the transformer function for the `code_desc`. Some of these fields are optional, so it is important to implement a base case to ensure our `code_desc` outputs are all consistent. +```typescript +function formatCodeDesc(vulnerability: unknown): string { + const codeDescArray: string[] = []; + const re = /,/gi; + if (_.has(vulnerability, 'source_comp_id')) { + codeDescArray.push( + `source_comp_id : ${_.get(vulnerability, 'source_comp_id')}` + ); + } else { + codeDescArray.push('source_comp_id : '); + } + if (_.has(vulnerability, 'component_versions.vulnerable_versions')) { + codeDescArray.push( + `vulnerable_versions : ${JSON.stringify( + _.get(vulnerability, 'component_versions.vulnerable_versions') + )}` + ); + } else { + codeDescArray.push('vulnerable_versions : '); + } + if (_.has(vulnerability, 'component_versions.fixed_versions')) { + codeDescArray.push( + `fixed_versions : ${JSON.stringify( + _.get(vulnerability, 'component_versions.fixed_versions') + )}` + ); + } else { + codeDescArray.push('fixed_versions : '); + } + if (_.has(vulnerability, 'issue_type')) { + codeDescArray.push(`issue_type : ${_.get(vulnerability, 'issue_type')}`); + } else { + codeDescArray.push('issue_type : '); + } + if (_.has(vulnerability, 'provider')) { + codeDescArray.push(`provider : ${_.get(vulnerability, 'provider')}`); + } else { + codeDescArray.push('provider : '); + } + return codeDescArray.join('\n').replace(re, ', '); +} +``` + +All that's left is to incoporate all these functions into our `base-converter` structure, write some smaller transformer functions for the simpler data formatting tasks, and combine it all together! + +::: Full Mapper Code +```typescript +import {ExecJSON} from 'inspecjs'; +import * as _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import { + BaseConverter, + generateHash, + ILookupPath, + impactMapping, + MappedTransform +} from './base-converter'; +import {CweNistMapping} from './mappings/CweNistMapping'; +import { + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + getCCIsForNISTTags +} from './utils/global'; + +// Constants +const IMPACT_MAPPING: Map = new Map([ + ['high', 0.7], + ['medium', 0.5], + ['low', 0.3] +]); + +const CWE_PATH = 'component_versions.more_details.cves[0].cwe'; + +const CWE_NIST_MAPPING = new CweNistMapping(); + +// Transformation Functions +function hashId(vulnerability: unknown): string { + if (_.get(vulnerability, 'id') === '') { + return generateHash( + (_.get(vulnerability, 'summary') as unknown as string).toString(), + 'md5' + ); + } else { + return _.get(vulnerability, 'id') as unknown as string; + } +} +function formatDesc(vulnerability: unknown): string { + const text = []; + if (_.has(vulnerability, 'description')) { + text.push( + (_.get(vulnerability, 'description') as unknown as string).toString() + ); + } + if (_.has(vulnerability, 'cves')) { + const re1 = /":/gi; + const re2 = /,/gi; + text.push( + `cves: ${JSON.stringify(_.get(vulnerability, 'cves')) + .replace(re1, '"=>') + .replace(re2, ', ')}` + ); + } + return text.join('
'); +} +function formatCodeDesc(vulnerability: unknown): string { + const codeDescArray: string[] = []; + const re = /,/gi; + if (_.has(vulnerability, 'source_comp_id')) { + codeDescArray.push( + `source_comp_id : ${_.get(vulnerability, 'source_comp_id')}` + ); + } else { + codeDescArray.push('source_comp_id : '); + } + if (_.has(vulnerability, 'component_versions.vulnerable_versions')) { + codeDescArray.push( + `vulnerable_versions : ${JSON.stringify( + _.get(vulnerability, 'component_versions.vulnerable_versions') + )}` + ); + } else { + codeDescArray.push('vulnerable_versions : '); + } + if (_.has(vulnerability, 'component_versions.fixed_versions')) { + codeDescArray.push( + `fixed_versions : ${JSON.stringify( + _.get(vulnerability, 'component_versions.fixed_versions') + )}` + ); + } else { + codeDescArray.push('fixed_versions : '); + } + if (_.has(vulnerability, 'issue_type')) { + codeDescArray.push(`issue_type : ${_.get(vulnerability, 'issue_type')}`); + } else { + codeDescArray.push('issue_type : '); + } + if (_.has(vulnerability, 'provider')) { + codeDescArray.push(`provider : ${_.get(vulnerability, 'provider')}`); + } else { + codeDescArray.push('provider : '); + } + return codeDescArray.join('\n').replace(re, ', '); +} +function nistTag(identifier: Record): string[] { + const identifiers: string[] = []; + if (Array.isArray(identifier)) { + identifier.forEach((element) => { + if (element.split('CWE-')[1]) { + identifiers.push(element.split('CWE-')[1]); + } + }); + } + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} + +// Mappings +export class JfrogXrayMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: 'JFrog Xray Scan', + title: 'JFrog Xray Scan', + summary: 'Continuous Security and Universal Artifact Analysis', + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + path: 'data', + key: 'id', + tags: { + cci: { + path: CWE_PATH, + transformer: (identifier: Record) => + getCCIsForNISTTags(nistTag(identifier)) + }, + nist: { + path: CWE_PATH, + transformer: nistTag + }, + cweid: {path: CWE_PATH} + }, + refs: [], + source_location: {}, + id: {transformer: hashId}, + title: {path: 'summary'}, + desc: { + path: 'component_versions.more_details', + transformer: formatDesc + }, + impact: { + path: 'severity', + transformer: impactMapping(IMPACT_MAPPING) + }, + code: { + transformer: (vulnerability: Record): string => { + return JSON.stringify(vulnerability, null, 2); + } + }, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: {transformer: formatCodeDesc}, + start_time: '' + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [ + { + name: 'JFrog Xray', + data: _.pick(data, ['total_count']) + } + ], + ...(this.withRaw && {raw: data}) + }; + } + } + }; + constructor(xrayJson: string, withRaw = false) { + super(JSON.parse(xrayJson), true); + this.withRaw = withRaw; + } +} +``` + +::: + +Now we have a fully implemented JFrog-to-OHDF mapper. From 0a1a97a24a0ad948ac38cc08e85c6298545f01e1 Mon Sep 17 00:00:00 2001 From: "Ryan Y. Lin" Date: Thu, 15 Aug 2024 13:00:45 -0700 Subject: [PATCH 65/71] SARIF Mapper demo Signed-off-by: Ryan Y. Lin --- src/courses/mappers/14.md | 361 +++++++++++++++++++++++++++++++++++++- 1 file changed, 360 insertions(+), 1 deletion(-) diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index 971f60a29..ea45f4db5 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -1911,7 +1911,7 @@ function formatCodeDesc(vulnerability: unknown): string { All that's left is to incoporate all these functions into our `base-converter` structure, write some smaller transformer functions for the simpler data formatting tasks, and combine it all together! -::: Full Mapper Code +:::details Full Mapper Code ```typescript import {ExecJSON} from 'inspecjs'; import * as _ from 'lodash'; @@ -2116,3 +2116,362 @@ export class JfrogXrayMapper extends BaseConverter { ::: Now we have a fully implemented JFrog-to-OHDF mapper. + + +### Mapper Demo - SARIF + +Here is one last example of implementing an OHDF mapper - the SARIF mapper. As in previous examples, we will assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. Like with the JFrog example, we will not be going into too much detail regarding the mapping itself. The goal is to simply provide more examples for reference. + +Here is our developed mapping for SARIF for reference: + +::: details SARIF-to-OHDF Mapping +```typescript +{ + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id + }, + version: HeimdallToolsVersion, + statistics: { + duration + }, + profiles: [ + { + name, + version: 'version', + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'results.ruleId', // If ID empty, hash the summary + title: 'results.message.text', + desc: 'results.message.text', + descriptions, + impact: 'results.level', + refs, + tags: { + nist: 'results.message.text', // Map to NIST + cci: 'results.message.text', // Map to CCI + cwe: 'results.message.text' + }, + code, + source_location: ['results.locations[0].physicalLocation.artifactLocation.uri', 'results.locations[0].physicalLocation.region.startLine'], + results: [ + { + status: 'Failed', // All reported findings are failures + code_desc: 'results.locations[0].physicalLocation', + message, + run_time, + start_time + } + ] + }, + ], + status: 'loaded' + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` +::: + +::: details SARIF Source Data +```json +{ + "$schema": "https://schemastore.azurewebsites.net/schemas/json/sarif-2.1.0-rtm.5.json", + "version": "2.1.0", + "runs": [ + { + "results": [ + { + "ruleId": "FF1014", + "level": "error", + "message": { + "text": "buffer/gets: Does not check for buffer overflows (CWE-120, CWE-20)." + }, + "locations": [ + { + "physicalLocation": { + "artifactLocation": { + "uri": "test/test-patched.c", + "uriBaseId": "SRCROOT" + }, + "region": { + "startLine": 36, + "startColumn": 2, + "endColumn": 10, + "snippet": { + "text": " gets(f);" + } + } + } + } + ], + "fingerprints": { + "contextHash/v1": "6a5bb383fb44030b0d9428b17359e94ba3979bc1ce702be450427f85592c649a" + }, + "rank": 1 + }, + ] + } + ] +} +``` +::: + +First, let us define some common constants that might help us with our code. +```typescript +const MESSAGE_TEXT = 'message.text'; +const CWE_NIST_MAPPING = new CweNistMapping(); +``` + +We will now outline the `IMPACT_MAPPING` for the SARIF mapper: +```typescript +const IMPACT_MAPPING: Map = new Map([ + ['error', 0.7], + ['warning', 0.5], + ['note', 0.3] +]); + +function impactMapping(severity: unknown): number { + if (typeof severity === 'string' || typeof severity === 'number') { + return IMPACT_MAPPING.get(severity.toString().toLowerCase()) || 0.1; + } else { + return 0.1; + } +} +``` + +Now, note that we will need to extract the CWEs from the message text, as well as map them to the proper NIST tags. For the CCIs, we can again use the global function `getCCIsForNISTTags()`. + +```typescript +function extractCwe(text: string): string[] { + let output = text.split('(').slice(-1)[0].slice(0, -2).split(', '); + if (output.length === 1) { + output = text.split('(').slice(-1)[0].slice(0, -2).split('!/'); + } + return output; +} +function nistTag(text: string): string[] { + let identifiers = extractCwe(text); + identifiers = identifiers.map((element) => element.split('-')[1]); + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} +``` + +Our last standalone transformer function will format our code description. This part is up to interpretation, but we decided to just concatenate them all with colon-separated key-value pairs +```typescript +function formatCodeDesc(input: unknown): string { + const output = []; + output.push(`URL : ${_.get(input, 'artifactLocation.uri')}`); + output.push(`LINE : ${_.get(input, 'region.startLine')}`); + output.push(`COLUMN : ${_.get(input, 'region.startColumn')}`); + return output.join(' '); +} +``` + +Now, all that's left is to combine our functions, write some mini-transformers for the small data formatting, and plug it all into the base converter! + + +:::details Full Mapper Code +```typescript +import {ExecJSON} from 'inspecjs'; +import * as _ from 'lodash'; +import {version as HeimdallToolsVersion} from '../package.json'; +import {BaseConverter, ILookupPath, MappedTransform} from './base-converter'; +import {CweNistMapping} from './mappings/CweNistMapping'; +import { + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + getCCIsForNISTTags +} from './utils/global'; + +const IMPACT_MAPPING: Map = new Map([ + ['error', 0.7], + ['warning', 0.5], + ['note', 0.3] +]); +const MESSAGE_TEXT = 'message.text'; +const CWE_NIST_MAPPING = new CweNistMapping(); + +function extractCwe(text: string): string[] { + let output = text.split('(').slice(-1)[0].slice(0, -2).split(', '); + if (output.length === 1) { + output = text.split('(').slice(-1)[0].slice(0, -2).split('!/'); + } + return output; +} +function impactMapping(severity: unknown): number { + if (typeof severity === 'string' || typeof severity === 'number') { + return IMPACT_MAPPING.get(severity.toString().toLowerCase()) || 0.1; + } else { + return 0.1; + } +} +function formatCodeDesc(input: unknown): string { + const output = []; + output.push(`URL : ${_.get(input, 'artifactLocation.uri')}`); + output.push(`LINE : ${_.get(input, 'region.startLine')}`); + output.push(`COLUMN : ${_.get(input, 'region.startColumn')}`); + return output.join(' '); +} +function nistTag(text: string): string[] { + let identifiers = extractCwe(text); + identifiers = identifiers.map((element) => element.split('-')[1]); + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} + +export class SarifMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & {passthrough: unknown}, + ILookupPath + > = { + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id: 'Static Analysis Results Interchange Format' + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + path: 'runs', + name: 'SARIF', + version: {path: '$.version'}, + title: 'Static Analysis Results Interchange Format', + supports: [], + attributes: [], + groups: [], + status: 'loaded', + controls: [ + { + path: 'results', + key: 'id', + tags: { + cci: { + path: MESSAGE_TEXT, + transformer: (data: string) => getCCIsForNISTTags(nistTag(data)) + }, + nist: {path: MESSAGE_TEXT, transformer: nistTag}, + cwe: { + path: MESSAGE_TEXT, + transformer: extractCwe + } + }, + refs: [], + source_location: { + transformer: (control: unknown) => { + return _.omitBy( + { + ref: _.get( + control, + 'locations[0].physicalLocation.artifactLocation.uri' + ), + line: _.get( + control, + 'locations[0].physicalLocation.region.startLine' + ) + }, + (value) => value === '' + ); + } + }, + title: { + path: MESSAGE_TEXT, + transformer: (text: unknown): string => { + if (typeof text === 'string') { + return text.split(': ')[0]; + } else { + return ''; + } + } + }, + id: {path: 'ruleId'}, + desc: { + path: MESSAGE_TEXT, + transformer: (text: unknown): string => { + if (typeof text === 'string') { + return text.split(': ')[1]; + } else { + return ''; + } + } + }, + impact: {path: 'level', transformer: impactMapping}, + code: { + transformer: (vulnerability: Record): string => + JSON.stringify(vulnerability, null, 2) + }, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: { + path: 'locations[0].physicalLocation', + transformer: formatCodeDesc + }, + + start_time: '' + } + ] + } + ], + sha256: '' + } + ], + passthrough: { + transformer: (data: Record): Record => { + let runsData = _.get(data, 'runs'); + if (Array.isArray(runsData)) { + runsData = runsData.map((run: Record) => + _.omit(run, ['results']) + ); + } + return { + auxiliary_data: [ + { + name: 'SARIF', + data: { + $schema: _.get(data, '$schema'), + runs: runsData + } + } + ], + ...(this.withRaw && {raw: data}) + }; + } + } + }; + constructor(sarifJson: string, withRaw = false) { + super(JSON.parse(sarifJson)); + this.withRaw = withRaw; + } +} +``` + +::: + +Now we have a fully implemented SARIF-to-OHDF mapper. From c2aac554ff8ffd94e8b8106f7c6eddbc5b3532e4 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Tue, 20 Aug 2024 08:02:12 -0400 Subject: [PATCH 66/71] Introduction/basics of OHDF mappers rework Signed-off-by: Charles Hu --- src/.vuepress/sidebar.ts | 2 +- src/assets/img/ExampleSchemaMappings.png | Bin 1266275 -> 0 bytes src/courses/mappers/02.md | 137 ++++++++----- src/courses/mappers/03.md | 62 ++++-- src/courses/mappers/04.md | 198 ++++++++++++++++--- src/courses/mappers/05.md | 24 ++- src/courses/mappers/README.md | 12 +- src/courses/mappers/img/basic_mapping.png | Bin 0 -> 35578 bytes src/courses/mappers/img/fingerprinting.png | Bin 0 -> 56376 bytes src/courses/mappers/img/mapper_mapping.png | Bin 0 -> 56492 bytes src/courses/mappers/img/mapping.png | Bin 0 -> 24976 bytes src/courses/mappers/img/mapping_bad.png | Bin 0 -> 28158 bytes src/courses/mappers/img/scan_to_assessor.png | Bin 0 -> 22720 bytes src/courses/mappers/img/testing.png | Bin 0 -> 59102 bytes 14 files changed, 346 insertions(+), 89 deletions(-) delete mode 100644 src/assets/img/ExampleSchemaMappings.png create mode 100644 src/courses/mappers/img/basic_mapping.png create mode 100644 src/courses/mappers/img/fingerprinting.png create mode 100644 src/courses/mappers/img/mapper_mapping.png create mode 100644 src/courses/mappers/img/mapping.png create mode 100644 src/courses/mappers/img/mapping_bad.png create mode 100644 src/courses/mappers/img/scan_to_assessor.png create mode 100644 src/courses/mappers/img/testing.png diff --git a/src/.vuepress/sidebar.ts b/src/.vuepress/sidebar.ts index cf8c179a1..7f768b807 100644 --- a/src/.vuepress/sidebar.ts +++ b/src/.vuepress/sidebar.ts @@ -41,7 +41,7 @@ export default sidebar({ }, { icon: "creative", - text: "OHDF Mapper Development Class", + text: "OHDF Mapper Class", prefix: "courses/mappers/", children: "structure", collapsible: true diff --git a/src/assets/img/ExampleSchemaMappings.png b/src/assets/img/ExampleSchemaMappings.png deleted file mode 100644 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The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security data context, requirements, and measures. +The OASIS Heimdall Data Format (OHDF) is a security data format used to normalize generated data exports from various security tools into a single common data format usable by the Security Automation Framework (SAF) tool suite. The format is defined by the [OHDF schema](https://saf.mitre.org/framework/normalize/ohdf-schema) and its goal is to provide a simple and intuitive means for representing security data context, requirements, and measures. + +:::info OASIS Open +[OASIS Open](https://www.oasis-open.org/) is an international standards body that works on the development and advancement of open source technological standards. OHDF is currently in the process of becoming an OASIS Open standard. -[OASIS Open](https://www.oasis-open.org/) is an international standards body that works on the development and advancement of open source technological standards. OHDF is currently in the process of becoming an OASIS Open standard. For more information on the OHDF charter for OASIS Open, [refer here](https://groups.oasis-open.org/communities/tc-community-home2?CommunityKey=f8888caa-8401-46f8-bf10-018dc7d3f577). +For more information on the OHDF charter for OASIS Open, [refer here](https://groups.oasis-open.org/communities/tc-community-home2?CommunityKey=f8888caa-8401-46f8-bf10-018dc7d3f577). +::: OHDF's goal is to provide: - Standardization: Defining data elements in a consistent and contextualized manner. - -- Normalization: is the process for mapping a format's data elements into another format's data elements +- Normalization: Processing any format's data elements into another format's data elements in a consistent and reliable manner. ## Why OHDF? -- Many security tools do not provide context to relevant categorization standards for comparison across security tools.​ +In a field saturated with data format standards, what sets OHDF apart from the rest? Why should you use OHDF for your project? + +In the realm of cybersecurity, many security data exports suffer from a plethora of shortcomings and oversights. This creates critical issues such as: -- Security tools typically generate data in unique formats that require multiple dashboards and utilities to process.​ +- Many security tools not providing context to relevant categorization standards for comparison across security tools.​ +- Security tools typically generating data in unique formats that require multiple dashboards and utilities to process.​ +- It taking too much time to process different security data types, data in disparate locations, and inconsistent semantics of a data element between formats.​ -- OHDF reduces the time it takes to process security data types, data in disparate locations, and inconsistent semantics of a data element between formats.​ +What makes OHDF stand out is its goal of standardization and normalization, which sets out to address these aforementioned problems. OHDF aims to create a simple, reliable, and targetable security standard, culminating in a data format that bridges and unifies the many diverse and disparate representations of security data. -## Features +### Features -### 1. Consistent integration, aggregation, and analysis of security data from all available sources.​ +By using OHDF, you can leverage the plethora of built-in features that help standardize and normalize security data across your project. This includes features such as: + +#### 1. Consistent integration, aggregation, and analysis of security data from all available sources.​ - Enforces consistent schema fields through consciously designed data format mappings. - Supports data format conversion from numerous established security tools such as AWS Security Hub's AWS Security Finding Format (ASFF) and Tenable Nessus' Nessus file format. -- Allows the integration of currently unsupported security tool data formats through the development of OHDF mappers for the OHDF Converters tool. +- Allows the integration of currently unsupported security tool data formats through the development of OHDF mappers for the OHDF Converters library. -![](../../assets/img/OHDF_Inputs.png) +![OHDF can ingest and standardize a plethora of security data formats.](../../assets/img/OHDF_Inputs.png) -### 2. Preserving data integrity with original source data. +#### 2. Preserving data integrity with original source data. - Uses mappings which maximize meaningful schema field conversions. - Leverages schema fields `passthrough` and `raw` to preserve the original data in its entirety. - Allows for bidirectional format conversions to and from OHDF. -See below for an example of how *some* fields in a source file are mapped to OHDF (not all the mappings are pictured, for the sake of not cluttering the figure). - -![Example of some mappings between a source file and OHDF](../../assets/img/ExampleSchemaMappings.png) +![A mapping between Format A and OHDF.](./img/basic_mapping.png) -### 3. Maximizing interoperability and data sharing.​ +#### 3. Maximizing interoperability and data sharing.​ - Provides a consistent and standardized format for communication. - Provides an easily ingestible data format and tools to improve user readability. -### 4. Facilitating the transformation and transport of data between security/management processes or technologies.​ +#### 4. Facilitating the transformation and transport of data between security/management processes or technologies.​ - Provides a clear schema for technologies/processes to support. - Includes a simple file format that technologies/processes can accept. - Compatible with [Heimdall](./03.md#what-is-heimdall) to provide data visualization. -### 5. Allowing for the mapping and enrichment of security data to relevant compliance standards (GDPR, NIST SP 800-53, CCIs, PCI-DSS, etc.). +![OHDF can help bridge the gap between security tool outputs and security assessors.](./img/scan_to_assessor.png) -- Uses mappers which provide and append relevant categorization standards to converted security tool data. +#### 5. Allowing for the mapping and enrichment of security data to relevant compliance standards (GDPR, NIST SP 800-53, CCIs, PCI-DSS, etc.). -:::::::note What Are All These Abbreviations? +- Uses mappers which provide and append relevant categorization standards to converted security tool data. +:::::::info What Are All These Abbreviations? The aforementioned terms are all security related guidelines, frameworks, or implementations. The following are explanations on terms that are commonly used in this course: :::details NIST @@ -77,11 +94,11 @@ More information can be found [here](https://csrc.nist.gov/projects/risk-managem ::: :::::details NIST SP 800-53 Controls/Requirements -- NIST Special Publication 800-53 (**NIST SP 800-53**) "provides a catalog of security and privacy controls for information systems and organizations to protect organizational operations and assets, individuals, other organizations, and the Nation from a diverse set of threats and risks." +The NIST Special Publication 800-53 (NIST SP 800-53s) "provides a catalog of security and privacy controls for information systems and organizations to protect organizational operations and assets, individuals, other organizations, and the Nation from a diverse set of threats and risks." More information can be found [here](https://csrc.nist.gov/pubs/sp/800/53/r5/upd1/final). -- NIST SP 800-53 excerpt: +- NIST SP 800-53 control example: ``` AC-17 REMOTE ACCESS @@ -90,6 +107,7 @@ a. Establish and document usage restrictions, configuration/connection requireme implementation guidance for each type of remote access allowed; and b. Authorize each type of remote access to the system prior to allowing such connections. ``` + ::::: :::details DISA @@ -103,7 +121,7 @@ Control Correlation Identifiers (**CCIs**) are "standard identifiers and descrip More information can be found [here](https://public.cyber.mil/stigs/cci/). -- CCI excerpt: +- CCI example: ``` CCI-000002: Disseminate the organization-level; mission/business process-level; and/or system-level access control policy that addresses purpose, scope, roles, responsibilities, management commitment, coordination among organizational entities, and compliance to organization-defined personnel or roles. @@ -114,45 +132,76 @@ References: - NIST: NIST SP 800-53 Revision 5 (v5): AC-1 a 1 (a) - NIST: NIST SP 800-53A (v1): AC-1.1 (iii) ``` + ::::: ::::::: -## Benefits +### Benefits + +Depending on your role, leveraging OHDF can help streamline and improve how you interact with your project's security processes in a myriad of ways: + +- For Commercial and Vendor Cybersecurity Partners: + + - OHDF defines a standardized, interoperable target format that vendor tools can consume across their customer base consistently and that is easily managed within the product lifecycle. + +- For the Open Source Community: -- For Commercial and Vendor Cybersecurity Partners, OHDF defines a standardized, interoperable target format that vendor tools can consume across their customer base consistently and that is easily managed within the product lifecycle. + - OHDF enables easy integration with commercial solutions without the need for direct partnerships. -- For the Open Source Community, OHDF enables easy integration with commercial solutions without the need for direct partnerships. +- For Government Agencies: -- For Government Agencies, OHDF can streamline business processes by having a standard, open source, machine-readable format for all security data. + - OHDF can streamline business processes by having a standard, open source, machine-readable format for all security data. -- For Academia, OHDF offers a structured way to communicate and enhance research findings throughout the security community. +- For Academia: -- For Corporate and Federal CISOs/CIOs, OHDF can increase visibility across the enterprise by taking advantage of normalized security data in a standard format that supports risk information interoperability from a broad range of inputs to support security risk decision-making. - -- For Security Engineers, OHDF can reduce resource requirements for multiple security data types by standardizing formatting across disparate security tools. - -- For Risk Managers, OHDF can improve decision making by using a standardized format to facilitate automation, standardize communication requirements, and inform risk-based analysis. + - OHDF offers a structured way to communicate and enhance research findings throughout the security community. -- For DevSecOps/Software Engineers, OHDF can streamline CI/CD processes by leveraging a standardized format to collate/aggregate normalized security data to support automated and continuous security processes. +- For Corporate and Federal CISOs/CIOs: + + - OHDF can increase visibility across the enterprise by taking advantage of normalized security data in a standard format that supports risk information interoperability from a broad range of inputs to support security risk decision-making. + +- For Security Engineers: + + - OHDF can reduce resource requirements for multiple security data types by standardizing formatting across disparate security tools. + +- For Risk Managers: + + - OHDF can improve decision making by using a standardized format to facilitate automation, standardize communication requirements, and inform risk-based analysis. + +- For DevSecOps/Software Engineers: + + - OHDF can streamline CI/CD processes by leveraging a standardized format to collate/aggregate normalized security data to support automated and continuous security processes. ## What Else? You can read more about OHDF [here](https://saf.mitre.org/framework/normalize). -## Knowledge Check +## A Look Back -:::details What is OHDF? -OHDF is a security data format used to normalize generated data exports from various security tools into a single common data format usable by the SAF tool suite. -::: +In this section, we covered: -:::details What are some uses of OHDF? -Some uses include: +- [What OHDF is](#what-is-ohdf) -- Aggregating security data formats into a single standard format. + - OHDF is a security data format used to normalize generated data exports from various security tools into a standard common data format usable by the SAF tool suite. -- Facilitating the transformation/transport of data across different processes and technologies. +- [Why you should use OHDF](#why-ohdf) -- Enhancing security data with relevant security standards. + - OHDF provides a simple, reliable, and targetable security standard which bridges and unifies the many diverse and disparate representations of security data in the field of cybersecurity. + +- [How you can use OHDF in your work](#features) + + - OHDF provides a plethora of built-in features which help you achieve standardization and normalization of your project's security data. + +- [Who benefits from OHDF and how](#benefits) + + - OHDF can help you streamline and ease how you specifcally process and interact with security data in your project. + +### Knowledge Check + +:::details Where is OHDF used? +OHDF can be found in a plethora of projects but is officially used in the SAF tool suite. This includes tools such as Heimdall, a visualization tool for security data. +::: -- And more. +:::details How do security tool exports get converted into OHDF? +Security tool exports are converted into OHDF through the use of OHDF mappers, which convert the data elements of an export into the corresponding data elements in OHDF. ::: diff --git a/src/courses/mappers/03.md b/src/courses/mappers/03.md index c6d5f0d36..9f81e1a57 100644 --- a/src/courses/mappers/03.md +++ b/src/courses/mappers/03.md @@ -5,20 +5,28 @@ title: Where Is OHDF Used? author: Charles Hu --- +## A Look Ahead + +In this section, we will cover: + +- Where OHDF is used: + - [The Security Automation Framework](#what-is-the-security-automation-framework) + - [InspecJS](#what-is-inspecjs) + - [OHDF Converters](#what-is-ohdf-converters) + - [The SAF CLI](#what-is-the-saf-cli) + - [Heimdall](#what-is-heimdall) + ## Where Is OHDF Used? OHDF is a cornerstone of the Security Automation Framework and is officially implemented and used in a plethora of tools and libraries including InspecJS, OHDF Converters, the SAF CLI, and Heimdall. -## What Is the Security Automation Framework? +### What Is the Security Automation Framework? The Security Automation Framework (SAF) is a suite of open-source security automation tools that facilitate the development, collection, and standardization of content for use by government and industry organizations to​: - Accelerate ATO. - - Establish security requirements. - - Build security in. - - Assess/monitor vulnerabilities. SAF has five core capabilities, of which OHDF is involved in varying degrees: @@ -29,7 +37,7 @@ SAF has five core capabilities, of which OHDF is involved in varying degrees: - **Validate**: InSpec's results format is a subset of the OHDF, meaning that InSpec is natively supported. Moreover, it's easy to write InSpec such that all the guidance information is passed through into both the OHDF profile and OHDF results formats. -- **Normalize**: With the use of OHDF Converters, we are able to map many different security results formats to our standard format, OHDF. These converters can either be accessed directly or via the SAF CLI. +- **Normalize**: With the use of OHDF Converters, we are able to map many different security result formats to our standard format, OHDF. These converters can either be accessed directly or via the SAF CLI. - **Visualize**: OHDF is ingested by a variety of tools and transformed in many different ways. For example, a results file can be turned into a threshold file for pipeline use, turned into a POAM for ingestion by eMASS, or ingested by Heimdall directly for display purposes. @@ -37,24 +45,56 @@ SAF has five core capabilities, of which OHDF is involved in varying degrees: You can read more about SAF [here](../user/03.md). -## What Is InspecJS? +### What Is InspecJS? [InspecJS](https://github.com/mitre/heimdall2/tree/master/libs/inspecjs) is a library that provides schema definitions, classes, and utilities for OHDF file handling. InspecJS plays a pivotal role in the contextualization process where it performs tasks such as converting the individual statuses for each finding into an overall status for the requirement/control. -## What Is OHDF Converters? +### What Is OHDF Converters? [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) is a custom data normalization library which hosts and leverages OHDF mappers for transforming various security data formats to and from OHDF. It is currently integrated in tools such as [Heimdall](https://github.com/mitre/heimdall2) and the [SAF CLI](https://github.com/mitre/saf), which collectively are part of the [Security Automation Framework (SAF)](https://saf.mitre.org/#/), a set of tools and processes which aim to standardize and ease security testing and verification for systems such as automated build pipelines. -## What Is the SAF CLI? +### What Is the SAF CLI? The Security Automation Framework Command Line Interface (SAF CLI) brings together applications, techniques, libraries, and tools developed by MITRE and the security community to streamline security automation for systems and DevOps pipelines. -An example use case of the SAF CLI is for automating certain security processes in a CI/CD pipeline. One process would be normalizing security data into OHDF using the `saf convert` command. One can set up the SAF CLI to automatically ingest security reports generated from the build pipeline, and then forward the newly generated OHDF files to a visualization tool such as Heimdall that allows a security assessor to review the state of the current software build. +One use case for the SAF CLI is automating certain security processes in a CI/CD pipeline. For instance, you can set up the SAF CLI to automatically ingest security reports generated from the build pipeline, normalize the security data into OHDF using the `saf convert` command, and then forward the newly generated OHDF files to a visualization tool such as Heimdall that allows a security assessor to review the state of the current software build. -![SAF CLI utility overview: Attest, Convert, View, Validate, and Generate](./img/saf_cli_features.png) +![SAF CLI utility overview: Attest, Convert, View, Validate, and Generate.](./img/saf_cli_features.png) -## What Is Heimdall? +### What Is Heimdall? [Heimdall](https://github.com/mitre/heimdall2) is a visualization tool that provides a GUI-based means for managing and analyzing security data. Data that is imported into Heimdall is automatically converted to OHDF through OHDF Converters, which serves as the underlying library that services data format conversion requests in Heimdall. ![An instance of Heimdall visualizing a security result set. Results are displayed with figures, charts, and compliance level percentages to quickly convey important takeaways at a glance.](./img/heimdall_view.png) + +## A Look Back + +In this section, we covered: + +- Where OHDF is used: + + - [The Security Automation Framework](#what-is-the-security-automation-framework) + + - The Security Automation Framework is a suite of open-source security automation tools that facilitate the development, collection, and standardization of content. OHDF is an integral data format used in many of these SAF tools. + + - [InspecJS](#what-is-inspecjs) + + - InspecJS is a library that provides schema definitions, classes, and utilities for OHDF file handling. + + - [OHDF Converters](#what-is-ohdf-converters) + + - OHDF Converters is a custom data normalization library which hosts and leverages OHDF mappers for transforming various security data formats to and from OHDF. + + - [The SAF CLI](#what-is-the-saf-cli) + + - The SAF CLI provides applications, techniques, libraries, and tools for security automation in systems and DevOps pipelines. OHDF is used in SAF CLI utilities such as the `saf convert` command which allows you to convert any compatible security data format into OHDF for further use in other SAF tools. + + - [Heimdall](#what-is-heimdall) + + - Heimdall is a security data visualization tool which uses OHDF as its primary data format. + +### Knowledge Check + +:::details Where can you find OHDF mappers? +OHDF mappers can be found in the OHDF Converters library, where they are hosted. They can also be found in tools which leverage OHDF Converters such as Heimdall and the SAF CLI. +::: diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index 1fdc2ffd1..cb3f7dc35 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -5,16 +5,32 @@ title: What Is an OHDF Mapper? author: Charles Hu --- +## A Look Ahead + +In this section, we will cover: + +- [What a mapper is](#what-is-a-mapper) +- [What an OHDF mapper is](#what-is-an-ohdf-mapper) + ## What Is a Mapper? -A mapper is an example of the Adapter Design Pattern which is used to correlate (or map) items in two different objects with one another. Mappers are useful in that they allow us to correlate values in objects that are nominally different but semantically the same. A result of this is that we can easily transform one object type into another through the use of mappings which define the direct relationship of values in each object type. An important aspect of the transformation process is that while the objects containing the values are transformed, the values themselves typically remain the same. +A mapper is an example of the Adapter Design Pattern which is used to correlate (or 'map') data elements in two different objects with one another. Mappers are useful in that they allow us to correlate items in objects that are nominally different but semantically the same. A result of this is that we can easily transform one object type into another through the use of mappings which define the direct relationship of data elements in each object type. An important aspect of the transformation process is that while the data elements containing the values are transformed, the values themselves typically remain the same. + +![A correlation between data elements in Format A and Format B.](./img/mapping.png) -Mappings are the actual correlation of values between two different objects. They are the basis for mappers and are responsible for defining which values between two objects are semantically the same. Mappers are the implementation of mappings which perform the necessary processing to transform the objects according to relationships found in the mappings. In order to have a mapper that is as accurate as possible in its transformations, the mappings should ideally include correlations for all values in the objects. +Mappings are the actual correlation of data elements between two different objects. They are the basis for mappers and are responsible for defining which data elements between two objects are semantically the same. Mappers are the implementation of mappings which perform the necessary processing to transform the objects according to relationships found in the mappings. In order to have a mapper that is as accurate as possible in its transformations, the mappings should ideally include correlations for all data elements in the objects. -Here is a scenario which demonstrates some key aspects of mappers: +![A mapper converting an object from Format A to Format B using a predefined mapping.](./img/mapper_mapping.png) -::: details Transferring IDs +Oftentimes, however, we will encounter situations where the data elements between two objects either do not perfectly align or are not correlatable in a one-to-one relationship. In such scenarios, data elements can also be correlated to other data elements that are semantically similar enough and or correlated to multiple data elements that are appropriate in a one-to-many or many-to-one relationship. + +![An instance of a mapping between formats which do not perfectly align.](./img/mapping_bad.png) + +Here are some scenarios which demonstrate some key aspects of mappers: + +::: details Transferring Employee IDs Say we have a business that is changing its employee identification software and needs to transfer the current credentials of its employees from Software A to Software B. The data formats the softwares use for IDs are as follows: + ```json // Software A {Name, DoB, Age, Title} @@ -24,47 +40,177 @@ Say we have a business that is changing its employee identification software and ``` How do we transfer John's credentials from Software A to Software B? + ```json -{Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} +{ + "Name": "John Doe", + "DoB": "10-6-1992", + "Age": 32, + "Title": "Security Technician" +} ``` What we can do is create a mapping which correlates the items from Software A's ID scheme to Software B's: -```json -{employee: Name, employeeBirthday: DoB, employeeAge: Age, jobTitle: Title} -``` + +| Format A | Format B | +| ---------------- | -------- | +| employee | Name | +| employeeBirthday | DoB | +| employeeAge | Age | +| jobTitle | Title | With this, we can then develop a mapper which takes John's credentials from Software A and transforms it to Software B's format as so: + ```json -{Name: 'John Doe', DoB: 10-6-1992, Age: 32, Title: 'Security Technician'} +{ + "Name": "John Doe", + "DoB": "10-6-1992", + "Age": 32, + "Title": "Security Technician" +} +``` - || - \ / - \/ +``` + || + \ / + \/ - MAPPER + MAPPER - || - \ / - \/ + || + \ / + \/ +``` -{employee: 'John Doe', employeeBirthday: 10-6-1992, employeeAge: 32, jobTitle: 'Security Technician'} -``` +```json +{ + "employee": "John Doe", + "employeeBirthday": "10-6-1992", + "employeeAge": 32, + "jobTitle": "Security Technician" +} +``` The important thing to note here is that mappers rely on underlying mappings which match semantically similar fields between two objects. These matches allow us to correctly convert each item in one object to the other. ::: +::: details Newly Issued Licenses +The city of Gdańsk is issuing a new license for its citizens. The old and new license formats are as so: + +```json +// Old license +{name, father, mother, spouse, age, id} + +// New license +{firstName, lastName, DoB, nationalID, spouse, children} +``` + +How do we transfer Wojtek's license from the old format to the new format? + +```json +{ + "name": "Wojtek Bokiewicz", + "father": "N/A", + "mother": "Irena Bokiewicz", + "spouse": "N/A", + "age": 21, + "id": 2491 +} +``` + +Like in the previous scenario, we can create a mapping between the two formats to correlate semantically similar items. In this case, however, our formats do not perfectly align, which means that we may have multicorrelated or uncorrelated data elements. + +| Old License | New License | +| ----------- | ----------- | +| name | firstName\* | +| name | lastName\* | +| father | N/A | +| mother | N/A | +| spouse | spouse | +| age | DoB\* | +| id | nationalID | +| N/A | children | + +\*: Data element requires manipulation to apply. + +Notice that certain data elements in the new license format do not have a direct mapping back to the old license format and vice versa. This results in data loss when we convert from the old data format to the new data format where we lose possibly critical information. + +We can prevent this through data preservation, which is specifically implemented by adding new data elements to accomodate the lost ones or by adding a 'data repository' which stores all unused data elements. Data preservation in OHDF mappers will be discussed further in the next section. + +We can see this data loss when we actually apply this mapping: + +```json +{ + "name": "Wojtek Bokiewicz", + "father": "N/A", + "mother": "Irena Bokiewicz", + "spouse": "N/A", + "age": 21, + "id": 2491 +} +``` + +``` + || + \ / + \/ + + MAPPER + + || + \ / + \/ +``` + +```json +{ + "firstName": "Wojtek", + "lastName": "Bokiewicz", + "DoB": 1942, + "nationalID": 2491, + "spouse": "N/A", + "children": "" +} +``` + +Note how the information stored in the `mother` field is totally lost. + +An additional issue that may occur is empty data elements being generated by the mapper when no data is pulled over from the input data object (see `children`). There are many possible solutions for this, including pulling in the correct data from an external source, providing a default value that automatically fills out for every generated entry, or just leaving the field blank. All options are potentially valid depending on the needs of your mapper. + +Another important detail to note is how certain mappings require additional manipulations performed on the data in order to qualify the data as applicable to that data element. This can occur in both singly correlated (see `age` to `DoB`) or multicorrelated mappings (see `name` to `firstName` and `lastName`). Ideally, you should limit the amount of manipulations you perform on data unless absolutely necessary in order to preserve the integrity of your input data. If you must perform manipulations on the data, try to also preserve the original data in a backup data element or data repository. + +::: + ## What Is an OHDF Mapper? An OHDF mapper is a mapper specifically focused on transforming security data to and from OHDF. It consists of a mapping and a number of helper functions which facilitate the actual application of the mapping. In the case of the SAF tool suite, these mappers allow for the conversion of any given data format to OHDF (\*-to-OHDF) and vice versa (OHDF-to-\*) using helper functions and utilities provided by the existing conversion infrastructure in OHDF Converters. -OHDF mappers are built upon an understanding of the security data format (whether through formal schemas or on-hand export examples) and the OHDF schema, and the mechanics of the mappers revolve around correlating the fields in each as accurately as possible. +We can break down each individual OHDF mapper into three general components: -## Knowledge Check +- Fingerprinting: This component contains information on specific data elements unique to a given data format. It uses those 'fingerprints' to correctly identify the data format when encountered and pass it along to the actual mapper for transformation. -:::details Where are OHDF mappers located? -OHDF mappers are located in OHDF Converters, which hosts and leverages the mappers to provide mapping services to and from OHDF. -::: +![We can use the fingerprinting component to screen input files to determine if we should apply this mapper or not depending on whether the correct data elements are identified.](./img/fingerprinting.png) + +- Mapper: This component contains the actual mapping correlating the given data format to or from OHDF and the mapper which implements it. Mappings are built upon an understanding of the security data format (whether through formal schemas or on-hand export examples) and the OHDF schema, and the mechanics of the mapper revolve around correlating the fields in each as accurately as possible. Mappers may sometimes include preprocessing on the input file in order to ensure that the data is readable and easily usable by the mapper implementation. + +- Testing: This component consists of a testing suite which verifies the operability of the mapper and a variety of sample files that the testing suite ingests to perform those verifications. + +![Testing helps us verify that our generated outputs are correct and that future iterations of the mapper do not break key functionality.](./img/testing.png) + +## A Look Back -::: details What is the difference between a mapping and a mapper? -A mapping shows the correlation between fields, while a mapper actually implements the transformation of correlated fields. -::: \ No newline at end of file +In this section, we covered: + +- [What a mapper is](#what-is-a-mapper) + + - A mapper is a design pattern which allows us to to correlate items in objects that are nominally different but semantically the same. Mappings are the underlying correlations that define the relationship between data elements in the objects, while mappers are the actual implementation of those correlations which transforms one object into the another. + +- [What an OHDF mapper is](#what-is-an-ohdf-mapper) + + - An OHDF mapper is a mapper specifically geared towards either converting to OHDF or from OHDF and can be broken down into three general components: The fingerprinting component, the mapper component, and the testing component. + +### Knowledge Check + +:::details How does an OHDF mapper identify the correct file to normalize? +An OHDF mapper uses its fingerprinting component, which identifies data elements unique to that data format. +::: diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index de4664d41..22e432582 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -5,6 +5,17 @@ title: OHDF Schema Basics author: Charles Hu --- +## A Look Ahead + +In this section, we will cover: + +- Core structures of the OHDF schema: + - [Exec JSON](#1-exec-json) + - [Profiles](#2-profiles) + - [Controls](#3-controls) + - [Results](#4-results) +- [An overall look at the OHDF schema](#an-overview-of-the-ohdf-schema) + ## An Overview of the OHDF Schema In order to make an OHDF mapper, it is important to understand the specifics of how OHDF is actually structured through the OHDF schema. @@ -13,7 +24,7 @@ The OHDF schema is designed to provide a simple, structured, and hierarchal view ### 1. **Exec JSON** -This is the top level structure that contains both the security data (which is stored in the Profiles structure) and relevant metadata on the tool used to generate the OHDF file (stored in structures such as Platform, Statistics, and Version). +This is the top level structure that contains both the security data (which is stored in the Profiles structure) and relevant metadata on the tool used to generate the OHDF file (stored in structures such as Platform, Statistics, and Version). ### 2. **Profiles** @@ -51,3 +62,14 @@ execjson: { ] } ``` + +## A Look Back + +In this section, we will covered: + +- Core structures of the OHDF schema: + - [Exec JSON](#1-exec-json) + - [Profiles](#2-profiles) + - [Controls](#3-controls) + - [Results](#4-results) +- [An overall look at the OHDF schema](#an-overview-of-the-ohdf-schema) diff --git a/src/courses/mappers/README.md b/src/courses/mappers/README.md index f5affe813..89e5cd65a 100644 --- a/src/courses/mappers/README.md +++ b/src/courses/mappers/README.md @@ -2,6 +2,7 @@ order: 1 next: 02.md title: OHDF Mapper Development Class +shortTitle: OHDF Mapper Development author: Charles Hu --- @@ -9,7 +10,7 @@ author: Charles Hu The purpose of this class is to provide you with the foundational knowledge needed to create data format mappers for mapping data to the [OASIS Heimdall Data Format (OHDF)](https://saf.mitre.org/framework/normalize). In the following course, you will be taught the art and science of schema translation through a combination of both guided explanations and hands-on demonstrations. -The class is split into 2 sections. The first portion will introduce you to the OHDF schema and its specificities, while the second portion will show you how to apply the OHDF schema to mappers for conversions from any security data format to OHDF. +The class is split into 2 sections. The first portion will introduce you to the OHDF schema and its specificities, while the second portion will show you how to apply the OHDF schema in mappers for conversions from any security data format to OHDF (\*-to-OHDF). ### Objectives @@ -18,12 +19,11 @@ By the end of this class, you should be able to achieve the following objectives - Understand the OHDF schema and its components. - Be able to identify and break down key components of any given security tool export. - Correlate schema fields of your security data export to schema fields in OHDF. -- Create a *-to-OHDF mapper. -- Integrate your mapper with the [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) library. - - -## Mapper Examples +- Create a \*-to-OHDF mapper. +- Integrate your mapper into the [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) library and the larger Security Automation Framework (SAF) tool suite. +:::info Mapper Examples This course will use examples and code derived from previously developed OHDF mappers which can be [found here](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters). 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z|Ewze(hem=@BNXQ<-2A>{aY+oOpA2e4sq7z;v&$|Jha$!(ZVY zmgQAT8$#2Hls9vf&li?y-?gK(g_ab@dejFu4msrXoC*=JU11?!V!#Nn*J)rhF{m$u zh;~1l5$`qOU*5U6r1>Ku8L0c)^5_4L-p>3Tsy&Y5BouX9Y>yDd4Y^D-^dO?7aqW8z zibuvSYnW?HncS4Ej0_`drfxT(X{=>h?iG_=mYPVB!AwZmx4EA~&%OV_ouAGR=X}re zoaKAw`~H01ulM8;Yt4)mX>!r(j)#uuwbSkz6*mInucF&>>PF4cc1&V_WXheaY_3I2 zgH%Ib)dDYEJtp~y9=a@FQLS;+2E!hfU{jJ3w4+>8CGZ4~W0MPk0nVcZ&uRw4_y+06 zT>c6lX-^DDK!iR7R<<&NB0j2inqsLIwB(JNkU`G9QJYVSP;`-qqw8@s^8 z{wvsbi;Qya#W7J6{{*zrk%{T;iN*n`hhswPqOP3P(84&1m)aFdg%wcrFl0t!H|?wS zCv&xu@fIcPeYXZr>RV))V*TC^FO2G|W0J9hi;SOy+l^c0xwd$vFjHSlzk!P6huUt3 z@(k%h>WzKfe;(o~1%n$2cT+^Yr32QL5qbNW82NWiY0tBJ8RGG_x#%!@(~ z^PiOC3Cp;9f>aT3!NOLMge6{iWo20m%NQEys#bV0kFE~Na>-6>x_bdLhQf|cJi2Gt zLX&l{Xfk{$qdRCf(mZW#BmuAkS=BG?%GS_N4rgzjQ7gwuSU8}k5Sch)qkJtn=N~; zkvbNw8bYKO6BCeh-khs`=N4bPZs|lmwP>1?DOLV-TlL3GEEbD2Qz1R`El6bwNQU5= z0{>hem@2-1Lo#KJ>y#5k#qM?QIW@RzR=9VE>Bh3~UL!@qKuyK2y25WYM6IOmrDUQt zmwM~K?dEU-TgIrDKUC&3z{E$5qxiHjOJ-Vb!tQ7{sSj$Bzf|Vo3BnYv^k}|ZPo+(w z20Oi`L&a^O(KdTb87PW1MG|=P zf75vP`{z>}X3~?YKj0sn=v*EHl#(w3(wrNJKKI!3#ir%4FWtb|MlMq~$;rdeXL_h% z5rxZ}Xea97vhk>*yIs*g3+-|JV>zhS!`F~}d_bssxt8-IZERihuLwLY8KZx?WVTvoJg>yj)~U!OKF;apt$+M3|$2|SzL34yK~j>z@nW1S^SX1P7hjH)Us z0*--_fu9+4j2*G0Xz3DkE7g&`(6!eS(7+5#I>U^MT~ie(oZhBr+`rCM`}*<4oHVkJ zUx-xdO%5Jp*;WWhrSj>{;;YMY5#Lx6R+g5@piYH?qbQfZRL=KZn=Vt$iA9Z66~Bzt8%&c&O|8^W^UH227$=M0di$4C4O}&XDV*gaBi=_bA%w#TMi!7>j(JXkh>V literal 0 HcmV?d00001 From 291bb74a7e9c1dc132bb30d5b6ecbc330f65b4f6 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Wed, 21 Aug 2024 15:38:00 -0400 Subject: [PATCH 67/71] OHDF schema section rework Signed-off-by: Charles Hu --- src/courses/mappers/04.md | 6 +- src/courses/mappers/05.md | 336 ++++++++++++++++++--- src/courses/mappers/06.md | 610 +++++++++++++++++++++++++++++++------- src/courses/mappers/07.md | 375 ++++++++++++++--------- src/courses/mappers/08.md | 288 ------------------ 5 files changed, 1034 insertions(+), 581 deletions(-) delete mode 100644 src/courses/mappers/08.md diff --git a/src/courses/mappers/04.md b/src/courses/mappers/04.md index cb3f7dc35..78f808633 100644 --- a/src/courses/mappers/04.md +++ b/src/courses/mappers/04.md @@ -187,13 +187,13 @@ An OHDF mapper is a mapper specifically focused on transforming security data to We can break down each individual OHDF mapper into three general components: -- Fingerprinting: This component contains information on specific data elements unique to a given data format. It uses those 'fingerprints' to correctly identify the data format when encountered and pass it along to the actual mapper for transformation. +- **Fingerprinting**: This component contains information on specific data elements unique to a given data format. It uses those 'fingerprints' to correctly identify the data format when encountered and pass it along to the actual mapper for transformation. ![We can use the fingerprinting component to screen input files to determine if we should apply this mapper or not depending on whether the correct data elements are identified.](./img/fingerprinting.png) -- Mapper: This component contains the actual mapping correlating the given data format to or from OHDF and the mapper which implements it. Mappings are built upon an understanding of the security data format (whether through formal schemas or on-hand export examples) and the OHDF schema, and the mechanics of the mapper revolve around correlating the fields in each as accurately as possible. Mappers may sometimes include preprocessing on the input file in order to ensure that the data is readable and easily usable by the mapper implementation. +- **Mapper**: This component contains the actual mapping correlating the given data format to or from OHDF and the mapper which implements it. Mappings are built upon an understanding of the security data format (whether through formal schemas or on-hand export examples) and the OHDF schema, and the mechanics of the mapper revolve around correlating the fields in each as accurately as possible. Mappers may sometimes include preprocessing on the input file in order to ensure that the data is readable and easily usable by the mapper implementation. -- Testing: This component consists of a testing suite which verifies the operability of the mapper and a variety of sample files that the testing suite ingests to perform those verifications. +- **Testing**: This component consists of a testing suite which verifies the operability of the mapper and a variety of sample files that the testing suite ingests to perform those verifications. ![Testing helps us verify that our generated outputs are correct and that future iterations of the mapper do not break key functionality.](./img/testing.png) diff --git a/src/courses/mappers/05.md b/src/courses/mappers/05.md index 22e432582..27e040282 100644 --- a/src/courses/mappers/05.md +++ b/src/courses/mappers/05.md @@ -9,67 +9,335 @@ author: Charles Hu In this section, we will cover: -- Core structures of the OHDF schema: - - [Exec JSON](#1-exec-json) - - [Profiles](#2-profiles) - - [Controls](#3-controls) - - [Results](#4-results) -- [An overall look at the OHDF schema](#an-overview-of-the-ohdf-schema) +- [Core structures of the OHDF schema:](#an-overview-of-the-ohdf-schema) + - Exec JSON + - Profiles + - Controls + - Results +- [A look at the overall OHDF schema hierarchy](#overall-hierarchy) ## An Overview of the OHDF Schema In order to make an OHDF mapper, it is important to understand the specifics of how OHDF is actually structured through the OHDF schema. -The OHDF schema is designed to provide a simple, structured, and hierarchal view of security tool results. OHDF actually consists of several related schema formats; however, the Exec JSON format is the most common and is typically the one being referred to when speaking of the OHDF schema. Any file or object that implements the schema can be broken down into a hierarchy of four main structures. These structures are: +The OHDF schema is designed to provide a simple, structured, and hierarchal view of security tool results. OHDF actually consists of several related schema formats; however, the Exec JSON format is the most common and is typically the one being referred to when speaking of the OHDF schema. Any file or object that implements the schema can be broken down into a hierarchy of four main object structures. These structures are: ### 1. **Exec JSON** -This is the top level structure that contains both the security data (which is stored in the Profiles structure) and relevant metadata on the tool used to generate the OHDF file (stored in structures such as Platform, Statistics, and Version). +This is the top level object structure that contains the security data (which is stored in the Profiles structure and related substructures), relevant metadata on the tool used to generate the OHDF file itself (stored in structures such as Platform, Version, and Statistics), and miscellaneous information that does not neatly fit in the previous structures (stored in the Passthrough structure). + +Before we discuss the Profiles structure and its related substructures, here is a brief introduction to the latter object structures contained by the Exec JSON superstructure: + +- **Platform**: This structure contains metadata involving the platform or tool that is producing the OHDF file. + +- **Version**: This structure contains metadata involving the version of the platform or tool that is producing the OHDF file. + +- **Statistics**: This structure contains metadata involving the specific statistics of the original run that produced the export. + +- **Passthrough**: The primary purpose of the Passthrough structure is to contain and transport any piece of information that cannot be properly stored in the other Exec JSON substructures. Unlike other object structures in the OHDF schema, there is no formal schema declaration for the specific fields that exist in Passthrough. This means that Passthrough is fluid and capable of accommodating user-defined object fields as needed. There are, however, commonly agreed upon fields for specific capabilities, such as data preservation, that are discussed further in the next section. + +A basic representation of this structure in JSON is as so: + +```json +{ + execjson: { + platform: {...}, + version: ..., + statistics: {...}, + profiles: [...], + passthrough: {...} + } +} +``` ### 2. **Profiles** -This structure contains metadata on the target system of the original security tool export and on the specific run performed by the security tool. Profiles provide a high-level overview of the security tool result and the targeted system, which are formatted in a manner which is digestible and immediately accessible to the assessor. There is typically only one profiles structure. Further instances of profiles are additional overlays. +This structure contains metadata on the target system of the original security tool export and on the specific run performed by the security tool. Through this, the Profiles structure provides a high-level overview of the security tool result and the targeted system, which are formatted in a manner that is digestible and immediately accessible to the assessor. There is typically only one Profiles instance in a single Exec JSON structure (represented as a single element in an array of Profiles). Further instances of Profiles are additional overlays. + +A basic representation of this structure in JSON is as so: + +```json +{ + execjson: { + profiles: [...], + ... + } +} +``` ### 3. **Controls** -Controls are security requirements that are used to prevent, mitigate, and address various security risks to sensitive information and infrastructure. In the case of OHDF, the controls structure is a collection of requirements tested for by an external security tool to ensure that the target complies with vulnerability and weakness prevention standards. Any given profile contains some number of controls which were tested against the target system during the original security tool run. +Controls are security requirements that are used to prevent, mitigate, and address various security risks to sensitive information, systems, and infrastructure. In the case of OHDF, the Controls structure is a collection of requirements tested for by an external security tool to ensure that the target complies with vulnerability and weakness prevention standards. Any given Profiles structure contains some number of Controls structures (i.e., an array of Controls) which were tested against the target system during the original security tool run. + +A basic representation of this structure in JSON is as so: + +```json +{ + profiles: [ + { + controls: [...], + ... + }, + ... + ], + ... +} +``` ### 4. **Results** -The results structure contains information on the results of specific tests ran by the security tool on the target system against a security requirement/control. These results will always correlate to a certain control and will either report `passed` or `failed` to indicate the test status (other statuses include `skipped` and `error`) which cumulatively influence the determined compliance level of the target system for some set of requirements/controls. Any given control contains some number of results which reflect the implemented tests to check if the target system is actually meeting the overall requirement/control. +The Results structure contains information on the results of specific tests ran by the security tool on the target system against a single security requirement/control. These results will always correlate to a certain instance of a Controls structure and can report either `passed`, `failed`, `skipped`, or `error` to indicate the test status. Any given Controls structure contains some number of Results structures (i.e., an array of Results) which reflect the implemented tests to check if the target system is actually meeting the overall requirement/control. The test statuses of these results cumulatively influence the determined compliance level of the target system for some set of requirements/controls. + +A basic representation of this structure in JSON is as so: + +```json +{ + controls: [ + { + results: [...], + ... + }, + ... + ], + ... +} +``` ## Overall Hierarchy -These aforementioned main structures cumulatively result in the following generalized structure: +These aforementioned main object structures cumulatively result in the following general structure: ```json -// Data fields have been removed for the sake of demonstration -execjson: { - profiles: [ - 0: { - controls: [ - 0: { - results: [ - 0: { - }, +{ + execjson: { + platform: {...}, + version: ..., + statistics: {...}, + profiles: [ + { + controls: [ + { + results: [...], ... - ] - }, + }, + ... + ], ... - ] - }, - ... - ] + }, + ... + ], + passthrough: {...} + } } ``` ## A Look Back -In this section, we will covered: +In this section, we covered: + +- [Core structures of the OHDF schema:](#an-overview-of-the-ohdf-schema) + + - Exec JSON + + - This is the top level object structure that acts as a container for all of the other object structures that are specialized for specific sets of information. + + - Profiles + + - This structure is for containing high-level metadata on the security tool run. + + - Controls + + - This structure is for containing information pertaining to the set of controls/requirements that were ran against the target system in the original security tool run. + + - Results + + - This structure is for containing information pertaining to the specific test results of the application of the control/requirement set against the target system. + +- [A look at the overall OHDF schema hierarchy](#overall-hierarchy) + +### Knowledge Check + +:::details Describe the relationship between Profiles, Controls, and Results. + +The Profiles object structure contains one or more Controls structures (represented as a `controls` array within a `profiles` element). + +The Controls object structure contains one or more Results structures (represented as a `results` array within a `controls` element). +::: + +:::details Say that we map from Format A to OHDF and have data elements left over in Format A that are still uncorrelated. What do we do with those data elements? +We perform data preservation and place the uncorrelated data elements from Format A into the Passthrough structure in OHDF (the explicit field to use will be defined later). +::: + +### Knowledge Review + +Now that we're familiar with the general layout of an OHDF file, let's briefly look at an actual OHDF file generated from a Twistlock security scan export. This OHDF file in particular was created through the OHDF Converters library embedded in the Heimdall visualizer. + +Since we have not yet gone over the specific OHDF schema fields, try to focus on the actual information being stored by file instead and ask yourself: + +- What is the purpose of this specific piece of data? What is it trying to convey (file metadata, vulnerability alerts, check results, etc.)? + +- Does this piece of data fit in with the general purpose of the structure that contains it? + +- Would this piece of data fit better in another structure? + +:::note Twistlock-to-OHDF Sample +This file has been truncated for pedagogical purposes. For the full file, see [here](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/sample_jsons/twistlock_mapper/twistlock-hdf.json) +::: + +:::details Twistlock-to-OHDF Sample + +```json +{ + "platform": { + "name": "Heimdall Tools", + "release": "2.6.29", + "target_id": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a" + }, + "version": "2.6.29", + "statistics": {}, + "profiles": [ + { + "name": "Twistlock Scan", + "title": "Twistlock Project: All / TEST-COLLECTION", + "summary": "Package Vulnerability Summary: 97 Application Compliance Issue Total: 0", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "controls": [ + { + "tags": { + "nist": ["SI-2", "RA-5"], + "cci": ["CCI-002605", "CCI-001643"], + "cveid": "CVE-2021-43529" + }, + "refs": [], + "source_location": {}, + "title": "CVE-2021-43529", + "id": "CVE-2021-43529", + "desc": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "impact": 0.9, + "code": "{\n \"id\": \"CVE-2021-43529\",\n \"status\": \"affected\",\n \"cvss\": 9.8,\n \"description\": \"DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec\",\n \"severity\": \"critical\",\n \"packageName\": \"nss-util\",\n \"packageVersion\": \"3.67.0-7.el8_5\",\n \"link\": \"https://access.redhat.com/security/cve/CVE-2021-43529\",\n \"riskFactors\": [\n \"Remote execution\",\n \"Attack complexity: low\",\n \"Attack vector: network\",\n \"Critical severity\",\n \"Recent vulnerability\"\n ],\n \"impactedVersions\": [\n \"*\"\n ],\n \"publishedDate\": \"2021-12-01T00:00:00Z\",\n \"discoveredDate\": \"2022-05-18T12:24:22Z\",\n \"layerTime\": \"2022-05-16T23:12:25Z\"\n}", + "results": [ + { + "status": "failed", + "code_desc": "Package \"nss-util\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-util\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-util\"", + "start_time": "2022-05-18T12:24:22Z" + }, + { + "status": "failed", + "code_desc": "Package \"nss-sysinit\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-sysinit\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-sysinit\"", + "start_time": "2022-05-18T12:24:22Z" + }, + { + "status": "failed", + "code_desc": "Package \"nss\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss\"", + "start_time": "2022-05-18T12:24:22Z" + }, + { + "status": "failed", + "code_desc": "Package \"nss-softokn\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-softokn\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-softokn\"", + "start_time": "2022-05-18T12:24:22Z" + }, + { + "status": "failed", + "code_desc": "Package \"nss-softokn-freebl\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-softokn-freebl\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-softokn-freebl\"", + "start_time": "2022-05-18T12:24:22Z" + } + ] + } + ], + "sha256": "807c8ef1534bb7f3e428db4a40667a6dd37d89f8a48dc6d1f6bb2426ff53f97f" + } + ], + "passthrough": { + "auxiliary_data": [ + { + "name": "Twistlock", + "data": { + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + }, + { + "type": "os", + "name": "nss-softokn", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + }, + { + "type": "os", + "name": "nss", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + }, + { + "type": "os", + "name": "nss-softokn-freebl", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + }, + { + "type": "os", + "name": "nss-sysinit", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } + ], + "applications": [ + { + "name": "asp.net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + }, + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceScanPassed": true, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-03T08:38:31Z" + }, + { + "created": "2022-05-03T08:39:27Z" + }, + { + "created": "2022-05-16T23:12:02Z", + "instruction": "ARG GOPROXY=http://nexus-repository-manager.nexus-repository-manager.svc.cluster.local:8081/repository/goproxy/ HTTP_PROXY=http://localhost:3128 http_proxy=http://localhost:3128" + }, + { + "created": "2022-05-16T23:12:02Z", + "instruction": "ARG GOPROXY=http://nexus-repository-manager.nexus-repository-manager.svc.cluster.local:8081/repository/goproxy/ GOSUMDB=sum.golang.org http://nexus-repository-manager.nexus-repository-manager.svc.cluster.local:8081/repository/gosum HTTP_PROXY=http://localhost:3128 http_proxy=http://localhost:3128" + } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" + } + } + ] + } +} +``` -- Core structures of the OHDF schema: - - [Exec JSON](#1-exec-json) - - [Profiles](#2-profiles) - - [Controls](#3-controls) - - [Results](#4-results) -- [An overall look at the OHDF schema](#an-overview-of-the-ohdf-schema) +::: diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index 2c604f471..3ed2d36c7 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -5,57 +5,176 @@ title: Formal OHDF Schema Definition author: Charles Hu --- +## A Look Ahead + +In this section, we will cover: + +- [Background context for technical aspects of the OHDF schema](#background) +- [A breakdown of the OHDF schema](#breaking-down-the-formal-ohdf-schema): + - [Exec JSON](#exec-json) + - [Platform](#platform) + - [Statistics](#statistics) + - [Passthrough](#passthrough) + - [Profiles](#profiles) + - [Controls](#controls) + - [Results](#results) + +## Background + +The OHDF schema is a JSON-based schema that uses typed values. This means that any given OHDF file must be formatted in JSON and the typing of each key-value pair in the JSON object must conform to its declared type in the OHDF schema. Nonconformance to these rules will result in an OHDF output that is incompatible with compliant OHDF-based functionality and will produce undefined and erroneous behavior. + +### Unused Fields + +:::info Required Fields +A required field in OHDF is a schema field that must always exist in the file to qualify the file as conforming to the OHDF schema. If a field is required by the OHDF schema, it does not necessarily mean that you have to provide it with meaningful data or correlate it with a data element from another source format. A file can still conform to OHDF by having a required field that has an empty value assigned to it. +::: + +Not all fields in the schema have to be filled or even used in an OHDF mapper. In practice, most implementations either provide an empty value (e.g, an empty string, an empty object, etc.) or omit an unused field entirely (i.e., by not defining the key or by passing a value of `undefined`). Whether or not you should provide an empty value or omit the key for an unused field depends on if the field is declared as required by the OHDF schema. If you have an unused field that is declared as required by the schema, you must define the key and pass it an empty value. If the unused field is not declared as required, you can safely omit the field. + +:::note Omitting Schema Fields +Just because you can omit a schema field does not mean that you should! + +Always aim to maximize the filled fields in your mapper and only skip a field as a last resort if no applicable equivalent exists in your source data. Consider required fields as priority fields that you should aim to fill out first instead of the bare minimum necessary to create a mapper. +::: + +For example, the following required key-value pairs are all considered valid: + +```json +{ + "platform": { + "name": "" + } +} +``` + +```json +{ + "profiles": [ + { + "supports": [] + } + ] +} +``` + +Here is a snippet from the previous Twistlock-to-OHDF sample file which shows some empty required fields: + +:::details Twistlock-to-OHDF Sample + +```json +{ + "statistics": {}, + "profiles": [ + { + "name": "Twistlock Scan", + "title": "Twistlock Project: All / TEST-COLLECTION", + "summary": "Package Vulnerability Summary: 97 Application Compliance Issue Total: 0", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "sha256": "807c8ef1534bb7f3e428db4a40667a6dd37d89f8a48dc6d1f6bb2426ff53f97f" + } + ] +} +``` + +::: + ## Breaking Down the Formal OHDF Schema We can break down the formal OHDF schema in the same manner as before by observing each structure in the hierarchy from a top-down view. ::: note Full OHDF Schema -The following section contains a breakdown of a streamlined version of the OHDF schema. For the full and up-to-date version, see [here](https://saf.mitre.org/framework/normalize/ohdf-schema). Visit [here](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts) for the technical implementation of the schema. -::: +The following section contains a breakdown of a streamlined version of the OHDF schema. + +For the full and up-to-date version, see [here](https://saf.mitre.org/framework/normalize/ohdf-schema). -:::note Required Fields -Not all fields are required. This will be expanded upon in the next section. +For the technical implementation of the schema, see [here](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts). ::: -### 1. Exec JSON - -Field Name | Definition --|- -`platform` | Platform substructure (see `Additional Structures`). -`profiles` | Profiles substructure (see below). -`statistics` | Statistics substructure (see below). -`version` | Version of tool generating the file. - -### 2. **Profiles** - -Field Name | Definition --|- -`name` | Name of profile, usually the original security tool; must be unique. -`version` | Version of security tool. -`sha256` | Checksum of the profile (NOTE: AUTOMATICALLY GENERATED BY HDF CONVERTERS, DO NOT POPULATE). -`title` | Title of security tool; must be human readable. -`maintainer` | Maintainer(s). -`summary` | Summary of security data (e.g., the STIG header). -`license` | Copyright license. -`copyright` | Copyright holder. -`copyright_email` | Copyright holder's email. -`supports` | Supported platform targets. -`attributes` | Inputs/attributes used in scan. -`groups` | Set of descriptions for the control groups (e.g., control IDs). -`controls` | Controls substructure (see below). -`status` | Status of profile (typically 'loaded'). -`status_message` | Reason for the status. -`skip_message` | Reason for skipping this profile if skipped. -`depends` | Set of dependencies this profile depends on (e.g., an overlay profile is dependent on another profile). -`parent_profile` | Name of the parent profile if this profile is a dependency of another profile. -`description` | Description of profile; should be more detailed than summary. -`inspec_version` | The version of the Inspec tool used to generate this profile. +### **Exec JSON** + +| Field Name | Definition | Type | Required | +| ------------- | ---------------------------------------------------------------------------- | ------------------------- | -------- | +| `platform` | Platform substructure (see [**Platform**](#platform)). | `Platform` | Yes | +| `version` | Version of tool generating the file. | `string` | Yes | +| `statistics` | Statistics substructure (see [**Statistics**](#statistics)). | `Statistics` | Yes | +| `profiles` | Profiles substructure (see [**Profiles**](#profiles)). | `ExecJSONProfile[]` | Yes | +| `passthrough` | Passthrough substructure (see [**Passthrough**](#passthrough)) | `Record` | No | + +A basic representation of this structure in JSON is as so: + +```json +{ + "platform": {}, + "version": "", + "statistics": {}, + "profiles": [], + "passthrough": {} +} +``` + +### **Profiles** + +| Field Name | Definition | Type | Required | +| ----------------- | ------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------ | -------- | +| `name` | Name of profile, usually the original security tool. Must be unique. | `string` | Yes | +| `version` | Version of security tool. | `string`, `null` | No | +| `sha256` | Checksum of the profile (NOTE: AUTOMATICALLY GENERATED BY HDF CONVERTERS, DO NOT POPULATE). | `string` | Yes | +| `title` | Title of security tool; must be human readable. | `string`, `null` | No | +| `maintainer` | Maintainer(s). | `string`, `null` | No | +| `summary` | Summary of security data (e.g., the STIG header). | `string`, `null` | No | +| `license` | Copyright license. | `string`, `null` | No | +| `copyright` | Copyright holder. | `string`, `null` | No | +| `copyright_email` | Copyright holder's email. | `string`, `null` | No | +| `supports` | Supported platform targets. | [`SupportedPlatform[]`](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts#L396) | Yes | +| `attributes` | Inputs/attributes used in scan. | `Record[]` | Yes | +| `groups` | Set of descriptions for the control groups (e.g., control IDs). | [`ControlGroup[]`](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts#L377) | Yes | +| `controls` | Controls substructure (see [**Controls**](#controls)). | `ExecJSONControl[]` | Yes | +| `status` | Status of profile (typically 'loaded'). | `string`, `null` | No | +| `status_message` | Reason for the status. | `string`, `null` | No | +| `skip_message` | Reason for skipping this profile if skipped. | `string`, `null` | No | +| `depends` | Set of dependencies this profile depends on (e.g., an overlay profile is dependent on another profile). | [`Dependency[]`](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts#L334), `null` | No | +| `parent_profile` | Name of the parent profile if this profile is a dependency of another profile. | `string`, `null` | No | +| `description` | Description of profile; should be more detailed than summary. | `string`, `null` | No | +| `inspec_version` | The version of the Inspec tool used to generate this profile. | `string`, `null` | No | + +A basic representation of this structure in JSON is as so: + +```json +{ + "name": "", + "version": "", + "sha256": "", + "title": "", + "maintainer": "", + "summary": "", + "license": "", + "copyright": "", + "copyright_email": "", + "supports": [], + "attributes": [], + "groups": [], + "controls": [], + "status": "", + "status_message": "", + "skip_message": "", + "depends": [], + "parent_profile": "", + "description": "", + "inspec_version": "" +} +``` #### Knowledge Check -Given a snippet of GoSec data, try and identify what information is applicable to the **Profiles** structure and which field they would correlate with. +Given a snippet of data, try and identify what information is applicable to the Profiles structure and which fields they would correlate with. + +- Data snippet: + +:::details GoSec Source Data -::: details GoSec Source Data ```json { "Golang errors": {}, @@ -86,9 +205,13 @@ Given a snippet of GoSec data, try and identify what information is applicable t "GosecVersion": "dev" } ``` + ::: -::: details OHDF Converted GoSec Data +- Converted OHDF snippet (may not perfectly align with your answers): + +:::details OHDF Converted GoSec Data + ```json "profiles": [ { @@ -106,29 +229,53 @@ Given a snippet of GoSec data, try and identify what information is applicable t } ] ``` + ::: -### 3. **Controls** -Field Name | Definition --|- -`id` | ID of control, used for sorting. Must be unique. -`title` | Title of control. -`desc` | The overarching description of the control. -`descriptions` | Additional descriptions; usually 'check' and 'fix' text for control. -`impact` | Security severity of control. On a scale of 0 to 1. This metric is aligned with the [Common Vulnerability Scoring System (CVSS)](https://www.first.org/cvss/). -`refs` | References to external control documentation. -`tags` | Control tags; typically correlate to existing vulnerability/weakness database (e.g., NIST, CVE, CWE). -`code` | Control source code for code preservation. -`source_location` | Location of control within source code. -`results` | Results substructure (see below). -`waiver_data` | Information on waiver if applicable. -`attestation_data` | Information on attestation if applicable. +### **Controls** + +| Field Name | Definition | Type | Required | +| ------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- | -------- | +| `id` | ID of control, used for sorting. Must be unique. | `string` | Yes | +| `title` | Title of control. | `string`, `null` | No | +| `desc` | The overarching description of the control. | `string`, `null` | No | +| `descriptions` | Additional descriptions; usually 'check' and 'fix' text for control. | [`ControlDescription[]`](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts#L224), `null` | No | +| `impact` | Security severity of control. On a scale of 0 to 1 and typically increments by 0.1 values. This metric is aligned with the [Common Vulnerability Scoring System (CVSS)](https://www.first.org/cvss/). | `number` | Yes | +| `refs` | References to external control documentation. | [`Reference[]`](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts#L244) | Yes | +| `tags` | Control tags; typically correlate to existing vulnerability/weakness database (e.g., NIST, CVE, CWE). | `Record` | Yes | +| `code` | Control source code for code preservation. | `string`, `null` | No | +| `source_location` | Location of control within source code. | [`SourceLocation`](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts#L311) | Yes | +| `results` | Results substructure (see [**Results**](#results)). | `ControlResult[]` | Yes | +| `waiver_data` | Information on waiver if applicable. | [`WaiverData`](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts#L322), `null` | No | +| `attestation_data` | Information on attestation if applicable. | [`AttestationData`](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts#L204), `null` | No | + +A basic representation of this structure in JSON is as so: + +```json +{ + "id": "", + "title": "", + "desc": "", + "descriptions": [], + "impact": 0, + "refs": [], + "tags": {}, + "code": "", + "source_location": {}, + "results": [], + "waiver_data": {}, + "attestation_data": {} +} +``` #### Knowledge Check -Given a snippet of GoSec data, try and identify what information is applicable to the **Controls** structure and which field they would correlate with. +Given a snippet of data, try and identify what information is applicable to the Controls structure and which fields they would correlate with. + +- Data snippet: + +:::details GoSec Source Data -::: details GoSec Source Data ```json { "Golang errors": {}, @@ -159,9 +306,13 @@ Given a snippet of GoSec data, try and identify what information is applicable t "GosecVersion": "dev" } ``` + ::: -::: details OHDF Converted GoSec Data +- Converted OHDF snippet (may not perfectly align with your answers): + +:::details OHDF Converted GoSec Data + ```json "controls": [ { @@ -188,28 +339,49 @@ Given a snippet of GoSec data, try and identify what information is applicable t } ], ``` + ::: -### 4. **Results** - -Field Name | Definition --|- -`status` | `passed`/`failed` status of test (other status include `skipped` and `error`). -`skip_message` | Reasoning for if test has `skipped` status. -`code_desc` | Test expectations as defined by control. -`exception` | Type of exception if one was thrown. -`backtrace` | Backtrace of exception if one was thrown. -`message` | Explanation of test status; typically in the form of expected and actual results. -`resource` | Resources used in the test (e.g., Inspec). -`resource_id` | The unique ID of the used resources. -`run_time` | Overall runtime of test. -`start_time` | Starting time of test. +### **Results** -#### Knowledge Check +| Field Name | Definition | Type | Required | +| -------------- | --------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- | -------- | +| `status` | `passed`/`failed` status of test (other status include `skipped` and `error`). | [`ControlResultStatus`](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts#L299), `null` | No | +| `skip_message` | Reasoning for if test has `skipped` status. | `string`, `null` | No | +| `code_desc` | Test expectations as defined by control. | `string` | Yes | +| `exception` | Type of exception if one was thrown. | `string`, `null` | No | +| `backtrace` | Backtrace of exception if one was thrown. | `string[]`, `null` | No | +| `message` | Explanation of test status; typically in the form of expected and actual results. | `string`, `null` | No | +| `resource` | Resources used in the test (e.g., Inspec). | `string`, `null` | No | +| `resource_id` | The unique ID of the used resources. | `string`, `null` | No | +| `run_time` | Overall runtime of test. | `number`, `null` | No | +| `start_time` | Starting time of test. | `string` | Yes | + +A basic representation of this structure in JSON is as so: + +```json +{ + "status": {}, + "skip_message": "", + "code_desc": "", + "exception": "", + "backtrace": [], + "message": "", + "resource": "", + "resource_id": "", + "run_time": 0, + "start_time": "" +} +``` + +#### Knowledge Review + +Given a snippet of data, try and identify what information is applicable to the Results structure and which fields they would correlate with. -Given a snippet of GoSec data, try and identify what information is applicable to the **Results** structure and which field they would correlate with. +- Data snippet: + +:::details GoSec Source Data -::: details GoSec Source Data ```json { "Golang errors": {}, @@ -240,9 +412,13 @@ Given a snippet of GoSec data, try and identify what information is applicable t "GosecVersion": "dev" } ``` + ::: -::: details OHDF Converted GoSec Data +- Converted OHDF snippet (may not perfectly align with your answers): + +:::details OHDF Converted GoSec Data + ```json "results": [ { @@ -253,33 +429,76 @@ Given a snippet of GoSec data, try and identify what information is applicable t } ] ``` + ::: -### 5. Additional Structures - -There are additional structures in the OHDF schema which are used for metadata/extraneous information storage. These exist alongside the profiles structure on the top level of the HDF schema. The general structure for the top level of the HDF schema is as follows: - -Field Name | Definition --|- -`platform` | Information on the platform producing the export. -`platform.name` | Name of platform export was run on. -`platform.release` | Platform version. -`platform.target_id` | Platform target ID (i.e., further identifying information on platform). -`statistics` | Statistics relating to target scan run. -`statistics.controls` | Break down of control statistics by result status. -`statistics.duration` | Duration of run (in seconds). -`profiles` | Profiles structure. -`passthrough` | Extraneous information storage. -`passthrough.auxiliary_data` | Storage for unused data from the sample file. -`passthrough.auxiliary_data.name` | Name of auxiliary data source. -`passthrough.auxiliary_data.data` | Auxiliary data. -`passthrough.raw` | Raw data dump of input security service export. +### **Platform** + +| Field Name | Definition | Type | Required | +| ----------- | ----------------------------------------------------------------------- | ---------------- | -------- | +| `name` | Name of platform export was run on. | `string` | Yes | +| `release` | Platform version. | `string` | Yes | +| `target_id` | Platform target ID (i.e., further identifying information on platform). | `string`, `null` | No | + +A basic representation of this structure in JSON is as so: + +```json +{ + "name": "", + "release": "", + "target_id": "" +} +``` + +### **Statistics** + +| Field Name | Definition | Type | Required | +| ---------- | -------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------- | -------- | +| `controls` | Break down of control statistics by result status. | [`StatisticHash`](https://github.com/mitre/heimdall2/blob/master/libs/inspecjs/src/generated_parsers/v_1_0/exec-json.ts#L442), `null` | No | +| `duration` | Duration of run (in seconds). | `number`, `null` | No | + +A basic representation of this structure in JSON is as so: + +```json +{ + "controls": {}, + "duration": 0 +} +``` + +### **Passthrough** + +There is no formal schema definition for the Passthrough structure. As such, any key-value pair can technically be used in this structure and still be compliant with the OHDF schema. There are, however, some common field naming conventions for certain types of data that are typically placed in Passthrough as defined below: + +| Field Name | Definition | Type | Required | +| ----------------------- | --------------------------------------------- | --------------------------- | ---------- | +| `auxiliary_data` | Storage for unused data from the sample file. | `Record[]` | Undeclared | +| `auxiliary_data[].name` | Name of auxiliary data source. | `string` | Undeclared | +| `auxiliary_data[].data` | Auxiliary data itself. | `Record` | Undeclared | +| `raw` | Raw data dump of input file. | `Record` | Undeclared | + +A basic representation of this structure in JSON is as so: + +```json +{ + "auxiliary_data": [ + { + "name": "", + "data": {} + } + ], + "raw": {} +} +``` #### Knowledge Check -Given a snippet of GoSec data, try and identify what information is applicable to the additional structures and which field they would correlate with. +Given a snippet of data, try and identify what information is applicable to the Exec JSON, Platform, Statistics, and Passthrough structures and which fields they would correlate with. + +- Data snippet: + +:::details GoSec Source Data -::: details GoSec Source Data ```json { "Golang errors": {}, @@ -310,9 +529,13 @@ Given a snippet of GoSec data, try and identify what information is applicable t "GosecVersion": "dev" } ``` + ::: -::: details OHDF Converted GoSec Data +- Converted OHDF snippet (may not perfectly align with your answers): + +:::details OHDF Converted GoSec Data + ```json { "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, @@ -324,24 +547,193 @@ Given a snippet of GoSec data, try and identify what information is applicable t } } ``` + ::: -## Knowledge Check +## A Look Back -:::details What is the purpose of Profiles, Controls, and Results? -- Profiles provides a high-level overview of the security tool result and the targeted system (i.e., metadata). +In this section, we covered: -- Controls provides information on the security requirements being applied to the target system. +- [Background context for technical aspects of the OHDF schema](#background) +- [A breakdown of the OHDF schema](#breaking-down-the-formal-ohdf-schema): + - [Exec JSON](#exec-json) + - [Platform](#platform) + - [Statistics](#statistics) + - [Passthrough](#passthrough) + - [Profiles](#profiles) + - [Controls](#controls) + - [Results](#results) -- Results provides information on the actual checks to ensure that the target system is meeting the security requirements. -::: +### Knowledge Review + +Now that we're familiar with the OHDF schema, let's revisit that Twistlock-to-OHDF sample with a specific focus on the fields that the data is assigned to. -:::details What is the relationship between Profiles, Controls, and Results? -- The profile contains some number of controls which were tested against the target system during the original security tool run. +Here are some key questions to ask yourself while reading: -- Any given control contains some number of results which reflect the implemented tests to check if the target system is actually meeting the security requirement. +- Does the information assigned to the schema field make sense? + +- Does the definition of the schema field match what the assigned data is trying to convey? + +- Would the data assigned to the schema field be more applicable elsewhere? + +:::note Twistlock-to-OHDF Sample +This file has been truncated for pedagogical purposes. For the full file, see [here](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/sample_jsons/twistlock_mapper/twistlock-hdf.json) ::: -:::details What is the purpose of `passthrough`? -`passthrough` is used to store extraneous information from the source data that has no equivalent in the OHDF schema. It is also used to store the entire raw source data in the `raw` subfield. The overall goal is to preserve data as thoroughly as possible. +:::details Twistlock-to-OHDF Sample + +```json +{ + "platform": { + "name": "Heimdall Tools", + "release": "2.6.29", + "target_id": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a" + }, + "version": "2.6.29", + "statistics": {}, + "profiles": [ + { + "name": "Twistlock Scan", + "title": "Twistlock Project: All / TEST-COLLECTION", + "summary": "Package Vulnerability Summary: 97 Application Compliance Issue Total: 0", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "controls": [ + { + "tags": { + "nist": ["SI-2", "RA-5"], + "cci": ["CCI-002605", "CCI-001643"], + "cveid": "CVE-2021-43529" + }, + "refs": [], + "source_location": {}, + "title": "CVE-2021-43529", + "id": "CVE-2021-43529", + "desc": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "impact": 0.9, + "code": "{\n \"id\": \"CVE-2021-43529\",\n \"status\": \"affected\",\n \"cvss\": 9.8,\n \"description\": \"DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec\",\n \"severity\": \"critical\",\n \"packageName\": \"nss-util\",\n \"packageVersion\": \"3.67.0-7.el8_5\",\n \"link\": \"https://access.redhat.com/security/cve/CVE-2021-43529\",\n \"riskFactors\": [\n \"Remote execution\",\n \"Attack complexity: low\",\n \"Attack vector: network\",\n \"Critical severity\",\n \"Recent vulnerability\"\n ],\n \"impactedVersions\": [\n \"*\"\n ],\n \"publishedDate\": \"2021-12-01T00:00:00Z\",\n \"discoveredDate\": \"2022-05-18T12:24:22Z\",\n \"layerTime\": \"2022-05-16T23:12:25Z\"\n}", + "results": [ + { + "status": "failed", + "code_desc": "Package \"nss-util\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-util\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-util\"", + "start_time": "2022-05-18T12:24:22Z" + }, + { + "status": "failed", + "code_desc": "Package \"nss-sysinit\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-sysinit\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-sysinit\"", + "start_time": "2022-05-18T12:24:22Z" + }, + { + "status": "failed", + "code_desc": "Package \"nss\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss\"", + "start_time": "2022-05-18T12:24:22Z" + }, + { + "status": "failed", + "code_desc": "Package \"nss-softokn\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-softokn\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-softokn\"", + "start_time": "2022-05-18T12:24:22Z" + }, + { + "status": "failed", + "code_desc": "Package \"nss-softokn-freebl\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-softokn-freebl\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-softokn-freebl\"", + "start_time": "2022-05-18T12:24:22Z" + } + ] + } + ], + "sha256": "807c8ef1534bb7f3e428db4a40667a6dd37d89f8a48dc6d1f6bb2426ff53f97f" + } + ], + "passthrough": { + "auxiliary_data": [ + { + "name": "Twistlock", + "data": { + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + }, + { + "type": "os", + "name": "nss-softokn", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + }, + { + "type": "os", + "name": "nss", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + }, + { + "type": "os", + "name": "nss-softokn-freebl", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + }, + { + "type": "os", + "name": "nss-sysinit", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } + ], + "applications": [ + { + "name": "asp.net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + }, + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceScanPassed": true, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-03T08:38:31Z" + }, + { + "created": "2022-05-03T08:39:27Z" + }, + { + "created": "2022-05-16T23:12:02Z", + "instruction": "ARG GOPROXY=http://nexus-repository-manager.nexus-repository-manager.svc.cluster.local:8081/repository/goproxy/ HTTP_PROXY=http://localhost:3128 http_proxy=http://localhost:3128" + }, + { + "created": "2022-05-16T23:12:02Z", + "instruction": "ARG GOPROXY=http://nexus-repository-manager.nexus-repository-manager.svc.cluster.local:8081/repository/goproxy/ GOSUMDB=sum.golang.org http://nexus-repository-manager.nexus-repository-manager.svc.cluster.local:8081/repository/gosum HTTP_PROXY=http://localhost:3128 http_proxy=http://localhost:3128" + } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" + } + } + ] + } +} +``` + ::: diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md index 7e6bdd197..0d0acbaf6 100644 --- a/src/courses/mappers/07.md +++ b/src/courses/mappers/07.md @@ -1,134 +1,42 @@ --- order: 7 -next: 08.md -title: Required OHDF Schema Fields +next: 09.md +title: OHDF Schema Review author: Charles Hu --- -## Required OHDF Schema Fields +## OHDF Schema Review -Not all fields in the schema have to be filled or even used in an OHDF mapper. In practice, most implementations either provide a blank field or omit an unused field entirely. +Now that you've familiarized yourself with the formal OHDF schema, let's revisit the GoSec and Twistlock examples and analyze both the original source data and how it has been converted to OHDF. -Note that just because you can skip a schema field does not mean that you should. Always aim to maximize the filled fields in your mapper and only skip a field as a last resort if no applicable equivalent exists in your source data. Consider required fields as priority fields that you should aim to fill out first instead of the bare minimum necessary to create a mapper. +Here are some key questions to keep note of while reading through these examples: -The fields that are specifically required by the schema are as follows: +- How is the source data structured/organized (e.g., by requirement, by target system, by finding)? +- Is the source data's data format perfectly aligned to OHDF? + - What should we do when multiple source data fields correspond to the same OHDF field? + - How should we handle a source data field that contains information correlating to multiple OHDF fields? + - How should we handle source data fields that don't fit into the OHDF schema? +- How is the structure of the source data interpreted to fit the OHDF hierarchy? + - What groups of fields in the source data correlate to our Profiles, Controls, and Results structures? +- Which fields in the source data are used to fill each OHDF field? Is that mapping accurate? + - Can you think of a reason for why that field is used to populate the OHDF field? + - Are there any fields in the source data that you believe are more applicable? Why? +- Which fields are unfilled/omitted? + - Can you think of a reason for why that field is unfilled/omitted? + - Are there any fields in the source data that you believe are applicable? Why? -::: details Required Fields -```json -{ - platform: { - name, - release - }, - version, - statistics, - profiles: [ - 0: { - name, - sha256, - supports, - attributes, - groups, - controls: [ - 0: { - id, - impact, - refs, - tags, - source_location, - results: [ - 0: { - code_desc, - start_time - }, - ] - }, - ] - }, - ] -} -``` -::: +These questions will help you understand the conversion process for when you create your own OHDF mappers later. -## In Context +:::note Sample Files +The sample files below are truncated for pedagogical purposes. -The required fields in context of the full schema are shown below: - -::: details Full Schema -```json -{ - platform: { // required field - name, // required field - release, // required field - target_id - }, - version, // required field - statistics: { // required field - duration - }, - profiles: [ // required field - 0: { - name, // required field - version, - sha256, // required field - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, // required field - attributes, // required field - groups, // required field - controls: [ // required field - 0: { - id, // required field - title, - desc, - descriptions, - impact, // required field - refs, // required field - tags, // required field - code, - source_location, // required field - results: [ // required field - 0: { - status, - code_desc, // required field - message, - run_time, - start_time // required field - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - 0: { - name, - data - }, - ], - raw - } -} -``` +For the original files and more examples of actual OHDF samples used in production, see [here](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters/sample_jsons). ::: -## Example - -Here's an example of GoSec source data and the converted OHDF file that has been annotated to show the required/not required fields. +### GoSec -Here are some key questions to keep note of while reading through the example: +:::details Source Data -- Why is a required field filled/unfilled? -- Why is an unrequired field filled/unfilled? -- Is there an appropriate field from the source data to fill in an unfilled field in the OHDF file? - -::: details Source Data ```json { "Golang errors": {}, @@ -159,29 +67,28 @@ Here are some key questions to keep note of while reading through the example: "GosecVersion": "dev" } ``` + ::: -::: details Converted OHDF File +:::details Converted OHDF File + ```json { - "platform": { // required - "name": "Heimdall Tools", // required - "release": "2.10.8" // required - }, - "version": "2.10.8", // required - "statistics": {}, // required - "profiles": [ // required + "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, + "version": "2.10.8", + "statistics": {}, + "profiles": [ { - "name": "Gosec scanner", // required - "title": "gosec", // not required - "version": "dev", // not required - "supports": [], // required - "attributes": [], // required - "groups": [], // required - "status": "loaded", // not required - "controls": [ // required + "name": "Gosec scanner", + "title": "gosec", + "version": "dev", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "controls": [ { - "tags": { // required + "tags": { "nist": ["SI-10"], "cwe": { "id": "22", @@ -192,28 +99,202 @@ Here are some key questions to keep note of while reading through the example: "severity": "MEDIUM", "confidence": "HIGH" }, - "refs": [], // required - "source_location": {}, // required - "title": "Potential file inclusion via variable", // not required - "id": "G304", // required - "desc": "", // not required - "impact": 0.5, // required - "results": [ // required + "refs": [], + "source_location": {}, + "title": "Potential file inclusion via variable", + "id": "G304", + "desc": "", + "impact": 0.5, + "results": [ + { + "status": "failed", + "code_desc": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "message": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go, line:83, column:14", + "start_time": "" + } + ] + } + ], + "sha256": "d0506f4b7715bf8b1cd81a8a87ab8efcce41ebeb2b5ec5fcfb23d3bdd136f48c" + } + ], + "passthrough": { + "auxiliary_data": [{ "name": "Gosec", "data": { "Golang errors": {} } }] + } +} +``` + +::: + +### Twistlock + +:::details Source Data + +```json +{ + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "collections": ["All", "TEST-COLLECTION"], + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } + ], + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceDistribution": { + "critical": 0, + "high": 0, + "medium": 0, + "low": 0, + "total": 0 + }, + "complianceScanPassed": true, + "vulnerabilities": [ + { + "id": "CVE-2021-43529", + "status": "affected", + "cvss": 9.8, + "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "severity": "critical", + "packageName": "nss-util", + "packageVersion": "3.67.0-7.el8_5", + "link": "https://access.redhat.com/security/cve/CVE-2021-43529", + "riskFactors": [ + "Remote execution", + "Attack complexity: low", + "Attack vector: network", + "Critical severity", + "Recent vulnerability" + ], + "impactedVersions": ["*"], + "publishedDate": "2021-12-01T00:00:00Z", + "discoveredDate": "2022-05-18T12:24:22Z", + "layerTime": "2022-05-16T23:12:25Z" + } + ], + "vulnerabilityDistribution": { + "critical": 5, + "high": 1, + "medium": 86, + "low": 5, + "total": 97 + }, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-03T08:38:31Z" + } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" +} +``` + +::: + +:::details Converted OHDF File + +```json +{ + "platform": { + "name": "Heimdall Tools", + "release": "2.10.8", + "target_id": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a" + }, + "version": "2.10.8", + "statistics": {}, + "profiles": [ + { + "name": "Twistlock Scan", + "title": "Twistlock Project: All / TEST-COLLECTION", + "summary": "Package Vulnerability Summary: 97 Application Compliance Issue Total: 0", + "supports": [], + "attributes": [], + "groups": [], + "status": "loaded", + "controls": [ + { + "tags": { + "nist": ["SI-2", "RA-5"], + "cci": ["CCI-002605", "CCI-001643"], + "cveid": "CVE-2021-43529" + }, + "refs": [], + "source_location": {}, + "title": "CVE-2021-43529", + "id": "CVE-2021-43529", + "desc": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "impact": 0.9, + "code": "{\n \"id\": \"CVE-2021-43529\",\n \"status\": \"affected\",\n \"cvss\": 9.8,\n \"description\": \"DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec\",\n \"severity\": \"critical\",\n \"packageName\": \"nss-util\",\n \"packageVersion\": \"3.67.0-7.el8_5\",\n \"link\": \"https://access.redhat.com/security/cve/CVE-2021-43529\",\n \"riskFactors\": [\n \"Remote execution\",\n \"Attack complexity: low\",\n \"Attack vector: network\",\n \"Critical severity\",\n \"Recent vulnerability\"\n ],\n \"impactedVersions\": [\n \"*\"\n ],\n \"publishedDate\": \"2021-12-01T00:00:00Z\",\n \"discoveredDate\": \"2022-05-18T12:24:22Z\",\n \"layerTime\": \"2022-05-16T23:12:25Z\"\n}", + "results": [ { - "status": "failed", // not required - "code_desc": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", // required - "message": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go, line:83, column:14", // not required - "start_time": "" // required + "status": "failed", + "code_desc": "Package \"nss-util\" should be updated to latest version above impacted versions [\"*\"]", + "message": "Expected latest version of \"nss-util\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-util\"", + "start_time": "2022-05-18T12:24:22Z" } ] } ], - "sha256": "d0506f4b7715bf8b1cd81a8a87ab8efcce41ebeb2b5ec5fcfb23d3bdd136f48c" // required + "sha256": "998180601124e9d2b4f03be239a5bb68d9045ba2dc5a26fa2c8d453500288b2e" } ], - "passthrough": { // not required - "auxiliary_data": [{ "name": "Gosec", "data": { "Golang errors": {} } }] // not required + "passthrough": { + "auxiliary_data": [ + { + "name": "Twistlock", + "data": { + "results": [ + { + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "packages": [ + { + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } + ], + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceScanPassed": true, + "vulnerabilityScanPassed": true, + "history": [{ "created": "2022-05-03T08:38:31Z" }], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" + } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" + } + } + ] } } ``` + ::: diff --git a/src/courses/mappers/08.md b/src/courses/mappers/08.md deleted file mode 100644 index cdab18b46..000000000 --- a/src/courses/mappers/08.md +++ /dev/null @@ -1,288 +0,0 @@ ---- -order: 8 -next: 09.md -title: OHDF Schema Review -author: Charles Hu ---- - -## OHDF Schema Review - -Now that you've familiarized yourself with the formal OHDF schema, let's revisit the GoSec and Twistlock examples and apply some of that knowledge. - -Here are some key questions to keep note of while reading through these examples: - -- How is the source data structured/organized (e.g., by requirement, by target system, by finding)? -- How is the OHDF file structured? -- What should we do when multiple source data fields correspond to the same OHDF field? -- How should we handle a source data field that contains information correlating to multiple oHDF fields? -- How should we handle source data fields that don't fit into the OHDF schema? -- How is the structure of the source data interpreted to fit the OHDF hierarchy? - - What groups of fields in the source data correlate to our profiles, controls, and results structures? -- Which fields in the source data are used to fill each OHDF field? Is that mapping accurate? - - Can you think of a reason for why that field is used to generate the OHDF field? - - Are there any fields in the source data that you believe are more applicable? Why? -- Which fields are unfilled/omitted? - - Can you think of a reason for why that field is unfilled/omitted? - - Are there any fields in the source data that you believe are applicable? Why? - -These questions will help you understand the conversion process for when you create your own OHDF mappers later. - -### GoSec - -::: details Source Data -```json -{ - "Golang errors": {}, - "Issues": [ - { - "severity": "MEDIUM", - "confidence": "HIGH", - "cwe": { - "id": "22", - "url": "https://cwe.mitre.org/data/definitions/22.html" - }, - "rule_id": "G304", - "details": "Potential file inclusion via variable", - "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", - "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - "line": "83", - "column": "14", - "nosec": false, - "suppressions": null - } - ], - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - }, - "GosecVersion": "dev" -} -``` -::: - -::: details Converted OHDF File -```json -{ - "platform": { "name": "Heimdall Tools", "release": "2.10.8" }, - "version": "2.10.8", - "statistics": {}, - "profiles": [ - { - "name": "Gosec scanner", - "title": "gosec", - "version": "dev", - "supports": [], - "attributes": [], - "groups": [], - "status": "loaded", - "controls": [ - { - "tags": { - "nist": ["SI-10"], - "cwe": { - "id": "22", - "url": "https://cwe.mitre.org/data/definitions/22.html" - }, - "nosec": "", - "suppressions": "", - "severity": "MEDIUM", - "confidence": "HIGH" - }, - "refs": [], - "source_location": {}, - "title": "Potential file inclusion via variable", - "id": "G304", - "desc": "", - "impact": 0.5, - "results": [ - { - "status": "failed", - "code_desc": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - "message": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go, line:83, column:14", - "start_time": "" - } - ] - } - ], - "sha256": "d0506f4b7715bf8b1cd81a8a87ab8efcce41ebeb2b5ec5fcfb23d3bdd136f48c" - } - ], - "passthrough": { - "auxiliary_data": [{ "name": "Gosec", "data": { "Golang errors": {} } }] - } -} -``` -::: - -### Twistlock - -::: details Source Data -```json -{ - "results": [ - { - "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", - "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", - "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", - "distroRelease": "RHEL8", - "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", - "collections": ["All", "TEST-COLLECTION"], - "packages": [ - { - "type": "os", - "name": "nss-util", - "version": "3.67.0-7.el8_5", - "licenses": ["MPLv2.0"] - } - ], - "applications": [ - { - "name": ".net-core", - "version": "5.0.17", - "path": "/usr/lib64/dotnet/dotnet" - } - ], - "complianceDistribution": { - "critical": 0, - "high": 0, - "medium": 0, - "low": 0, - "total": 0 - }, - "complianceScanPassed": true, - "vulnerabilities": [ - { - "id": "CVE-2021-43529", - "status": "affected", - "cvss": 9.8, - "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", - "severity": "critical", - "packageName": "nss-util", - "packageVersion": "3.67.0-7.el8_5", - "link": "https://access.redhat.com/security/cve/CVE-2021-43529", - "riskFactors": [ - "Remote execution", - "Attack complexity: low", - "Attack vector: network", - "Critical severity", - "Recent vulnerability" - ], - "impactedVersions": ["*"], - "publishedDate": "2021-12-01T00:00:00Z", - "discoveredDate": "2022-05-18T12:24:22Z", - "layerTime": "2022-05-16T23:12:25Z" - } - ], - "vulnerabilityDistribution": { - "critical": 5, - "high": 1, - "medium": 86, - "low": 5, - "total": 97 - }, - "vulnerabilityScanPassed": true, - "history": [ - { - "created": "2022-05-03T08:38:31Z" - } - ], - "scanTime": "2022-05-18T12:24:32.855444532Z", - "scanID": "6284e580d9600f8d0db159e2" - } - ], - "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" -} -``` -::: - -::: details Converted OHDF File -```json -{ - "platform": { - "name": "Heimdall Tools", - "release": "2.10.8", - "target_id": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a" - }, - "version": "2.10.8", - "statistics": {}, - "profiles": [ - { - "name": "Twistlock Scan", - "title": "Twistlock Project: All / TEST-COLLECTION", - "summary": "Package Vulnerability Summary: 97 Application Compliance Issue Total: 0", - "supports": [], - "attributes": [], - "groups": [], - "status": "loaded", - "controls": [ - { - "tags": { - "nist": ["SI-2", "RA-5"], - "cci": ["CCI-002605", "CCI-001643"], - "cveid": "CVE-2021-43529" - }, - "refs": [], - "source_location": {}, - "title": "CVE-2021-43529", - "id": "CVE-2021-43529", - "desc": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", - "impact": 0.9, - "code": "{\n \"id\": \"CVE-2021-43529\",\n \"status\": \"affected\",\n \"cvss\": 9.8,\n \"description\": \"DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec\",\n \"severity\": \"critical\",\n \"packageName\": \"nss-util\",\n \"packageVersion\": \"3.67.0-7.el8_5\",\n \"link\": \"https://access.redhat.com/security/cve/CVE-2021-43529\",\n \"riskFactors\": [\n \"Remote execution\",\n \"Attack complexity: low\",\n \"Attack vector: network\",\n \"Critical severity\",\n \"Recent vulnerability\"\n ],\n \"impactedVersions\": [\n \"*\"\n ],\n \"publishedDate\": \"2021-12-01T00:00:00Z\",\n \"discoveredDate\": \"2022-05-18T12:24:22Z\",\n \"layerTime\": \"2022-05-16T23:12:25Z\"\n}", - "results": [ - { - "status": "failed", - "code_desc": "Package \"nss-util\" should be updated to latest version above impacted versions [\"*\"]", - "message": "Expected latest version of \"nss-util\"\nDetected vulnerable version \"3.67.0-7.el8_5\" of \"nss-util\"", - "start_time": "2022-05-18T12:24:22Z" - } - ] - } - ], - "sha256": "998180601124e9d2b4f03be239a5bb68d9045ba2dc5a26fa2c8d453500288b2e" - } - ], - "passthrough": { - "auxiliary_data": [ - { - "name": "Twistlock", - "data": { - "results": [ - { - "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", - "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", - "distroRelease": "RHEL8", - "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", - "packages": [ - { - "type": "os", - "name": "nss-util", - "version": "3.67.0-7.el8_5", - "licenses": ["MPLv2.0"] - } - ], - "applications": [ - { - "name": ".net-core", - "version": "5.0.17", - "path": "/usr/lib64/dotnet/dotnet" - } - ], - "complianceScanPassed": true, - "vulnerabilityScanPassed": true, - "history": [{ "created": "2022-05-03T08:38:31Z" }], - "scanTime": "2022-05-18T12:24:32.855444532Z", - "scanID": "6284e580d9600f8d0db159e2" - } - ], - "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" - } - } - ] - } -} -``` -::: - -More examples of actual OHDF samples used in production can be [found here](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters/sample_jsons). From c0e03d49e6128ba5c65282d2b0d0c83ba523e725 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Fri, 23 Aug 2024 10:26:55 -0400 Subject: [PATCH 68/71] OHDF Converters rework Signed-off-by: Charles Hu --- src/courses/mappers/06.md | 3 + src/courses/mappers/07.md | 2 +- src/courses/mappers/08.md | 304 +++++ src/courses/mappers/09.md | 219 ++-- src/courses/mappers/10.md | 63 +- src/courses/mappers/11.md | 1653 +++++++++++++++++++++++- src/courses/mappers/12.md | 2572 ++++++++++++++++++++++++++++++++++++- src/courses/mappers/13.md | 1588 +---------------------- src/courses/mappers/14.md | 2504 ++---------------------------------- src/courses/mappers/15.md | 42 +- src/courses/mappers/16.md | 460 ++++--- src/courses/mappers/17.md | 24 - src/courses/mappers/18.md | 279 ---- 13 files changed, 5040 insertions(+), 4673 deletions(-) create mode 100644 src/courses/mappers/08.md delete mode 100644 src/courses/mappers/17.md delete mode 100644 src/courses/mappers/18.md diff --git a/src/courses/mappers/06.md b/src/courses/mappers/06.md index 3ed2d36c7..089b13bca 100644 --- a/src/courses/mappers/06.md +++ b/src/courses/mappers/06.md @@ -555,6 +555,9 @@ Given a snippet of data, try and identify what information is applicable to the In this section, we covered: - [Background context for technical aspects of the OHDF schema](#background) + + - Certain unused/uncorrelated fields in the final OHDF mapping can be omitted/left empty depending on whether the field is qualified as required. + - [A breakdown of the OHDF schema](#breaking-down-the-formal-ohdf-schema): - [Exec JSON](#exec-json) - [Platform](#platform) diff --git a/src/courses/mappers/07.md b/src/courses/mappers/07.md index 0d0acbaf6..ff9db3033 100644 --- a/src/courses/mappers/07.md +++ b/src/courses/mappers/07.md @@ -1,6 +1,6 @@ --- order: 7 -next: 09.md +next: 08.md title: OHDF Schema Review author: Charles Hu --- diff --git a/src/courses/mappers/08.md b/src/courses/mappers/08.md new file mode 100644 index 000000000..6925732ed --- /dev/null +++ b/src/courses/mappers/08.md @@ -0,0 +1,304 @@ +--- +order: 8 +next: 09.md +title: OHDF Converters +author: Charles Hu +--- + +## A Look Ahead + +In this section, we will cover: + +- [What OHDF Converters is](#overview) +- How OHDF Converters can be used to create: + - [The fingerprinting component](#fingerprinting) + - [The mapper component](#mapper) + - [The testing component](#testing) + +## Overview + +OHDF Converters is a custom data normalization library that hosts and provides OHDF mapper normalization services to other applications in the SAF tool suite. All OHDF mappers depend on and utilize the functionality that OHDF converters provides in order to implement [the three core components of an OHDF mapper](./04.md). As such, it is important to have a general understanding of what some key OHDF Converters utilities are and how they operate in order to create the necessary components for an OHDF mapper and successfully integrate your OHDF mapper into OHDF Converters. + +### Directory Structure + +The following is a simplified depiction of the directory tree for the HDF Converters. Only noteworthy and potentially useful files and directories are included. It is not imperative to memorize the structure, but it is useful to familiarize yourself with it to better understand what exists where in the library for future reference. + +``` +hdf-converters ++-- data +| +-- converters +| | +-- csv2json.ts +| | +-- xml2json.ts ++-- sample_jsons // Sample exports for mapper testing are located here ++-- src // *-to-OHDF mappers are located here +| +-- converters-from-hdf // OHDF-to-* mappers are located here +| | +-- reverse-any-base-converter.ts +| | +-- reverse-base-converter.ts +| +-- mappings // Non-OHDF mappings are located here (e.g., CVE, CCI, NIST) +| +-- utils // Utility functions are located here +| | +-- fingerprinting.ts +| | +-- global.ts +| +-- base-converter.ts ++-- test // Mapper tests are located here +| +-- mappers +| | +-- forward // *-to-OHDF tests +| | +-- reverse // OHDF-to-* tests +| | +-- utils.ts ++-- types // Explicit data typing for known export schemas ++-- index.ts ++-- package.json +``` + +## Fingerprinting + +Fingerprinting in OHDF Converters is performed by the fingerprinting feature implemented in the `fingerprinting.ts` file under `/src/utils/`. The actual fingerprinting utility itself is provided through the following function: + +```typescript +export function fingerprint(guessOptions: { + data: string; + filename: string; +}): INPUT_TYPES; +``` + +This function takes an object which consists of the key-value pairs `data`, which contains a stringified representation of an input file of unknown data format, and `filename`, which contains the file name of the input file. Once the function receives the file to analyze, it leverages two key items: `INPUT_TYPES` and `fileTypeFingerprints`. + +`INPUT_TYPES` is an enumerated type that defines a common set of agreed upon names to identify each data format with. Members of `INPUT_TYPES` typically appear as so: + +```typescript +export enum INPUT_TYPES { + ASFF = "asff", + BURP = "burp", + CHECKLIST = "checklist", + CONVEYOR = "conveyor", + // Truncated for pedagogical purposes +} +``` + +where the enum member is the uppercase snake case form of the common name while the initialized value is the stringified lowercase form of the name. + +`fileTypeFingerprints` is a variable defining the specific set of data elements that we are to uniquely associate with a certain data format. Members of `fileTypeFingerprints` typically appear as so: + +```typescript +const fileTypeFingerprints: Record = { + [INPUT_TYPES.ASFF]: ["Findings", "AwsAccountId", "ProductArn"], + [INPUT_TYPES.CONVEYOR]: ["api_error_message", "api_response"], + [INPUT_TYPES.FORTIFY]: ["FVDL", "FVDL.EngineData.EngineVersion", "FVDL.UUID"], + // Truncated for pedagogical purposes +}; +``` + +where the key is the standard name for a data format as defined by `INPUT_TYPES`, while the value is an array of stringified field names that are cumulatively unqiue to that data format. + +Using the fields defined in `fileTypeFingerprints`, the function `fingerprint()` will search through the input file and attempt to assign it a data format according to whichever fingerprint array in `fileTypeFingerprints` has the most matches to keys found in the input file. It will then return the common name of that data format as defined by `INPUT_TYPES`. If no match is found, it will return an empty string instead (as defined by `INPUT_TYPES.NOT_FOUND`). + +Most OHDF mapper developers will not touch the `fingerprint()` function itself but will rather add the necessary members to `INPUT_TYPES` and `fileTypeFingerprints` in order to allow `fingerprint()` to correctly identify their data format. + +## Mapper + +Mappers are often self-contained in a single specialized file under `/src/`, but leverage a number of utilities spread throughout OHDF Converters to actually implement the ability to normalize input files from developer-provided mappings. + +### Mapper Base Class + +The core of OHDF Converters revolves around the [`base-converter`](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/base-converter.ts) class found in the `base-converter.ts` file under `/src/`. `base-converter` is a key class that all \*-to-OHDF mappers extend. It enables the streamlined development of \*-to-OHDF mappers by abstracting the actual implementation of the underlying service that performs the data transformations (i.e., the mapper), resulting in the developer only having to write a technical implementation of their developed \*-to-OHDF mapping for the `base-converter` class to consume and use. + +Other services provided by `base-converter` include: + +#### File Format Parsing + +`base-converter` provides a number of functions which can parse a variety of file formats and convert them into a usable Javascript object equivalent. + +Currently supported file formats are as follows: + +| Format | Function | +| ------ | ------------------------------------------------------------------------------------------------------------- | +| CSV | [`parseCsv()`](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/base-converter.ts#L75) | +| HTML | [`parseHtml()`](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/base-converter.ts#L43) | +| XML | [`parseXml()`](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/base-converter.ts#L57) | + +#### Generic Types + +`base-converter` accepts type arguments to define the typing of the data that the mapper is expected to ingest. This is defined here: + +```typescript +export class BaseConverter> { + data: D; + mappings?: MappedTransform; + collapseResults: boolean; + + constructor(data: D, collapseResults = false) { + this.data = data; + this.collapseResults = collapseResults; + } + // Truncated for pedagogical purposes +} +``` + +and can be used as so: + +```typescript +export class CycloneDXSBOMMapper extends BaseConverter +``` + +This is particularly useful for when we know the type of incoming data and want to avoid continuous manual casting of types within the mapping. + +#### Keywords + +`base-converter` provides a series of keywords that can be inserted into the technical implementation of the mapping in order to allow necessary code functions or data manipulations to occur within the mapping definition. These keywords are inherited upon extending `base-converter` and are as follows: + +- `path`: Define JSON object path to go to. Paths are found recursively (e.g., if a top-level field is set to the path `result`, then all fields below it will only see the `result` field of the source file). To escape this recursion, you can set the `$` symbol at the beginning of the path. + + - Use: + + ```typescript + path: PATH_AS_STRING; + ``` + + - Example: + + ```typescript + // Attribute `id` will be set as whatever JSON object attribute `vulnerability.id` is + id: { + path: "vulnerability.id"; + } + ``` + + - Example of recursion: + + ```typescript + // Attribute `id` will look at the path `result.id` is instead of just the path `id` + controls: [ + { + path: "result", + id: { path: "id" }, + }, + ]; + ``` + + - Example of escaping from recursion: + + ```typescript + // Attribute `id` will look at the top-level path `id`, ignoring the recursive path `result` + controls: [ + { + path: "result", + id: { path: "$id" }, + }, + ]; + ``` + +- `transformer`: Oftentimes, source data is not be formatted in a readable/desirable manner. To remedy this, we can make use of the `transformer` keyword. The `transformer` accepts a function as a parameter. This can either be an anonymous funciton or a normal, named function. This transformer acts as a callback function that will go to the specified path location and modify the data accordingly. Note that while the `transformer` keyword can accept an array as an input, it expects and will treat the input as a Javascript object. + + - Use: + + ```typescript + transformer: (PARAMETER: TYPE): OUTPUT_TYPE => { + CODE_TO_EXECUTE; + }; + ``` + + - Example: + + ```typescript + // Applying a transformer that maps NIST 800-53 tags to CCI tags + // Attribute 'cci' will be set as the returned CCI tag(s) from the ingested 'data' argument + cci: { + path: 'vulnerabilityClassifications', + transformer: (data: string) => getCCIsForNISTTags(nistTag(data)) + } + ``` + +- `arrayTransformer`: The `arrayTransformer` works similarly to the `transformer` in that it takes our in-progress mapping for the array structure, accepts a function that returns an array, and transforms the array accordingly (e.g., filtering out element items, passing in additional data, etc.). + + - Use: + + ```typescript + arrayTransformer: (PARAMETER: TYPE[]): OUTPUT_TYPE[] => { + CODE_TO_EXECUTE; + }; + ``` + + - Example: + + ```typescript + controls: [ + { + path: "...", // Some path to the array in the source file + // The function 'deduplicateId' will run against all items in the current array that the 'arrayTransformer' was called inside + arrayTransformer: deduplicateId, + }, + ]; + ``` + + In the above code block, `arrayTransformer` is used in the controls array of the mapping, which creates a control for every item in the source file's specified path location. This array, however, may contain duplicate items (with the same IDs); thus, the `arrayTransformer` is being leveraged to deduplicate items with the same ID and collapse them into one element. + +- `pathTransform`: Converts the object path structure. This preprocesses the source file before any of the other keywords are run. Only use this as a last resort if the source file needs to be drastically reworked. Note that the intermediate format generated by it is not saved to disk, so it can be difficult to work through. + + - Use: + + ```typescript + pathTransform: (PARAMETER: TYPE): OUTPUT_TYPE => { + CODE_TO_EXECUTE; + }; + ``` + + - Example: + + ```typescript + // Returns the JSON path if it is an array, otherwise returns an empty array + pathTransform: (value) => (Array.isArray(value) ? value : []), + ``` + +- `key`: Used by `base-converter` to sort an array of objects by. Currently, this is only used in the `controls` array to automatically de-duplicate elements with the same key to ensure that all controls are unique. As a result, you typically only pass control IDs to `key`. When calling the constructor for the mapper, we can set `collapseResults=true` to make use of this automatic deduplication function. + + - Use: + + ```typescript + key: KEY_AS_STRING; + ``` + + - Example: + + ```typescript + // `id` is now the key by which this array will be sorted by + key: "id"; + ``` + +### Utility Files + +Several exported utility functions and variables exist within files contained under `/src/utils/`. Some examples of commonly used ones from `global.ts` are as follows: + +- [`getCCIsForNISTTags()`](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/utils/global.ts#L66): Converts a set of NIST 800-53 tags into CCI tags. + +- [`DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS`](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/utils/global.ts#L12): An array of NIST 800-53s applicable to all automated configuration tests. + +- [`filterString()`](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/utils/global.ts#L104): Return the input string if it is not empty, otherwise return `undefined` if the string is empty. + +You are encouraged to explore these files for further utilities and to add on more to help other developers who may require similar functionality to the one you're implementing. + +## Testing + +Testing in OHDF Converters is facilitated through the [Jest testing framework](https://jestjs.io/docs/getting-started). The tests for \*-to-OHDF mappers are contained under `/test/mappers/forward/` and depend on a set of sample files and expected OHDF output files contained under `/sample_jsons/`. + +The mapper tests operate by passing the sample files found under `/sample_jsons/` to the given mapper to create a set of observed OHDF outputs. These observed outputs will then be compared against the set of expected outputs generated from expected OHDF files also stored under `/sample_jsons/`. The tests will pass if the observed outputs match the expected outputs and will fail otherwise. The exact technical implementation of this will be discussed later on. + +## A Look Back + +In this section, we covered: + +- [What OHDF Converters is](#overview) + + - OHDF Converters is a custom data normalization library that all OHDF mappers depend upon to implement the three core components of an OHDF mapper. + +- How OHDF Converters can be used to create: + + - [The fingerprinting component](#fingerprinting) + + - OHDF Converters provides a fingerprinting service that helps identify the data format of the given input data. + + - [The mapper component](#mapper) + + - OHDF Converters provides a number of utilities provided by both the `base-converter` class and associated utility files to help streamline the OHDF mapper development experience. + + - [The testing component](#testing) + + - OHDF Converters extends the testing framework provided by Jest to ensure that the tested OHDF mappers generate the correct OHDF output. diff --git a/src/courses/mappers/09.md b/src/courses/mappers/09.md index 939aa989b..660ac456d 100644 --- a/src/courses/mappers/09.md +++ b/src/courses/mappers/09.md @@ -1,133 +1,98 @@ --- order: 9 next: 10.md -title: Mapper Preparations - OHDF Converters +title: The Art of Mapper Making author: Charles Hu --- -## An Overview of OHDF Converters - -OHDF Converters is the library that hosts and provides OHDF mappers to other applications in the SAF tool suite. It is important to have a general understanding of a few key features of OHDF Converters as the mappers you develop will be integrated here and leverage the library's utilities. - -### Features - -- Implements OHDF mappers to transform security data formats to and from OHDF. -- Special keyword functions provided by the base-converter class. -- Fingerprinting services for automatic data format identification. - -### Keywords - -base-converter is an underlying class which enables \*-to-HDF mapping in OHDF Converters. It defines \*-to-HDF mappers and provides critical tools in the form of keywords which allow for the construction of such mappers. All \*-to-HDF mappers inherit from this class and therefore have access to the keywords that this class provides. You should aim to utilize these keywords to their fullest potential to ease and simplify mapper development. The provided tools are as follows: - -- `path`: Define JSON object path to go to. Paths are found recursively (for example, if a top-level field has the path `result`, then all fields below it will only see the `result` field of the source file). To escape this recursion, we can make use of the `$` symbol at the beginning of the path. - - Use: - ```typescript - path: PATH_AS_STRING - ``` - - Example: - ```typescript - // Attribute 'id' will be set as whatever JSON object attribute 'vulnerability.id' is - id: {path: 'vulnerability.id'} - ``` - - Example of recursion: - ```typescript - controls: [ - { - path: 'result', - id: {path: 'id'} // This is grabbing from the path 'result.id', not just 'id' - } - ] - ``` - - Example of escaping from recursion: - ```typescript - controls: [ - { - path: 'result', - id: {path: '$id'} // This is grabbing from the top-level path 'id' - } - ] - ``` - -- `transformer`: Sometimes, source data is not formatted in the way we desire. To remedy this, we can make use of the `base-converter` `transformer` functionality. The `transformer` accepts a function as a parameter. This can either be an anonymous funciton or a normal, named function. This transformer acts as a callback function that will go to the specified path location and modify the data accordingly. See the following example, where we apply a transformer that maps nist tags to CCI tags. - - Use: - ```typescript - transformer: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} - ``` - - Example: - ```typescript - // Attribute 'cci' will be set as the returned CCI tag from the ingested 'data' argument - cci: { - path: 'vulnerabilityClassifications', - transformer: (data: string) => getCCIsForNISTTags(nistTag(data)) - } - ``` - -- `arrayTransformer`: The `arrayTransformer` works similarly to the `transformer` in that it takes our in-progress mapping for the array structure, accepts a function that returns an array, and transforms the array accordingly (whether it be filtering out some items, passing in some additional data, or otherwise). - - Use: - ```typescript - arrayTransformer: (PARAMETER: TYPE[]): OUTPUT_TYPE[] => {CODE_TO_EXECUTE} - ``` - - Example: - ```typescript - controls: [ - { - path: '...', // Some path to the array in the source file - // The function 'deduplicateId' will run against all items in the current array that the 'arrayTransformer' was called inside - arrayTransformer: deduplicateId - } - ] - ``` -In the above code block, the `arrayTransformer` is used in the controls array of the mapping, which creates a control for every item in the source file's specified path location. However, this array may contain duplicate items (with the same IDs). Thus, the `arrayTransformer` is being leveraged to de-duplicate items with the same ID and collapse them into one element. - -- `pathTransform`: Converts the JSON object path structure. This preprocesses the source file before *any* of the other keywords are run. We only use this as a last resort if the source file needs to be drastically reworked. Using the `pathTransform` can be difficult to work through, since the intermediate format generated by it is not saved to disk anywhere. - - - Use: - ```typescript - pathTransform: (PARAMETER: TYPE): OUTPUT_TYPE => {CODE_TO_EXECUTE} - ``` - - Example: - ```typescript - // Returns the JSON path if it is an array, otherwise returns an empty array - pathTransform: (value) => (Array.isArray(value) ? value : []), - ``` - -- `key`: Used by base-converter to sort an array of objects by. Currently, this is only used in the `controls` array area to automatically de-duplicate elements with the same key to ensure that they are unique. Thus, we have only ever been passing `id` as a `key`. When calling the constructor for the mapper, we can set `collapseResults=true` to make use of this automatic deduplication function. - - Use: - ```typescript - key: KEY_AS_STRING - ``` - - Example: - ```typescript - // 'id' is now the key by which this array will be sorted by - key: 'id' - ``` - -### Directory Structure - -The following is a simplified depiction of the directory tree for the HDF Converters. Only noteworthy and potentially useful files and directories are included. It is not imperative to memorize the structure, but it is useful to familiarize yourself with it to better understand what exists where within the library for future reference. - -``` -hdf-converters -+-- data -| +-- converters -| | +-- csv2json.ts -| | +-- xml2json.ts -+-- sample_jsons // Sample exports for mapper testing are located here -+-- src // *-to-HDF mappers are located here -| +-- converters-from-hdf // HDF-to-* mappers are located here -| | +-- reverse-any-base-converter.ts -| | +-- reverse-base-converter.ts -| +-- mappings // Non-HDF mappers are located here (e.g., CVE, CCI, NIST) -| +-- utils -| | +-- fingerprinting.ts -| | +-- global.ts -| +-- base-converter.ts -+-- test // Mapper tests are located here -| +-- mappers -| | +-- forward // *-to-HDF tests -| | +-- reverse // HDF-to-* tests -| | +-- utils.ts -+-- types // Explicit data typing for known export schemas -+-- index.ts -+-- package.json -``` +## A Look Ahead + +In this section, we will cover: + +- [Tips and best practices for mapper development](#overview): + - [Reference existing solutions](#reference-existing-solutions) + - [Understand your security tool and data](#understand-your-security-tool-and-data) + - [Use detailed and diverse samples](#use-detailed-and-diverse-samples) + - [Regularly check your work](#regularly-check-your-work) + - [Reach out](#reach-out) + +## Overview + +Mapper creation is a nuanced process in which every situation demands a unique and tailored solution. As a result, there is no one objective best template or process to follow as field mappings will always be designed on a case-by-case basis. + +But don't fret! Mapper making, like many forms of development, is a skill you have to cultivate and improve at. So while there is no one-size-fits-all solution, you can still train yourself to produce mappers that are the best for your needs and uses. + +To help in improving your mapper making skills, the following section details a number of tips and best practices for mapper development that you should keep in mind while creating your mapper. + +## Tips and Best Practices + +### Reference Existing Solutions + +Try to browse and reference existing solutions for other mappers in [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) to glean some insight on how previous \*-to-OHDF mappers were implemented. By doing this, you may be able to find existing solutions to problems you may be facing or find novel ways of implementing concepts that you never thought of before. + +Some simple and generally helpful mappers to look at when starting out are the [Burp Suite mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/burpsuite-mapper.ts) and the [Snyk mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/snyk-mapper.ts). These mappers are straightforward and involve minimal data manipulation or corner cases. They represent the standard mapper experience and will likely reflect how your mapper will turn out unless your data format involves complicated or nontraditional data. + +Some more technically involved mappers are the [CycloneDX SBOM mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/cyclonedx-sbom-mapper.ts) and the [Nessus mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/nessus-mapper.ts). These mappers are much more complicated but involve handling of specific corner cases (SBOM data formatting for the CycloneDX SBOM mapper and high complexity data for the Nessus mapper). It is not advised to look at these mappers unless you are decently familiar with Typescript and software development paradigms. + +### Understand Your Security Tool and Data + +Understand how your security data is meant to be consumed in the original security tool's use case (i.e., don't just start development with the raw security data). Ask yourself the following questions: + +- How does the original security tool group security data? Is it by type of concern? Where/what component was affected? +- What associations does the tool make to common security references (e.g., NIST SP 800-53, CVE, CWE, CCE, OWASP, STIG IDs)? +- What is the purpose of the security tool (e.g., vulnerability scanning, information visualization, etc.)? +- How does the security tool organize its results (e.g., by requirement, by system, etc.)? + +These answers will help ensure that the intent of the data isn't skewed by the mapping process. It is important to try and "seek parity" with the original display style in the vendor's own tool. In other words, users must be able to recognize and navigate the security data in Heimdall just as easily as they can in the original native format. + +### Use Detailed and Diverse Samples + +:::warning Data Sanitization +Sanitize your data sample so that it is safe for public release in the OHDF Converters GitHub repository. Once sensitive data is publically released, it is difficult to effectively scrub off the Internet. You can easily prevent this from happening by thoroughly screening the data first. +::: + +Build your mapper around sample outputs that are detailed and diverse, and try to obtain the data in any machine-readable format (e.g., JSON, XML, CSV) that is natively available. Oftentimes, the schema for the data format is not publically available or is poorly documented, so it is good practice to gather a large volume of varied samples in order to accurately cover the many possible representations of the data format that may exist. + +:::note APIs +If your security tool provides an API instead of a security data export, you will need to explore the API to determine what information may need to be collected and collated for use within the mapper. Even without an explicit results file from the vendor, you should have a thorough understanding of the security data that needs to be mapped to OHDF. We recommend contacting the SAF team for further guidance in creating a specialized mapper that works with that API. +::: + +### Regularly Check Your Work + +Mapper development is an iterative process that involves many adjustments and corrections in order to achieve an \*-to-OHDF mapping that is as accurate as possible. You are encouraged to periodically check on your mapper output during development in order to check on your progress and verify that your mapper is operating as expected. + +The technical details of how to check your output will be discussed later on. + +### Reach Out + +Don't be afraid to reach out to the SAF team for assistance with mapper development if you are unable to solve an issue by yourself or are totally lost on how to continue. Our developers can help you with everything from mapping decisions to mapper integration with OHDF Converters. + +You can contact us through email (saf@groups.mitre.org) for inquiries and by creating a [GitHub issue on the Heimdall2 repository](https://github.com/mitre/heimdall2/issues/new/choose) for technical implementation issues. + +Try to be detailed and thorough in describing your issue. It is difficult to help when we have little to no context on what your problem is or how we can address it, and we certainly can't read minds to figure it out either. + +## A Look Back + +In this section, we covered: + +- [Tips and best practices for mapper development](#overview): + + - [Reference existing solutions](#reference-existing-solutions) + + - Review existing mappers for potential solutions to any development issues you may encounter. + + - [Understand your security tool and data](#understand-your-security-tool-and-data) + + - Have a thorough understanding of your data format so you can preserve the intent of your data format when mapping to OHDF. + + - [Use detailed and diverse samples](#use-detailed-and-diverse-samples) + + - Have a detailed and diverse set of samples to use for building your mapping in order to cover all possible representations of your data format. + + - [Regularly check your work](#regularly-check-your-work) + + - Check on your in-progress OHDF mapper to ensure that your current mapping is satisfactory and working as expected. + + - [Reach out](#reach-out) + + - Reach out for help if you can't work it out on your own. diff --git a/src/courses/mappers/10.md b/src/courses/mappers/10.md index 68062b32c..a49a2354c 100644 --- a/src/courses/mappers/10.md +++ b/src/courses/mappers/10.md @@ -1,45 +1,62 @@ --- order: 10 next: 11.md -title: Mapper Preparations - The Art of Mapper Making +title: Environment Set Up author: Charles Hu --- -## The Art of Mapper Making +## A Look Ahead -Mapper creation is a nuanced process as every situation demands a unique and tailored solution. As a result, there is no one objective best template or process to follow as field translations will always be designed on a case-by-case basis. +In this section, we will cover: -But don't fret! Mapper making, like many forms of development, is a skill you have to cultivate and improve at. So while there is no one-size-fits-all solution, you can still train yourself to produce mappers that are the best for your needs and uses. +## Environment Set Up -To help in improving your mapper making skills, the following section details a number of tips and best practices for mapper development that you should keep in mind while creating your mapper. +Node.js (a runtime environment for JavaScript) and Yarn (a package manager for JavaScript/TypeScript) are external utilities which are utilized extensively within this guide. The following section details their installation process. -## Mapper Making Best Practices +Linux/Mac OS: -### 1. Reach Out +1. Install [nvm](https://github.com/nvm-sh/nvm#install--update-script). -Don't be afraid to reach out to the SAF team for assistance with mapper development. Our developers can help you with everything from mapping decisions to mapper integration with OHDF Converters. +- 1a. Use either of the following commands to install nvm: -You can contact us through email (saf@groups.mitre.org) for inquiries and by creating a [GitHub issue on the Heimdall2 repository](https://github.com/mitre/heimdall2/issues/new/choose) for technical implementation issues. + ```shell + curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash + ``` -### 2. Reference Existing Solutions + ```shell + wget -qO- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash + ``` -Try to browse and reference existing solutions in [OHDF Converters](https://github.com/mitre/heimdall2/tree/master/libs/hdf-converters) to glean some insight to how previous mappers were implemented. Through this, you might be able to find potential solutions to issues you encounter while making your mapper. +- 1b. Either restart the terminal or run the following commands to use nvm: + ```shell + export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")" + [ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh" # This loads nvm + ``` -### 3. Understand Your Security Tool and Data +2. Run the following command to install and use Node.js v18: -Understand how your security data is meant to be consumed in the original security tool's use case (i.e., don't just start development with the raw security data). Ask yourself the following questions: +```shell +nvm install 18 +``` -- How does the original security tool vendor group security data? Is it by type of concern? Where/what component was affected? -- What associations does the tool make to common security references (e.g., NIST SP 800-53, CVE, CWE, CCE, OWASP, STIG IDs)? -- What is the purpose of the security tool (e.g., vulnerability scanning, information visualization, etc.)? -- How does the security tool organize its results (e.g., by requirement, by system, etc.)? +3. Install [Yarn](https://yarnpkg.com/getting-started/install) -These answers will help ensure that the intent of the data isn't skewed by the mapping process. It is important to try and "seek parity" with the original display style in the vendor's own tool. In other words, users must be able to recognize and navigate the security data in Heimdall just as easily as they can in the original native format. +Windows: -### 4. Use a Detailed Sample +1. Install [Node.js v18 via the installer](https://nodejs.org/en/download/). -::: note APIs -If your security tool provides an API instead of a security data export, you will need to explore the API to determine what information may need to be collected and collated for use within the mapper. Even without an explicit results file from the vendor, you should have a thorough understanding of the security data that needs to be mapped to OHDF. We recommend contacting the SAF team for further guidance in creating a specialized mapper that works with that API. -::: +2. Install [Yarn](https://yarnpkg.com/getting-started/install): -Build your mapper around a sample output that is the most detailed the tool can provide, and try to obtain the data in any machine-readable format (e.g., JSON, XML, CSV) that is natively available. Also try to sanitize your data sample so that it is safe for public release in the OHDF Converters GitHub repository. +## Repository Set Up + +1. Fork/branch a development repository from the main [Heimdall2 GitHub repository](https://github.com/mitre/heimdall2). + + - SAF team developers have write access to the main repository and should [create a branch](https://docs.github.com/en/desktop/contributing-and-collaborating-using-github-desktop/making-changes-in-a-branch/managing-branches#creating-a-branch) on the primary development repository. Non-SAF team developers should instead [create a fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo#forking-a-repository) of the main repository and create a development branch there. + +2. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. + +3. Install the necessary dependencies for Heimdall2. Under the `heimdall2` directory, enter the following command in the terminal: + +```shell +yarn install +``` diff --git a/src/courses/mappers/11.md b/src/courses/mappers/11.md index aa13e09e6..c990c6b32 100644 --- a/src/courses/mappers/11.md +++ b/src/courses/mappers/11.md @@ -1,54 +1,1637 @@ --- order: 11 next: 12.md -title: Mapper Preparations - Setting Up -author: Charles Hu +title: Creating a Mapping +author: Charles Hu, Ryan Lin --- -## Environment Set Up +## Mapping Introduction -Node.js (a runtime environment for JavaScript) and Yarn (a package manager for JavaScript/TypeScript) are external utilities which are utilized extensively within this guide. The following section details their installation process. +::: note Security Tool Type +This walkthrough is targeted at converting security scans to OHDF. If your security tool provides exports that are not security scans or are APIs, contact the SAF team for further instruction on how to develop those services into an OHDF mapper. +::: -Linux/Mac OS: +We begin the creation of every OHDF mapper by first planning out how we want correlate the fields in the OHDF and security tool's data format. This mapping is important for the following reasons: -1. Install [nvm](https://github.com/nvm-sh/nvm#install--update-script). - - - 1a. Use either of the following commands to install nvm: - ```shell - curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash - ``` - ```shell - wget -qO- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash - ``` - - - 1b. Either restart the terminal or run the following commands to use nvm: - ```shell - export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")" - [ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh" # This loads nvm - ``` +1. It gives us a good framework for guiding how we actually implement the \*-to-OHDF mapper. +2. It notifies us of potential knowledge gaps we may have of a security tool's data format. We need to close these gaps as best as we can in order to ensure that we can create field correlations that are as accurate/applicable as possible. +3. It gives us a chance to review our mapping in a format that is still human readable. +4. It helps us reduce the amount of corrections and rewrites we have to perform on the actual mapper implementation due to potential mapping errors. -2. Run the following command to install and use Node.js v18: -```shell -nvm install 18 +As we develop the mappings in the following examples, note that we will break down and analyze the fields according to the OHDF schema structures we previously learned about (profiles, controls, and results). This is not necessarily the only or the best way to do this and you are encouraged to develop your own methods for correlating fields that work best for you. + +::: note Use of Exported Security Tool Data +The following examples will use generated instances of exported security tool data that do not reflect the entirety of the schemas they are based on. Ideally, you will want to use the full schema when creating a mapping; however, the full schema is always not readily available. To reflect this, we will be using generated export data and will fill in missing schema data when possible. +::: + +## Mapping Demo - GoSec + +### 1. Breaking Down the Data + +Let's first start with our GoSec sample, which you should be already familiar with: + +::: details GoSec Source Data + +```json +{ + "Golang errors": {}, + "Issues": [ + { + "severity": "MEDIUM", + "confidence": "HIGH", + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + "rule_id": "G304", + "details": "Potential file inclusion via variable", + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + "line": "83", + "column": "14", + "nosec": false, + "suppressions": null + } + ], + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + "GosecVersion": "dev" +} +``` + +::: + +We can begin our mapping process by identifying the purpose of each field in the source data. This is relatively simple in this case as we have a [formal schema for GoSec](https://github.com/securego/gosec/blob/master/issue/issue.go) that defines many of its fields. While we do this, it's also important that we try to tie back each identified purpose to the three general OHDF schema structures that we learned about earlier; that is, in addition to finding the purpose of each field, we should also ask ourselves the following: + +- Is this field recording metadata? +- Is this field recording requirements? +- Is this field recording requirement testing? + +Let's apply this to our GoSec source data. Try to find the answers to these two questions for each field yourself and then refer back to our annotated solution to check your work. + +::: details GoSec Annotated Source Data + +```json +{ + // Purpose: Go compilation errors + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: Container for identified security issues + // Recording: Requirements - This entity records all identified security issues in a Go source code + "Issues": [ + { + // Purpose: The severity of the identified issue + // Recording: Requirements - This is specifically related to the severity level of the requirement + "severity": "MEDIUM", + // Purpose: How sure that the identified issue if applicable to this source code + // Recording: Requirements testing - This field gives the applicability of the issue after source code testing + "confidence": "HIGH", + // Purpose: The associated CWE for the security issue + // Recording: Requirements - This gives the associated CWE for the security issue + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + // Purpose: The internal GoSec ID for the security issue + // Recording: Requirements - This gives an ID for the security issue + "rule_id": "G304", + // Purpose: Explanation of the security issue + // Recording: Requirements - This explains the security issue + "details": "Potential file inclusion via variable", + // Purpose: The offending file + // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The offending code + // Recording: Requirement testing - This specifies the code that fails the requirement after source code testing + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + // Purpose: The line number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "line": "83", + // Purpose: The column number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "column": "14", + // Purpose: Whether this security issue should be ignored + // Recording: Requirements - Specifies whether this security issue should be ignored + "nosec": false, + // Purpose: The supression level for info on the security issue + // Recording: Requirements - Specifies the info suppression level of the security issue + "suppressions": null + } + ], + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Metadata - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + // Purpose: The version of the GoSec instance currently running + // Recording: Metadata - Info on the scan itself + "GosecVersion": "dev" +} +``` + +::: + +Note that this process is subjective and your answers may vary from ours. Don't be so quick to backtrack on your own answers, as your solutions may be as equally valid as ours. There is no objective answer to this process and what's important is that you can identify and break down the source data into useful pieces that we can correlate back to the OHDF schema. + +The purpose of this annotation is to understand the intention of the security tool that produced the source data. By breaking down the source data field by field, we can gain a better understanding of how the security tool structures its export data and intends for it to be read by a user. GoSec, for example, organizes its data by security issues because GoSec is intended for code correction and hardening. This manifests in the real world through the user reading the GoSec report issue by issue and solving them as they go along. We can use this knowledge to help guide us in both correlating the schemas and reconfiguring the structure of the source data to fit OHDF. + +### 2. Correlating the Schemas + +Now that we're familiar with the specifics of the GoSec schema, we can begin to map these fields to the OHDF schema. We'll do this by taking a field in the source data and correlating it to the most applicable OHDF schema field. While performing these correlations, it is important to account for the intention and structure of the source data schema. + +This initial mapping is informal and does not need to adhere to any programming syntax since you're probably annotating the documents by hand. The mapping process entails taking the full field path from the source data and placing it as the corresponding value for the OHDF schema field. Proper implementation of these mappings will be done later in the course. An example of such mapping is as follows: + +```typescript +{ + profiles: [ + { + controls: [ + { + title: Issues.details, + }, + ], + }, + ]; +} +``` + +This shows us a mapping of the field `Issues.details` from the source data to the field `profiles.controls.title` in OHDF. + +Note that sometimes every relevant field within the OHDF schema is addressed, but the source data still contains unmapped data. In such an event, it is good practice to ensure that such data is still passed through to and recorded somewhere within the OHDF schema for data preservation. In most cases, you should place such data in the `passthrough` field. + +Let's first start with an empty OHDF schema as follows: + +::: details Empty OHDF Schema + +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id, + title, + desc, + descriptions, + impact, + refs, + tags, + code, + source_location, + results: [ + { + status, + code_desc, + message, + run_time, + start_time + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +#### Mapping Version 1 + +We can begin our schema correlation by directly porting over fields from the GoSec source data that are obvious: `GosecVersion`, `Issues.rule_id`, `Issues.details`, and `Issues.cwe`. Try to map these fields youself as you follow along and refer to our solution to check your work. + +::: details Correlated Fields +OHDF | Source Data +-|- +`profiles.version` | `GosecVersion` +`profiles.controls.id` | `Issues.rule_id` +`profiles.controls.title` | `Issues.details` +`profiles.controls.tags` | `Issues.cwe` +::: + +::: details OHDF Schema Mapping Ver. 1 + +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version: GosecVersion, // Version of GoSec instance + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc, + descriptions, + impact, + refs, + tags: { + Issues.cwe // Associated CWE for the requirement + }, + code, + source_location, + results: [ + { + status, + code_desc, + message, + run_time, + start_time + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details Remaining GoSec Source Data + +```json +{ + // Purpose: Go compilation errors + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: Container for identified security issues + // Recording: Requirements - This entity records all identified security issues in a Go source code + "Issues": [ + { + // Purpose: The severity of the identified issue + // Recording: Requirements - This is specifically related to the severity level of the requirement + "severity": "MEDIUM", + // Purpose: How sure that the identified issue if applicable to this source code + // Recording: Requirements testing - This field gives the applicability of the issue after source code testing + "confidence": "HIGH", + // Purpose: The offending file + // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The offending code + // Recording: Requirement testing - This specifies the code that fails the requirement after source code testing + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + // Purpose: The line number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "line": "83", + // Purpose: The column number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "column": "14", + // Purpose: Whether this security issue should be ignored + // Recording: Requirements - Specifies whether this security issue should be ignored + "nosec": false, + // Purpose: The supression level for info on the security issue + // Recording: Requirements - Specifies the info suppression level of the security issue + "suppressions": null + } + ], + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Metadata - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + } +} +``` + +::: + +::: details Reasoning + +- `version: GosecVersion`: We want to specifically place this in `version` in `profiles` because this is metadata on the actual security tool that generated these results. This is different from `version` on the top level since that refers to the platform, or the tool creating the actual OHDF file itself. + +- `id: Issues.rule_id`: `rule_id` gives us an ID used by GoSec to identify each failing requirement in the source code. + +- `title: Issues.details`: The source data doesn't provide a proper title that goes along with the failing requirement. In lieu of this, we can use `Issues.details` which does give us a human readable description of the requirement and repurpose it as a title for our control. + +- `tags: {Issues.cwe}`: `Issues.cwe` provides an association of our GoSec security issue with a known vulnerability database. This can be used in `tags` to act as metadata which can used to filter or organize controls created from these GoSec security issues. + ::: + +#### Mapping Version 2 + +Next, let's look at `Issues.code`, which can be a little bit tricky. + +::: details Correlated Fields +OHDF | Source Data +-|- +`profiles.controls.results.code_desc` | `Issues.code` +::: + +::: details OHDF Schema Mapping Ver. 2 + +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version: GosecVersion, // Version of GoSec instance + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc, + descriptions, + impact, + refs, + tags: { + Issues.cwe // Associated CWE for the requirement + }, + code, + source_location, + results: [ + { + status, + code_desc: Issues.code, // The code failing the requirement test + message, + run_time, + start_time + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details Remaining GoSec Source Data + +```json +{ + // Purpose: Go compilation errors + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: Container for identified security issues + // Recording: Requirements - This entity records all identified security issues in a Go source code + "Issues": [ + { + // Purpose: The severity of the identified issue + // Recording: Requirements - This is specifically related to the severity level of the requirement + "severity": "MEDIUM", + // Purpose: How sure that the identified issue if applicable to this source code + // Recording: Requirements testing - This field gives the applicability of the issue after source code testing + "confidence": "HIGH", + // Purpose: The offending file + // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The line number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "line": "83", + // Purpose: The column number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "column": "14", + // Purpose: Whether this security issue should be ignored + // Recording: Requirements - Specifies whether this security issue should be ignored + "nosec": false, + // Purpose: The supression level for info on the security issue + // Recording: Requirements - Specifies the info suppression level of the security issue + "suppressions": null + } + ], + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Metadata - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + } +} +``` + +::: + +::: details Reasoning + +- `code_desc: Issues.code`: `Issues.code` refers to the source code that is explicitly failing the GoSec requirement. This does not align with our definition for `code_desc` but remember that we always aim to seek parity with the original security tool. GoSec focuses heavily on identifying a security issue and directly pinpointing where that issue occurs for immediate resolution. We want to mirror that behavior by also pinpointing where the security issue occurs at instead of providing a code description of what test went wrong. + ::: + +#### Mapping Version 3 + +Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.nosec`, and `Issues.suppressions`. + +::: details Correlated Fields +OHDF | Source Data +-|- +`profiles.controls.tags` | `Issues.severity` +`profiles.controls.tags` | `Issues.confidence` +`profiles.controls.tags` | `Issues.nosec` +`profiles.controls.tags` | `Issues.suppressions` +::: + +::: details OHDF Schema Mapping Ver. 3 + +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version: GosecVersion, // Version of GoSec instance + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc, + descriptions, + impact, + refs, + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + code, + source_location, + results: [ + { + status, + code_desc: Issues.code, // The code for the requirement test + message, + run_time, + start_time + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details Remaining GoSec Source Data + +```json +{ + // Purpose: Go compilation errors + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: Container for identified security issues + // Recording: Requirements - This entity records all identified security issues in a Go source code + "Issues": [ + { + // Purpose: The offending file + // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The line number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "line": "83", + // Purpose: The column number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "column": "14" + } + ], + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Metadata - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + } +} +``` + +::: + +::: details Reasoning +We map these fields to `tags` in the OHDF schema due to each of these fields acting as descriptive traits of the control which we can categorize and sort the controls by. + +It may be tempting to map `Issues.severity` to `impact`; however, it is important to note that `severity` is not the same as `impact`. These two fields are related but distinct metrics, and while conversion is possible, it is not performed in this case due to uncertainty on how to translate the two metrics properly. +::: + +#### Mapping Version 4 + +Next, let's look at the fields `Issues.file`, `Issues.line`, and `Issues.column`. + +::: details Correlated Fields +OHDF | Source Data +-|- +`profiles.controls.results.message` | `Issues.file` +`profiles.controls.results.message` | `Issues.line` +`profiles.controls.results.message` | `Issues.column` +::: + +::: details OHDF Schema Mapping Ver. 4 + +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version: GosecVersion, // Version of GoSec instance + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc, + descriptions, + impact, + refs, + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + code, + source_location, + results: [ + { + status, + code_desc: Issues.code, // The code for the requirement test + message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred + run_time, + start_time + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details Remaining GoSec Source Data + +```json +{ + // Purpose: Go compilation errors + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Metadata - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + } +} +``` + +::: + +::: details Reasoning +This is a situation similar to the one `Issues.code` is in. `Issues.file`, `Issues.line`, and `Issues.column` do not fit the definition given for `message` (i.e., they are not explanations for the test status); however, they do elaborate upon the location of the offending code snippet identified by GoSec, which we want to seek parity with. Thus, in lieu of any suitable substitutes, we instead use the locational information of the failing source code snippet as a description for the control result. +::: + +#### Mapping Version 5 + +Next, let's look at the fields `Golang errors` and `Stats`. + +::: details Correlated Fields +OHDF | Source Data +-|- +`passthrough.auxiliary_data` | `Golang errors` +`passthrough.auxiliary_data` | `Stats` +::: + +::: details OHDF Schema Mapping Ver. 5 + +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version: GosecVersion, // Version of GoSec instance + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc, + descriptions, + impact, + refs, + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + code, + source_location, + results: [ + { + status, + code_desc: Issues.code, // The code for the requirement test + message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred + run_time, + start_time + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } + ], + raw + } +} +``` + +::: + +::: details Reasoning +For these fields, we can place them in `passthrough` as there are no reasonably applicable fields in the OHDF schema to place them in. + +`Golang errors` is not used anywhere in `controls` as it is a description of compilation errors which would've already been flagged by GoSec as security issues if they already occurred. Thus, to avoid duplication, `Golang errors` is omitted from the main OHDF structures. +::: + +#### Mapping Version 6 + +Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. + +::: details Correlated Fields +OHDF | Source Data +-|- +`platform.name` | `'Heimdall Tools'` +`platform.release` | `HeimdallToolsVersion` +`version` | `HeimdallToolsVersion` +`profiles.name` | `'Gosec scanner'` +`profiles.title` | `'gosec'` +`profiles.controls.impact` | `0.5` +`profiles.controls.results.status` | `'Failure'` +`profiles.status` | `'loaded'` +::: + +::: details OHDF Schema Mapping Ver. 6 + +```typescript +{ + platform: { // We fill in Heimdall for the platform as it handles the generation of this OHDF file + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, // See 'platform' reasoning + statistics: {}, // Not enough info to fill + profiles: [ + { + name: 'Gosec scanner', // We know that this report is generated from GoSec + version: GosecVersion, // Version of GoSec instance + sha256: '', // Leave it empty as OHDF Converters will generate one for us + title: 'gosec', // We know that this report is generated from GoSec + supports: [], // Not enough info to fill + attributes: [], // Not enough info to fill + groups: [], // Not enough info to fill + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc: '', // Not enough info to fill + impact: 0.5, // Have no solid information on impact of security issue, so we default to 0.5 + refs: [], // Not enough info to fill + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + source_location: {}, // Not enough info to fill + results: [ + { + status: 'failed', // The security scan only reports failed requirements, so all findings we receive get fail statuses + code_desc: Issues.code, // The code failing the requirement test + message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred + start_time // Not enough info to fill + } + ] + }, + ], + status: 'loaded' // Give loaded status to denote that profile is loaded by OHDF Converters + }, + ], + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } + ], + raw + } +} +``` + +::: + +::: details Reasoning +Unfilled fields are a result of a lack of sufficent information from the source data that can be used to reasonably associate with these fields. + +The reasoning for the filled fields are as follows: + +- `platform: {name: 'Heimdall Tools'}`: `platform` refers to the instance generating the OHDF file, which in this case is Heimdall2 or Heimdall Tools. + +- `platform: {release: HeimdallToolsVersion}`: Similar reasoning as above. + +- `version: HeimdallToolsVersion`: Similar reasoning as `platform` fields. + +- `name: 'Gosec scanner'`: `profiles` refers to the security tool that generated the original source data. In this case, it is the GoSec security scanning tool. + +- `title: 'gosec'`: We can give a succinct title for the profile here. + +- `impact: 0.5`: We use a default value of `0.5` since we do not have a direct mapping set up to convert the `Issues.severity` field. + +- `status: 'failed'`: GoSec only reports security vulnerabilities if it finds that the scanned source code has such security issues present. As such, every reported issue in a GoSec scan will always be a result of a failed security test. + +- `status: 'loaded'`: The status of a profile is typically `loaded` since it has been ingested and converted to OHDF. + ::: + +Now we have a finalized mapping for GoSec to OHDF. + +## Mapping Demo - DbProtect + +It is also possible to convert XML-based results formats. The OHDF library relies on `fast-xml-parser` to convert these XML files into a JSON-like format for compatibility with the base converter. Let us take a look at one such example: The DbProtect Mapper. + +### 1. Breaking Down the Data + +Let's first start with our DbProtect sample. + +::: details DbProtect Source Data + +```xml + + + + + + + + + + + + + + + + + + + + + TEST ORGANIZATION (Local DBP server) + Audit + Microsoft SQL Server + CONDS181 + 10.0.10.204, 1433, MSSQLSERVER + Heimdall Test scan report generation + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + Fact + Improper Access Controls + Medium + 2986 + Schema ownership + Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole + Feb 18 2021 15:57 + + + TEST ORGANIZATION (Local DBP server) + Audit + Microsoft SQL Server + CONDS181 + 10.0.10.204, 1433, MSSQLSERVER + Heimdall Test scan report generation + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + Fact + Improper Access Controls + Medium + 2986 + Schema ownership + Schema name=db_accessadmin;Database=AppDetective;Owner name=db_accessadmin + Feb 18 2021 15:57 + + ... + + + +``` + +::: + +You may notice that the metadata field maps corresponding keys to each of the values in a row of the data field. Consider ways you might try to restructure this data, but focus mainly on the purpose of each of the values for now. We will handle data restructuring in a later portion. + +Unlike with GoSec, DbProtect does not have a published schema. Thus, we must empirically reason the mapping based on our sample data. Because we are reasoning solely off of sample data, even more so than the previous example, this process is subjective and your mapping may vary from ours. One thing we can use to inform ourselves about the purpose of each field in place of a schema, however, is the metadata fields at the top of the sample. + +#### Knowledge Check + +::: details What questions do we ask ourselves when analyzing security data fields? + +- What is the purpose of this field? + +- What is this field recording (metadata, requirements, requirement testing)? + ::: + +Let us now apply this philosophy to our DbProtect source data. Try to find the answers to these two questions for each field yourself and then refer back to our annotated solution to check your work. + +::: details DbProtect Annotated Source Data + +```xml + + + + + + + + + + + + + + + + + + + + + + + + + TEST ORGANIZATION (Local DBP server) + + + Audit + + + Microsoft SQL Server + + + CONDS181 + + + 10.0.10.204, 1433, MSSQLSERVER + + + Heimdall Test scan report generation + + + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + + + Fact + + + Improper Access Controls + + + Medium + + + 2986 + + + Schema ownership + + + Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole + + + Feb 18 2021 15:57 + + ... + + +``` + +::: + +Note that this process is subjective and your answers may vary from ours. Don't be so quick to backtrack on your own answers, as your solutions may be as equally valid as ours. There is no objective answer to this process and what's important is that you can identify and break down the source data into useful pieces that we can correlate back to the OHDF schema. + +### 2. Correlating the Schemas + +Now that we're familiar with the specifics of the DbProtect report structure, we can begin to map these fields to the OHDF schema. + +Note that since we used an export from DbProtect and are not basing our mapping off the full schema, we will inevitably miss some fields. We can rectify this by adding them into our mapping post hoc whenever needed; however, we can still capture these missed fields without manual intervention by using our `passthrough` field to capture unmapped data. + +Let's first start with an empty OHDF schema as follows: + +::: details Empty OHDF Schema + +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id, + title, + desc, + descriptions, + impact, + refs, + tags, + code, + source_location, + results: [ + { + status, + code_desc, + message, + run_time, + start_time + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +#### Mapping Version 1 + +We can begin our schema correlation by directly porting over fields from the DbProtect source data that are obvious: `Check ID`, `Result Status`, and `Date`. Try to map these fields yourself, and refer to our solution below to check your work. + +As in the previous example, note that these mapping are informal and do not need to adhere to any programming syntax. Proper implementation of these mappings will be done later in the course. + +::: details Correlated Fields +OHDF | Source Data +-|- +`profiles.controls.id` | `Check ID` +`profiles.controls.results.status` | `Result Status` +`profiles.controls.results.start_time` | `Date` +::: + +::: details OHDF Schema Mapping Ver. 1 + +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title, + desc, + descriptions, + impact, + refs, + tags: { + nist, + cci + }, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc, + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details Remaining DbProtect Source Data + +```xml + + + + + + + ... + + + + + + TEST ORGANIZATION (Local DBP server) + + + Audit + + + Microsoft SQL Server + + + CONDS181 + + + 10.0.10.204, 1433, MSSQLSERVER + + + Heimdall Test scan report generation + + + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + + + Improper Access Controls + + + Medium + + + Schema ownership + + + Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole + + ... + + ``` -3. Install [Yarn](https://yarnpkg.com/getting-started/install) +::: + +::: details Reasoning + +- `id: 'Check ID'`: `Check ID` gives us an ID used by DbProtect to identify each failing requirement. + +- `status: 'Result Status'`: `Result Status` gives us information about the result of the scan, whether it passed or failed or was skipped. -Windows: +- `start_time: 'Date'`: `Date` provides information about when the scan was run. + ::: -1. Install [Node.js v18 via the installer](https://nodejs.org/en/download/). +#### Mapping Version 2 -2. Install [Yarn](https://yarnpkg.com/getting-started/install): +Now let us handle some of the more detailed information about the specific controls, namely `Task`, `Check Category`, `Risk DV`, `Check`, and `Details`. -## Repository Set Up +::: details Correlated Fields +OHDF | Source Data +-|- +`profiles.controls.desc` | `Task`, `Check Category` +`profiles.controls.impact` | `Risk DV` +`profiles.controls.title` | `Check` +`profiles.controls.results.code_desc` | `Details` +::: -1. Fork/branch a development repository from the main [Heimdall2 GitHub repository](https://github.com/mitre/heimdall2). - - - SAF team developers have write access to the main repository and should [create a branch](https://docs.github.com/en/desktop/contributing-and-collaborating-using-github-desktop/making-changes-in-a-branch/managing-branches#creating-a-branch) on the primary development repository. Non-SAF team developers should instead [create a fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo#forking-a-repository) of the main repository and create a development branch there. +::: details OHDF Schema Mapping Ver. 2 -2. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title: 'Check', + desc: ['Task', 'Check Category'], + descriptions, + impact: 'Risk DV', + refs, + tags: { + nist, + cci + }, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc: 'Details', + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details Remaining DbProtect Source Data -3. Install the necessary dependencies for Heimdall2. Under the `heimdall2` directory, enter the following command in the terminal: -``` shell -yarn install +```xml + + + + + + + ... + + + + + + TEST ORGANIZATION (Local DBP server) + + + Microsoft SQL Server + + + CONDS181 + + + 10.0.10.204, 1433, MSSQLSERVER + + + Heimdall Test scan report generation + + + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + + ... + + ``` + +::: + +::: details Reasoning + +For the control description, we want to give information about the type of control being run. Thus, it makes sense to store the category of the check, and the particular task it was for (whether it was for an Audit, or for another reason). + +In this case, we can directly map impact to `Risk DV` because there exists an intuitive mapping: High, Medium, Low, and Informational can map to 0.7, 0.5, 0.3, and 0, respectively. + +Note that `Check` appears to also correspond to the `Check ID`, and is a brief desciption of the check being run. Thus, it would make sense to map it to the title field of a control. + +Finally, for the details, recall that the `code_desc` is looking for the test expectations as defined by the particular control. `Details` is telling us about the particular result's associated parameters. +::: + +#### Mapping Version 3 + +Finally, we are left with the more general, report-level information from our DbProtect sample file: `Organization`, `Asset Type`, `Check Asset`, `IP Address, Port, Instance`, `Job Name`, `Policy`. Notice that OHDF does not have fields that correspond to some of this additional info, so consider ways to condense this data and encode it into other fields. + +::: details Correlated Fields +OHDF | Source Data +-|- +`profiles.summary` | `Organization`, `Asset`, `Asset Type`, `IP Address, Port, Instance` +`profiles.title` | `Job Name` +`profiles.name` | `Policy` +::: + +::: details OHDF Schema Mapping Ver. 3 + +```typescript +{ + platform: { + name, + release, + target_id + }, + version, + statistics: { + duration + }, + profiles: [ + { + name: 'Policy', + version, + sha256, + title: 'Job Name', + maintainer, + summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title: 'Check', + desc: ['Task', 'Check Category'], + descriptions, + impact: 'Risk DV', + refs, + tags: { + nist, + cci + }, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc: 'Details', + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + status + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details Reasoning +As mentioned previously, OHDF does not have a specific place to put information like the `Organization`, `Asset`, or `Asset Type`. However, we do have a summary field for profiles. Recall our goal of preserving as much data as possible from the source. With this in mind, it would be reasonable to map all these fields to the summary for the sake of preservation. + +The profile name and title fields are a little tricky. Note that the `Policy` field refers to the baseline guidance that the scan tested against. This aligns more with the profile name than the `Job Name`, which is just a name the customer added for the report. Thus, we map the `Policy` field to the `profiles.name` and the `Job Name` field to the `profiles.title` instead. +::: + +#### Mapping Version 4 + +Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. + +::: details Correlated Fields +OHDF | Source Data +-|- +`platform.name` | `'Heimdall Tools'` +`platform.release` | `HeimdallToolsVersion` +`version` | `HeimdallToolsVersion` +`profiles.controls.tags.nist` | `DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS` +`profiles.controls.tags.cci` | `DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS` +`profiles.status` | `'loaded'` +::: + +::: details OHDF Schema Mapping Ver. 4 + +```typescript +{ + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id + }, + version: HeimdallToolsVersion, + statistics: { + duration + }, + profiles: [ + { + name: 'Policy', + version, + sha256, + title: 'Job Name', + maintainer, + summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title: 'Check', + desc: ['Task', 'Check Category'], + descriptions, + impact: 'Risk DV', + refs, + tags: { + nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + cci: DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS + }, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc: 'Details', + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + status: 'loaded' + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details Reasoning +Unfilled fields are a result of a lack of sufficent information from the source data that can be used to reasonably associate with these fields. + +The reasoning for the filled fields are as follows: + +- `platform: {name: 'Heimdall Tools'}`: `platform` refers to the instance generating the OHDF file, which in this case is Heimdall2 or Heimdall Tools. + +- `platform: {release: HeimdallToolsVersion}`: Similar reasoning as above. + +- `version: HeimdallToolsVersion`: Similar reasoning as `platform` fields. + +- `profiles.controls.tags.nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS`: The DbProtect sample does not have any associated NIST tags within it. Thus, we use the default tags for a static code analysis. + +- `profiles.controls.tags.cci: DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS`: Similar reasoning as above. + +- `status: 'loaded'`: The status of a profile is typically `loaded` since it has been ingested and converted to OHDF. + ::: + +Now we have a finalized mapping for DbProtect to OHDF. diff --git a/src/courses/mappers/12.md b/src/courses/mappers/12.md index b896a2781..d8ef8cc5d 100644 --- a/src/courses/mappers/12.md +++ b/src/courses/mappers/12.md @@ -1,26 +1,2566 @@ --- order: 12 next: 13.md -title: Mapping Introduction +title: Implementing a Mapper author: Charles Hu --- -## Overview +## Mapper Introduction -Now that you've finished learning about OHDF and setting up your environment, we can start creating some OHDF mappers. +::: note OHDF Converters Utilities +Special utilities from OHDF Converters are used here. [Refer here](./09.md) for a refresher on OHDF Converters. +::: -The rest of this course will consist of practice examples demonstrating and explaining the what's, how's and why's of OHDF mapper creation with a focus on practical examples derived from mappers used in a production setting. You are encouraged to actively follow along with the examples and recreate them in your own environment. +Now that we have developed a mapping, we can implement that mapping as a mapper which applies the mapping to any compatible file for a conversion to OHDF. -The following is an index of the remaining walkthrough portion of the course: +## File Set Up -1. [Creating a Mapping](./13.md) - - Material type: Conceptual - - Requirement(s): OHDF schema knowledge, security tool schema/format knowledge -2. [Implementing a Mapper](./14.md) - - Material type: Practical - - Requirement(s): TypeScript, OHDF schema knowledge, OHDF Converters knowledge, file format (e.g., JSON, XML, CSV) knowledge -3. [Finalizing the Mapper](./15.md) - - Material type: Practical - - Requirement(s): TypeScript, OHDF Converters knowledge, file format (e.g., JSON, XML, CSV) knowledge -4. [More Practice](./16.md) -5. [Next Steps](./17.md) +A number of crucial files that support and provide the infrastructure needed for the \*-to-OHDF mapper have to be set up first before we begin actual mapper development. + +::: note Specialized Security Tools +This guide is geared for security tools that provide scan-based export data. If your security tool provides a specialized form of export data or is an API, contact the SAF team for further guidance. +::: + +### Mapper File + +First, we need to create the file that hosts the mapper and link to it so other files in OHDF Converters can access it. + +1. Create a blank TypeScript file under the `src` directory in `hdf-converters`. It should be named: + +``` +{YOUR-EXPORT-NAME-HERE}-mapper.ts +``` + +2. Select the appropriate mapper skeleton (see below) for your export type. Place them in the file created in step 1. Replace names (`SKELETON` by default) as necessary. + +::: details JSON Mapper Skeleton + +```typescript +import { ExecJSON } from "inspecjs"; +import _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, +} from "./base-converter"; + +export class SKELETONMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + target_id: null, //Insert data + }, + version: HeimdallToolsVersion, + statistics: { + duration: null, //Insert data + }, + profiles: [ + { + name: "", //Insert data + title: null, //Insert data + version: null, //Insert data + maintainer: null, //Insert data + summary: null, //Insert data + license: null, //Insert data + copyright: null, //Insert data + copyright_email: null, //Insert data + supports: [], //Insert data + attributes: [], //Insert data + depends: [], //Insert data + groups: [], //Insert data + status: "loaded", //Insert data + controls: [ + { + key: "id", + tags: {}, //Insert data + descriptions: [], //Insert data + refs: [], //Insert data + source_location: {}, //Insert data + title: null, //Insert data + id: "", //Insert data + desc: null, //Insert data + impact: 0, //Insert data + code: null, //Insert data + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, //Insert data + code_desc: "", //Insert data + message: null, //Insert data + run_time: null, //Insert data + start_time: "", //Insert data + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{ name: "", data: _.omit([]) }], //Insert service name and mapped fields to be removed + ...(this.withRaw && { raw: data }), + }; + }, + }, + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw; + } +} +``` + +::: + +3. Export your mapper class created in the previous steps by specifying its export in the index.ts file. Add the following line: + +``` +export * from './src/{YOUR-EXPORT-NAME-HERE}-mapper'; +``` + +### Sample File + +Next, we need to add a sample file for the mapper to ingest when running unit tests on it. + +1. Create a new directory named `{YOUR-EXPORT-NAME-HERE}_mapper` under the `sample_jsons` directory in `hdf-converters`. Create another directory named `sample_input_report` in the directory you just made. The directory structure should look like this: + +``` ++-- sample_jsons +| +-- {YOUR-EXPORT-NAME-HERE}-mapper +| | +-- sample_input_report +``` + +2. Place your sample export under the `sample_input_report` directory. Your sample export should be genericized to avoid any leaking of sensitive information. The directory structure should now look like this: + +``` ++-- sample_jsons +| +-- {YOUR-EXPORT-NAME-HERE}-mapper +| | +-- sample_input_report +| | | +-- {YOUR-SAMPLE-EXPORT} +``` + +### Regression Testing + +Now that we have a sample file, we can now add some regression tests which automatically test our mapper to ensure that it is producing readable and correct OHDF file outputs. + +1. Create a blank TypeScript file under the `test/mappers/forward` directory in `hdf-converters`. It should be named: + +``` +{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts +``` + +2. Select the appropriate mapper test skeleton (see below) for your export type. Place it in the file created in step 1. Replace names (`SKELETON` by default) as necessary. + +::: details JSON Mapper Test Skeleton + +```typescript +import fs from "fs"; +import { SKELETONMapper } from "../../../src/SKELETON-mapper"; +import { omitVersions } from "../../utils"; + +describe("SKELETON_mapper", () => { + it("Successfully converts SKELETON targeted at a local/cloned repository data", () => { + const mapper = new SKELETONMapper( + fs.readFileSync( + "sample_jsons/SKELETON_mapper/sample_input_report/SKELETON.json", + { encoding: "utf-8" } + ) + ); + + // fs.writeFileSync( + // 'sample_jsons/SKELETON_mapper/SKELETON-hdf.json', + // JSON.stringify(mapper.toHdf(), null, 2) + // ); + + expect(omitVersions(mapper.toHdf())).toEqual( + omitVersions( + JSON.parse( + fs.readFileSync("sample_jsons/SKELETON_mapper/SKELETON-hdf.json", { + encoding: "utf-8", + }) + ) + ) + ); + }); +}); + +describe("SKELETON_mapper_withraw", () => { + it("Successfully converts withraw flagged SKELETON targeted at a local/cloned repository data", () => { + const mapper = new SKELETONMapper( + fs.readFileSync( + "sample_jsons/SKELETON_mapper/sample_input_report/SKELETON.json", + { encoding: "utf-8" } + ), + true + ); + + // fs.writeFileSync( + // 'sample_jsons/SKELETON_mapper/SKELETON-hdf-withraw.json', + // JSON.stringify(mapper.toHdf(), null, 2) + // ); + + expect(omitVersions(mapper.toHdf())).toEqual( + omitVersions( + JSON.parse( + fs.readFileSync( + "sample_jsons/SKELETON_mapper/SKELETON-hdf-withraw.json", + { + encoding: "utf-8", + } + ) + ) + ) + ); + }); +}); +``` + +::: + +### Fingerprinting + +OHDF Converters has a fingerprinting service that detects a security tool data format and automatically applies the correct mapper to convert it to OHDF. To enable this feature, we need to explicitly declare keywords unique to the security tool data format as follows: + +1. Go to the file `report_intake.ts` under the `heimdall2/apps/frontend/src/store` directory. + +2. Import your mapper file. You should be able to add the name of your mapper class to a pre-existing import statement pointing at `hdf-converters` as follows: + +```typescript +import { + ASFFResults as ASFFResultsMapper, + BurpSuiteMapper, + ... + {YOUR-MAPPER-CLASS-HERE} +} from '@mitre/hdf-converters'; +``` + +3. Instantiate your mapper class in the `convertToHdf` switch block. Add the following lines: + +```typescript +case '{YOUR-EXPORT-SERVICE-NAME-HERE}': + return new {YOUR-MAPPER-CLASS-HERE}(convertOptions.data).toHdf(); +``` + +4. Navigate to the file `fingerprinting.ts` in the `src/utils` directory in `hdf-converters`. Add keywords that are unique to your sample export to the `fileTypeFingerprints` variable. It should be formatted as follows: + +```typescript +export const fileTypeFingerprints = { + asff: ['Findings', 'AwsAccountId', 'ProductArn'], + ... + {YOUR-EXPORT-SERVICE-NAME-HERE}: [{UNIQUE KEYWORDS AS STRINGS}] +}; +``` + +## Mapper Implementation + +With the necessary files now set up, we can begin the actual creation of the OHDF mapper using the skeleton mapper base in the `{YOUR-EXPORT-NAME-HERE}-mapper.ts` file. The skeleton mapper and the `base-converter` class have been designed to provide the base functionality needed for \*-to-HDF mapper generation. For most developers, mapper creation will be limited to assigning objects from the export structure to correlating attributes in the mapper according to the mappings they developed earlier. + +::: warning File Processing +Certain security services produce exports which are not immediately usable by the skeleton mapper. In such case, pre-processing on the export and or post-processing on the generated OHDF file is necessary in order to ensure compatibility. +::: + +While developing the mapper, it's useful to occasionally check on the generated OHDF file to check that the mapper is working as intended. You can do this by starting a local instance of Heimdall with the following command: + +```shell +yarn start:dev +``` + +Note that the `yarn start:dev` command will dynamically rebuild the application upon changes to the Heimdall frontend. However, if you make any changes to OHDF-Converters, you will have to restart the command entirely. + +Import your source data and then export it as an OHDF JSON to check what your mapper is actually mapping. + +### Mapper Demo - GoSec + +This section is a demonstration on implementing an OHDF mapper for GoSec, assuming that the [appropriate file set up for the mapper](#file-set-up) has been performed. + +Here is our developed mapping for GoSec for reference: + +::: details GoSec-to-OHDF Mapping + +```typescript +{ + platform: { // We fill in Heimdall for the platform as it handles the generation of this OHDF file + name: 'Heimdall Tools', + release: HeimdallToolsVersion + }, + version: HeimdallToolsVersion, // See 'platform' reasoning + statistics: {}, // Not enough info to fill + profiles: [ + { + name: 'Gosec scanner', // We know that this report is generated from GoSec + version: GosecVersion, // Version of GoSec instance + sha256: '', // Leave it empty as OHDF Converters will generate one for us + title: 'gosec', // We know that this report is generated from GoSec + supports: [], // Not enough info to fill + attributes: [], // Not enough info to fill + groups: [], // Not enough info to fill + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + desc: '', // Not enough info to fill + impact: 0.5, // Have no solid information on impact of security issue, so we default to 0.5 + refs: [], // Not enough info to fill + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + source_location: {}, // Not enough info to fill + results: [ + { + status: 'failed', // The security scan only reports failed requirements, so all findings we receive get fail statuses + code_desc: Issues.code, // The code failing the requirement test + message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred + start_time // Not enough info to fill + } + ] + }, + ], + status: 'loaded' // Give loaded status to denote that profile is loaded by OHDF Converters + }, + ], + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } + ], + raw + } +} +``` + +::: + +::: details GoSec Annotated Source Data + +```json +{ + // Purpose: Go compilation errors + // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical + "Golang errors": {}, + // Purpose: Container for identified security issues + // Recording: Requirements - This entity records all identified security issues in a Go source code + "Issues": [ + { + // Purpose: The severity of the identified issue + // Recording: Requirements - This is specifically related to the severity level of the requirement + "severity": "MEDIUM", + // Purpose: How sure that the identified issue if applicable to this source code + // Recording: Requirements testing - This field gives the applicability of the issue after source code testing + "confidence": "HIGH", + // Purpose: The associated CWE for the security issue + // Recording: Requirements - This gives the associated CWE for the security issue + "cwe": { + "id": "22", + "url": "https://cwe.mitre.org/data/definitions/22.html" + }, + // Purpose: The internal GoSec ID for the security issue + // Recording: Requirements - This gives an ID for the security issue + "rule_id": "G304", + // Purpose: Explanation of the security issue + // Recording: Requirements - This explains the security issue + "details": "Potential file inclusion via variable", + // Purpose: The offending file + // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing + "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", + // Purpose: The offending code + // Recording: Requirement testing - This specifies the code that fails the requirement after source code testing + "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", + // Purpose: The line number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "line": "83", + // Purpose: The column number of the offending code + // Recording: Requirement testing - This field specifies the location of the failing code + "column": "14", + // Purpose: Whether this security issue should be ignored + // Recording: Requirements - Specifies whether this security issue should be ignored + "nosec": false, + // Purpose: The supression level for info on the security issue + // Recording: Requirements - Specifies the info suppression level of the security issue + "suppressions": null + } + ], + // Purpose: The statistics of the GoSec scan on the source code + // Recording: Metadata - Info on the scan itself + "Stats": { + "files": 199, + "lines": 12401, + "nosec": 0, + "found": 7 + }, + // Purpose: The version of the GoSec instance currently running + // Recording: Metadata - Info on the scan itself + "GosecVersion": "dev" +} +``` + +::: + +Mapper creation has been streamlined to be as simple as possible for a developer. Most of the work involves simple references to the object path for a field in the source data as so: + +```typescript +version: { + path: "GosecVersion"; +} +``` + +This primarily applies in cases where the field is simply carried over. Some fields from the source data need to be processed or transformed in some way, which will be elaborated upon later. + +#### Unfilled/Omitted and Hard Coded Fields + +First, let's assign mappings which are unfilled/omitted or are not dependent on the source data (i.e., hard coded data). This include fields like our mappings for `profiles.name` and `profiles.sha256` + +::: details GoSec-to-OHDF Mapper + +```typescript +import { ExecJSON } from "inspecjs"; +import _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, +} from "./base-converter"; + +export class GoSecMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: "Gosec scanner", + title: "gosec", + version: null, //Insert data + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + key: "id", + tags: {}, //Insert data + refs: [], + source_location: {}, + title: null, //Insert data + id: "", //Insert data + desc: "", + impact: 0.5, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: "", //Insert data + message: null, //Insert data + start_time: "", + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{ name: "", data: _.omit([]) }], //Insert service name and mapped fields to be removed + ...(this.withRaw && { raw: data }), + }; + }, + }, + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw; + } +} +``` + +::: + +::: details Remaining GoSec-to-OHDF Mapping + +```typescript +{ + profiles: [ + { + version: GosecVersion, // Version of GoSec instance + controls: [ + { + id: Issues.rule_id, // ID of the requirement + title: Issues.details, // Human readable title for the requirement + tags: { + Issues.cwe // Associated CWE for the requirement + Issues.severity, // Severity of the requirement + Issues.confidence, // Applicability of the requirement + Issues.nosec, // Whether to ignore the requirement + Issues.suppressions // Info suppression level of the requirement + }, + results: [ + { + code_desc: Issues.code, // The code failing the requirement test + message: Issues.file + Issues.line + Issues.column // All materials describing where the issue occurred + } + ] + }, + ] + }, + ], + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } + ], + raw + } +} +``` + +::: + +#### Simple Portable Fields + +Next, let's look at the fields which can be just simply be directly ported over from the source data like `GosecVersion`. To do this, we just need to invoke the `path` keyword from `base-converter` and feed the direct JSON object path as a value like so: + +```typescript +version: { + path: "GosecVersion"; +} +``` + +For nested fields (i.e., fields requiring traversal through parent fields), we need to have the mapper traverse into the level containing the fields we want to access. Think of this as a similar process as using `cd` to traverse through a directory to access a file. For example, if we can allow the access of fields using `path` in the `Issues` superfield in the source data as follows: + +```typescript +path: "Issues"; +``` + +Let's put this into practice and start implementing the mappings for simple fields that don't require transformation or processing: + +::: details GoSec-to-OHDF Mapper + +```typescript +import { ExecJSON } from "inspecjs"; +import _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, +} from "./base-converter"; + +export class GoSecMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: "Gosec scanner", + title: "gosec", + version: { path: "GosecVersion" }, + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + path: "Issues", + key: "id", + tags: { + cwe: { path: "cwe" }, + nosec: { path: "nosec" }, + suppressions: { path: "suppressions" }, + severity: { path: "severity" }, + confidence: { path: "confidence" }, + }, + refs: [], + source_location: {}, + title: { path: "details" }, + id: { path: "rule_id" }, + desc: "", + impact: 0.5, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: { path: "code" }, + message: null, //Insert data + start_time: "", + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{ name: "", data: _.omit([]) }], //Insert service name and mapped fields to be removed + ...(this.withRaw && { raw: data }), + }; + }, + }, + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw; + } +} +``` + +::: + +::: details Remaining GoSec-to-OHDF Mapping + +```typescript +{ + profiles: [ + { + controls: [ + { + results: [ + { + message: Issues.file + Issues.line + Issues.column // All materials describing where the issue occurred + } + ] + }, + ] + }, + ], + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } + ], + raw + } +} +``` + +::: + +#### Transformed/Processed Fields + +Finally, let's look at fields that require some level of processing before we can use them in the OHDF mapper. + +The fields like `Issues.file`, `Issues.line`, and `Issues.column` need to be combined to make a coherent locational message. We can combine them using a simple function that concatenates them together. The function to do this is provided: + +```typescript +function formatMessage(input: Record): string { + return `${_.get(input, "file")}, line:${_.get(input, "line")}, column:${_.get( + input, + "column" + )}`; +} +``` + +This function just pulls the three fields and joins them into a single string. + +To invoke this, we can use the `transformer` keyword and feed the function as a value for the transformer to invoke. This is implemented as follows: + +::: details GoSec-to-OHDF Mapper + +```typescript +import { ExecJSON } from "inspecjs"; +import _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, +} from "./base-converter"; + +function formatMessage(input: Record): string { + return `${_.get(input, "file")}, line:${_.get(input, "line")}, column:${_.get( + input, + "column" + )}`; +} + +export class GoSecMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: "Gosec scanner", + title: "gosec", + version: { path: "GosecVersion" }, + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + path: "Issues", + key: "id", + tags: { + cwe: { path: "cwe" }, + nosec: { path: "nosec" }, + suppressions: { path: "suppressions" }, + severity: { path: "severity" }, + confidence: { path: "confidence" }, + }, + refs: [], + source_location: {}, + title: { path: "details" }, + id: { path: "rule_id" }, + desc: "", + impact: 0.5, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: { path: "code" }, + message: { transformer: formatMessage }, + start_time: "", + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{ name: "", data: _.omit([]) }], //Insert service name and mapped fields to be removed + ...(this.withRaw && { raw: data }), + }; + }, + }, + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw; + } +} +``` + +::: + +::: details Remaining GoSec-to-OHDF Mapping + +```typescript +{ + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } + ], + raw + } +} +``` + +::: + +We can also combine keywords such as using `path` to traverse to a particular field and then apply a function using `transformer`. For example, we can target the `Issues.cwe` field specifically and apply the following function to create corresponding NIST 800-53s: + +```typescript +import { CweNistMapping } from "./mappings/CweNistMapping"; + +const CWE_NIST_MAPPING = new CweNistMapping(); +const DEFAULT_NIST_TAG = ["SI-2", "RA-5"]; + +function nistTag(input: Record): string[] { + const cwe = [`${_.get(input, "id")}`]; + return CWE_NIST_MAPPING.nistFilter(cwe, DEFAULT_NIST_TAG); +} +``` + +We can then correlate it with a `profiles.controls.tags.nist` field in the OHDF mapper as so: + +::: details GoSec-to-OHDF Mapper + +```typescript +import { ExecJSON } from "inspecjs"; +import _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, +} from "./base-converter"; +import { CweNistMapping } from "./mappings/CweNistMapping"; + +const CWE_NIST_MAPPING = new CweNistMapping(); +const DEFAULT_NIST_TAG = ["SI-2", "RA-5"]; + +function nistTag(input: Record): string[] { + const cwe = [`${_.get(input, "id")}`]; + return CWE_NIST_MAPPING.nistFilter(cwe, DEFAULT_NIST_TAG); +} + +function formatMessage(input: Record): string { + return `${_.get(input, "file")}, line:${_.get(input, "line")}, column:${_.get( + input, + "column" + )}`; +} + +export class GoSecMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: "Gosec scanner", + title: "gosec", + version: { path: "GosecVersion" }, + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + path: "Issues", + key: "id", + tags: { + nist: { + path: "cwe", + transformer: nistTag, + }, + cwe: { path: "cwe" }, + nosec: { path: "nosec" }, + suppressions: { path: "suppressions" }, + severity: { path: "severity" }, + confidence: { path: "confidence" }, + }, + refs: [], + source_location: {}, + title: { path: "details" }, + id: { path: "rule_id" }, + desc: "", + impact: 0.5, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: { path: "code" }, + message: { transformer: formatMessage }, + start_time: "", + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [{ name: "", data: _.omit([]) }], //Insert service name and mapped fields to be removed + ...(this.withRaw && { raw: data }), + }; + }, + }, + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw; + } +} +``` + +::: + +::: details Remaining GoSec-to-OHDF Mapping + +```typescript +{ + passthrough: { + auxiliary_data: [ + { // Go source data compilation errors; Stats on GoSec scan + name: 'Gosec', + data: Golang errors, Stats + } + ], + raw + } +} +``` + +::: + +For the remaining fields that we want to place in `passthrough`, we need to use the [lodash library](https://lodash.com/docs/) to preserve the field in its entirety. In particular, we will use the `_.get(OBJECT, FIELD)` command to pull a field from the source data object. + +::: details GoSec-to-OHDF Mapper + +```typescript +import { ExecJSON } from "inspecjs"; +import _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, +} from "./base-converter"; +import { CweNistMapping } from "./mappings/CweNistMapping"; + +const CWE_NIST_MAPPING = new CweNistMapping(); +const DEFAULT_NIST_TAG = ["SI-2", "RA-5"]; + +function nistTag(input: Record): string[] { + const cwe = [`${_.get(input, "id")}`]; + return CWE_NIST_MAPPING.nistFilter(cwe, DEFAULT_NIST_TAG); +} + +function formatMessage(input: Record): string { + return `${_.get(input, "file")}, line:${_.get(input, "line")}, column:${_.get( + input, + "column" + )}`; +} + +export class GoSecMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: "Gosec scanner", + title: "gosec", + version: { path: "GosecVersion" }, + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + path: "Issues", + key: "id", + tags: { + nist: { + path: "cwe", + transformer: nistTag, + }, + cwe: { path: "cwe" }, + nosec: { path: "nosec" }, + suppressions: { path: "suppressions" }, + severity: { path: "severity" }, + confidence: { path: "confidence" }, + }, + refs: [], + source_location: {}, + title: { path: "details" }, + id: { path: "rule_id" }, + desc: "", + impact: 0.5, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: { path: "code" }, + message: { transformer: formatMessage }, + start_time: "", + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [ + { + name: "Gosec", + data: { + "Golang errors": _.get(data, "Golang errors"), + Stats: _.get(data, "Stats"), + }, + }, + ], + ...(this.withRaw && { raw: data }), + }; + }, + }, + }; + constructor(exportJson: string, withRaw = false) { + super(JSON.parse(exportJson), true); + this.withRaw = withRaw; + } +} +``` + +::: + +Now we have a fully implemented GoSec-to-OHDF mapper. + +### Mapper Demo - DbProtect + +This section is a demonstration for implementing an OHDF mapper that handles XML-based source data, namely DbProtect. As in the previous section, we assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. + +Here is our developed mapping for DbProtect for reference: + +::: details DbProtect-to-OHDF Mapping + +```typescript +{ + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id + }, + version: HeimdallToolsVersion, + statistics: { + duration + }, + profiles: [ + { + name: 'Policy', + version, + sha256, + title: 'Job Name', + maintainer, + summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'Check ID', // ID of the requirement + title: 'Check', + desc: ['Task', 'Check Category'], + descriptions, + impact: 'Risk DV', + refs, + tags: { + nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + cci: DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS + }, + code, + source_location, + results: [ + { + status: 'Result Status', // The result of the scan for that particular control + code_desc: 'Details', + message, + run_time, + start_time: 'Date' // Some indication of when the scan was run + } + ] + }, + ], + status: 'loaded' + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details DbProtect Annotated Source Data + +```xml + + + + + + + + + + + + + + + + + + + + + + + + + TEST ORGANIZATION (Local DBP server) + + + Audit + + + Microsoft SQL Server + + + CONDS181 + + + 10.0.10.204, 1433, MSSQLSERVER + + + Heimdall Test scan report generation + + + DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) + + + Fact + + + Improper Access Controls + + + Medium + + + 2986 + + + Schema ownership + + + Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole + + + Feb 18 2021 15:57 + + ... + + +``` + +::: + +As in the previous GoSec example, most of the work involves simple references to the object path for a field in the source data. For example: + +```typescript +title: { + path: "Check"; +} +``` + +Again, some fields from the source data need to be processed or transformed in some way, which will be elaborated upon later. + +#### Unfilled/Omitted and Hard Coded Fields + +First, let's assign mappings which are unfilled/omitted or are not dependent on the source data (i.e., hard coded data). This include fields like our mappings for `platform.name` and `profiles.sha256`. Note that for our tags, we use the global method in the Heimdall repo, `getCCIsForNISTTags`, as well as the global constant `DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS`. We can also just directly put the source data into the passthrough. Also note the `compileFindings` function we wrote to deal with the strange structure of the XML, which has metadata correlated with each row in the data field. No need to worry about this function for now - just think of it as a way of assigning the metadata keys to each data row explicitly, so that our base converter has a way to easily access fields and know what they are. + +::: details DbProtect-to-OHDF Mapper + +```typescript +import { ExecJSON } from "inspecjs"; +import * as _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, + parseXml, +} from "./base-converter"; + +function compileFindings( + input: Record +): Record { + const keys = _.get(input, "dataset.metadata.item"); + const findings = _.get(input, "dataset.data.row"); + + let output: unknown[] = []; + + if (Array.isArray(keys) && Array.isArray(findings)) { + const keyNames = keys.map((element: Record): string => { + return _.get(element, "name") as string; + }); + output = findings.map((element: Record) => { + return Object.fromEntries( + keyNames.map(function (name: string, i: number) { + return [name, _.get(element, `value[${i}]`)]; + }) + ); + }); + } + return Object.fromEntries([["data", output]]); +} + +export class DBProtectMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: {}, + title: {}, + summary: {}, + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + key: "id", + tags: { + nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + cci: getCCIsForNISTTags(DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS), + }, + refs: [], + source_location: {}, + title: {}, + id: {}, + desc: {}, + impact: {}, + code: {}, + results: [ + { + status: {}, + code_desc: {}, + start_time: {}, + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { ...(this.withRaw && { raw: data }) }; + }, + }, + }; + constructor(dbProtectXml: string, withRaw = false) { + super(compileFindings(parseXml(dbProtectXml))); + this.withRaw = withRaw; + } +} +``` + +::: + +::: details Remaining DbProtect-to-OHDF Mapping + +```typescript +{ + profiles: [ + { + name: "Policy", + title: "Job Name", + maintainer, + summary: [ + "Organization", + "Asset", + "Asset Type", + "IP Address, Port, Instance", + ], + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: "Check ID", // ID of the requirement + title: "Check", + desc: ["Task", "Check Category"], + descriptions, + impact: "Risk DV", + refs, + code, + source_location, + results: [ + { + status: "Result Status", // The result of the scan for that particular control + code_desc: "Details", + message, + run_time, + start_time: "Date", // Some indication of when the scan was run + }, + ], + }, + ], + }, + ]; +} +``` + +::: + +#### Simple Portable Fields + +Next, let's look at the fields which can be just simply be directly ported over from the source data like `Policy`. To do this, we just need to invoke the `path` keyword from `base-converter` and feed the direct JSON object path as a value like so: + +```typescript +name: { + path: "data.[0].Policy"; +} +``` + +Note that in this example, we must call the path with `data.[0]`, since even though the Policy is the same for all data rows, we still must specify an element to extract the data from. + +Let's put this into practice and start implementing the mappings for simple fields that don't require transformation or processing: + +::: details DbProtect-to-OHDF Mapper + +```typescript +import { ExecJSON } from "inspecjs"; +import * as _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, + parseXml, +} from "./base-converter"; + +function compileFindings( + input: Record +): Record { + const keys = _.get(input, "dataset.metadata.item"); + const findings = _.get(input, "dataset.data.row"); + + let output: unknown[] = []; + + if (Array.isArray(keys) && Array.isArray(findings)) { + const keyNames = keys.map((element: Record): string => { + return _.get(element, "name") as string; + }); + output = findings.map((element: Record) => { + return Object.fromEntries( + keyNames.map(function (name: string, i: number) { + return [name, _.get(element, `value[${i}]`)]; + }) + ); + }); + } + return Object.fromEntries([["data", output]]); +} + +export class DBProtectMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: { path: "data.[0].Policy" }, + title: { path: "data.[0].Job Name" }, + summary: {}, + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + path: "data", + key: "id", + tags: { + nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + cci: getCCIsForNISTTags(DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS), + }, + refs: [], + source_location: {}, + title: { path: "Check" }, + id: {}, + desc: {}, + impact: {}, + code: {}, + results: [ + { + status: {}, + code_desc: { path: "Details" }, + start_time: { path: "Date" }, + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { ...(this.withRaw && { raw: data }) }; + }, + }, + }; + constructor(dbProtectXml: string, withRaw = false) { + super(compileFindings(parseXml(dbProtectXml))); + this.withRaw = withRaw; + } +} +``` + +::: + +::: details Remaining DbProtect-to-OHDF Mapping + +```typescript +{ + profiles: [ + { + maintainer, + summary: [ + "Organization", + "Asset", + "Asset Type", + "IP Address, Port, Instance", + ], + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: "Check ID", // ID of the requirement + desc: ["Task", "Check Category"], + descriptions, + impact: "Risk DV", + refs, + code, + source_location, + results: [ + { + status: "Result Status", // The result of the scan for that particular control + message, + run_time, + }, + ], + }, + ], + }, + ]; +} +``` + +::: + +#### Transformed/Processed Fields + +As in the previous example, there are several fields that need to be processed further. To do so, we can make use of the `transformer` field supported by the OHDF Converters library. Some simple transformers include casting the `id` field to a string, and mapping the `impact` fields properly (by creating a mapping and passing it into the `impactMapping` function in `base-converter`): + +```typescript +const IMPACT_MAPPING: Map = new Map([ + ["high", 0.7], + ["medium", 0.5], + ["low", 0.3], + ["informational", 0], +]); + +function idToString(id: unknown): string { + if (typeof id === "string" || typeof id === "number") { + return id.toString(); + } else { + return ""; + } +} +``` + +For the OHDF fields that concatenate information from multiple DbProtect fields, we must write corresponding transformers that format these strings: + +```typescript +function formatSummary(entry: unknown): string { + const text = []; + text.push(`Organization : ${_.get(entry, "Organization")}`); + text.push(`Asset : ${_.get(entry, "Check Asset")}`); + text.push(`Asset Type : ${_.get(entry, "Asset Type")}`); + text.push(`IP Address, Port, Instance : ${_.get(entry, "Asset Type")}`); + text.push( + `IP Address, Port, Instance : ${_.get( + entry, + "IP Address, Port, Instance" + )} ` + ); + return text.join("\n"); +} + +function formatDesc(entry: unknown): string { + const text = []; + text.push(`Task : ${_.get(entry, "Task")}`); + text.push(`Check Category : ${_.get(entry, "Check Category")}`); + return text.join("; "); +} +``` + +Finally, we write one more function to map the `Result Status` to the proper `ExecJSON` statuses: + +```typescript +function getStatus(input: unknown): ExecJSON.ControlResultStatus { + switch (input) { + case "Fact": + return ExecJSON.ControlResultStatus.Skipped; + case "Failed": + return ExecJSON.ControlResultStatus.Failed; + case "Finding": + return ExecJSON.ControlResultStatus.Failed; + case "Not A Finding": + return ExecJSON.ControlResultStatus.Passed; + } + return ExecJSON.ControlResultStatus.Skipped; +} +``` + +Writing out all these transformers and applying them to the mapping fed into `base-converter` looks something like this: + +:::details Full Mapper Code + +```typescript +import { ExecJSON } from "inspecjs"; +import * as _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + ILookupPath, + impactMapping, + MappedTransform, + parseXml, +} from "./base-converter"; +import { + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + getCCIsForNISTTags, +} from "./utils/global"; + +const IMPACT_MAPPING: Map = new Map([ + ["high", 0.7], + ["medium", 0.5], + ["low", 0.3], + ["informational", 0], +]); + +function compileFindings( + input: Record +): Record { + const keys = _.get(input, "dataset.metadata.item"); + const findings = _.get(input, "dataset.data.row"); + + let output: unknown[] = []; + + if (Array.isArray(keys) && Array.isArray(findings)) { + const keyNames = keys.map((element: Record): string => { + return _.get(element, "name") as string; + }); + output = findings.map((element: Record) => { + return Object.fromEntries( + keyNames.map(function (name: string, i: number) { + return [name, _.get(element, `value[${i}]`)]; + }) + ); + }); + } + return Object.fromEntries([["data", output]]); +} + +function formatSummary(entry: unknown): string { + const text = []; + text.push(`Organization : ${_.get(entry, "Organization")}`); + text.push(`Asset : ${_.get(entry, "Check Asset")}`); + text.push(`Asset Type : ${_.get(entry, "Asset Type")}`); + text.push(`IP Address, Port, Instance : ${_.get(entry, "Asset Type")}`); + text.push( + `IP Address, Port, Instance : ${_.get( + entry, + "IP Address, Port, Instance" + )} ` + ); + return text.join("\n"); +} + +function formatDesc(entry: unknown): string { + const text = []; + text.push(`Task : ${_.get(entry, "Task")}`); + text.push(`Check Category : ${_.get(entry, "Check Category")}`); + return text.join("; "); +} + +function getStatus(input: unknown): ExecJSON.ControlResultStatus { + switch (input) { + case "Fact": + return ExecJSON.ControlResultStatus.Skipped; + case "Failed": + return ExecJSON.ControlResultStatus.Failed; + case "Finding": + return ExecJSON.ControlResultStatus.Failed; + case "Not A Finding": + return ExecJSON.ControlResultStatus.Passed; + } + return ExecJSON.ControlResultStatus.Skipped; +} + +function idToString(id: unknown): string { + if (typeof id === "string" || typeof id === "number") { + return id.toString(); + } else { + return ""; + } +} + +export class DBProtectMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: { path: "data.[0].Policy" }, + title: { path: "data.[0].Job Name" }, + summary: { path: "data.[0]", transformer: formatSummary }, + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + path: "data", + key: "id", + tags: { + nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + cci: getCCIsForNISTTags(DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS), + }, + refs: [], + source_location: {}, + title: { path: "Check" }, + id: { path: "Check ID", transformer: idToString }, + desc: { transformer: formatDesc }, + impact: { + path: "Risk DV", + transformer: impactMapping(IMPACT_MAPPING), + }, + code: { + transformer: (vulnerability: Record): string => + JSON.stringify(vulnerability, null, 2), + }, + results: [ + { + status: { path: "Result Status", transformer: getStatus }, + code_desc: { path: "Details" }, + start_time: { path: "Date" }, + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { ...(this.withRaw && { raw: data }) }; + }, + }, + }; + constructor(dbProtectXml: string, withRaw = false) { + super(compileFindings(parseXml(dbProtectXml))); + this.withRaw = withRaw; + } +} +``` + +::: + +Now we have a fully implemented DbProtect-to-OHDF mapper. + +### Mapper Demo - JFrog + +This section is yet another example of implementing an OHDF mapper, namely the JFrog-Xray mapper. Again, we will assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. Because we have already gone through several examples, this section will not explain too many things in detail. The goal is to simply provide more examples for reference. + +Here is our developed mapping for JFrog-Xray for reference: + +::: details JFrog-to-OHDF Mapping + +```typescript +{ + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id + }, + version: HeimdallToolsVersion, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'data.id', // If ID empty, hash the summary + title: 'data.summary', + desc: 'component_versions.more_details', + descriptions, + impact: 'data.severity', + refs, + tags: { + nist: 'data.component_versions.more_details.cves[0].cwe', // Map to NIST + cci: 'data.component_versions.more_details.cves[0].cwe', // Map to CCI + cweid: 'data.component_versions.more_details.cves[0].cwe' + }, + code, + source_location, + results: [ + { + status: 'Failed', // All reported findings are failures + code_desc: ['data.source_comp_id', 'data.component_versions.vulnerable_versions', 'data.component_versions.fixed_versions', 'data.issue_type', 'data.provider'], + message, + run_time, + start_time + } + ] + }, + ], + status: 'loaded' + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details JFrog Source Data + +```json +{ + "total_count": 30, + "data": [ + { + "id": "", + "severity": "High", + "summary": "Acorn regexp.js Regular Expression Validation UTF-16 Surrogate Handling Infinite Loop DoS", + "issue_type": "security", + "provider": "JFrog", + "component": "acorn", + "source_id": "npm://acorn", + "source_comp_id": "npm://acorn:5.7.3", + "component_versions": { + "id": "acorn", + "vulnerable_versions": [ + "5.5.0 ≤ Version < 5.7.4", + "6.0.0 ≤ Version < 6.4.1", + "7.0.0", + "7.1.0" + ], + "fixed_versions": ["5.7.4", "6.4.1", "7.1.1"], + "more_details": { + "cves": [ + { + "cvss_v2": "7.1/AV:N/AC:M/Au:N/C:N/I:N/A:C", + "cvss_v3": "7.5/CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H" + } + ], + "description": "Acorn contains an infinite loop condition in regexp.js that is triggered when handling UTF_16 surrogates while validating regular expressions. This may allow a context-dependent attacker to hang a process using the library.", + "provider": "JFrog" + } + }, + "edited": "2020-11-03T19:30:42-05:00" + } + ] +} +``` + +::: + +We will now go over the mapper code that allows us to shape this data properly. Firstly, let us handle the ID. Sometimes, JFrog source files will not have an ID field. In this case, it is appropriate to generate a hash based on the `summary` as follows: + +```typescript +function hashId(vulnerability: unknown): string { + if (_.get(vulnerability, "id") === "") { + return generateHash( + (_.get(vulnerability, "summary") as unknown as string).toString(), + "md5" + ); + } else { + return _.get(vulnerability, "id") as unknown as string; + } +} +``` + +As with most mappers, we must also define an impact mapping: + +```typescript +const IMPACT_MAPPING: Map = new Map([ + ["high", 0.7], + ["medium", 0.5], + ["low", 0.3], +]); +``` + +Recall that we wanted to format the `desc` field based on the data in the source file's `component_versions.more_details`. We can write a simple transformer function to concatenate all these keys: + +```typescript +function formatDesc(vulnerability: unknown): string { + const text = []; + if (_.has(vulnerability, "description")) { + text.push( + (_.get(vulnerability, "description") as unknown as string).toString() + ); + } + if (_.has(vulnerability, "cves")) { + const re1 = /":/gi; + const re2 = /,/gi; + text.push( + `cves: ${JSON.stringify(_.get(vulnerability, "cves")) + .replace(re1, '"=>') + .replace(re2, ", ")}` + ); + } + return text.join("
"); +} +``` + +We also must properly handle the mappings to NIST and CCI tags. Luckily, we can make use of the library's existing mappings, as well as an existing global function called `getCCIsForNISTTags()` in `global.ts`. + +```typescript +const CWE_PATH = "component_versions.more_details.cves[0].cwe"; +const CWE_NIST_MAPPING = new CweNistMapping(); + +function nistTag(identifier: Record): string[] { + const identifiers: string[] = []; + if (Array.isArray(identifier)) { + identifier.forEach((element) => { + if (element.split("CWE-")[1]) { + identifiers.push(element.split("CWE-")[1]); + } + }); + } + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} +``` + +Finally, we can implement the transformer function for the `code_desc`. Some of these fields are optional, so it is important to implement a base case to ensure our `code_desc` outputs are all consistent. + +```typescript +function formatCodeDesc(vulnerability: unknown): string { + const codeDescArray: string[] = []; + const re = /,/gi; + if (_.has(vulnerability, "source_comp_id")) { + codeDescArray.push( + `source_comp_id : ${_.get(vulnerability, "source_comp_id")}` + ); + } else { + codeDescArray.push("source_comp_id : "); + } + if (_.has(vulnerability, "component_versions.vulnerable_versions")) { + codeDescArray.push( + `vulnerable_versions : ${JSON.stringify( + _.get(vulnerability, "component_versions.vulnerable_versions") + )}` + ); + } else { + codeDescArray.push("vulnerable_versions : "); + } + if (_.has(vulnerability, "component_versions.fixed_versions")) { + codeDescArray.push( + `fixed_versions : ${JSON.stringify( + _.get(vulnerability, "component_versions.fixed_versions") + )}` + ); + } else { + codeDescArray.push("fixed_versions : "); + } + if (_.has(vulnerability, "issue_type")) { + codeDescArray.push(`issue_type : ${_.get(vulnerability, "issue_type")}`); + } else { + codeDescArray.push("issue_type : "); + } + if (_.has(vulnerability, "provider")) { + codeDescArray.push(`provider : ${_.get(vulnerability, "provider")}`); + } else { + codeDescArray.push("provider : "); + } + return codeDescArray.join("\n").replace(re, ", "); +} +``` + +All that's left is to incoporate all these functions into our `base-converter` structure, write some smaller transformer functions for the simpler data formatting tasks, and combine it all together! + +:::details Full Mapper Code + +```typescript +import { ExecJSON } from "inspecjs"; +import * as _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + generateHash, + ILookupPath, + impactMapping, + MappedTransform, +} from "./base-converter"; +import { CweNistMapping } from "./mappings/CweNistMapping"; +import { + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + getCCIsForNISTTags, +} from "./utils/global"; + +// Constants +const IMPACT_MAPPING: Map = new Map([ + ["high", 0.7], + ["medium", 0.5], + ["low", 0.3], +]); + +const CWE_PATH = "component_versions.more_details.cves[0].cwe"; + +const CWE_NIST_MAPPING = new CweNistMapping(); + +// Transformation Functions +function hashId(vulnerability: unknown): string { + if (_.get(vulnerability, "id") === "") { + return generateHash( + (_.get(vulnerability, "summary") as unknown as string).toString(), + "md5" + ); + } else { + return _.get(vulnerability, "id") as unknown as string; + } +} +function formatDesc(vulnerability: unknown): string { + const text = []; + if (_.has(vulnerability, "description")) { + text.push( + (_.get(vulnerability, "description") as unknown as string).toString() + ); + } + if (_.has(vulnerability, "cves")) { + const re1 = /":/gi; + const re2 = /,/gi; + text.push( + `cves: ${JSON.stringify(_.get(vulnerability, "cves")) + .replace(re1, '"=>') + .replace(re2, ", ")}` + ); + } + return text.join("
"); +} +function formatCodeDesc(vulnerability: unknown): string { + const codeDescArray: string[] = []; + const re = /,/gi; + if (_.has(vulnerability, "source_comp_id")) { + codeDescArray.push( + `source_comp_id : ${_.get(vulnerability, "source_comp_id")}` + ); + } else { + codeDescArray.push("source_comp_id : "); + } + if (_.has(vulnerability, "component_versions.vulnerable_versions")) { + codeDescArray.push( + `vulnerable_versions : ${JSON.stringify( + _.get(vulnerability, "component_versions.vulnerable_versions") + )}` + ); + } else { + codeDescArray.push("vulnerable_versions : "); + } + if (_.has(vulnerability, "component_versions.fixed_versions")) { + codeDescArray.push( + `fixed_versions : ${JSON.stringify( + _.get(vulnerability, "component_versions.fixed_versions") + )}` + ); + } else { + codeDescArray.push("fixed_versions : "); + } + if (_.has(vulnerability, "issue_type")) { + codeDescArray.push(`issue_type : ${_.get(vulnerability, "issue_type")}`); + } else { + codeDescArray.push("issue_type : "); + } + if (_.has(vulnerability, "provider")) { + codeDescArray.push(`provider : ${_.get(vulnerability, "provider")}`); + } else { + codeDescArray.push("provider : "); + } + return codeDescArray.join("\n").replace(re, ", "); +} +function nistTag(identifier: Record): string[] { + const identifiers: string[] = []; + if (Array.isArray(identifier)) { + identifier.forEach((element) => { + if (element.split("CWE-")[1]) { + identifiers.push(element.split("CWE-")[1]); + } + }); + } + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} + +// Mappings +export class JfrogXrayMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: "JFrog Xray Scan", + title: "JFrog Xray Scan", + summary: "Continuous Security and Universal Artifact Analysis", + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + path: "data", + key: "id", + tags: { + cci: { + path: CWE_PATH, + transformer: (identifier: Record) => + getCCIsForNISTTags(nistTag(identifier)), + }, + nist: { + path: CWE_PATH, + transformer: nistTag, + }, + cweid: { path: CWE_PATH }, + }, + refs: [], + source_location: {}, + id: { transformer: hashId }, + title: { path: "summary" }, + desc: { + path: "component_versions.more_details", + transformer: formatDesc, + }, + impact: { + path: "severity", + transformer: impactMapping(IMPACT_MAPPING), + }, + code: { + transformer: (vulnerability: Record): string => { + return JSON.stringify(vulnerability, null, 2); + }, + }, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: { transformer: formatCodeDesc }, + start_time: "", + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [ + { + name: "JFrog Xray", + data: _.pick(data, ["total_count"]), + }, + ], + ...(this.withRaw && { raw: data }), + }; + }, + }, + }; + constructor(xrayJson: string, withRaw = false) { + super(JSON.parse(xrayJson), true); + this.withRaw = withRaw; + } +} +``` + +::: + +Now we have a fully implemented JFrog-to-OHDF mapper. + +### Mapper Demo - SARIF + +Here is one last example of implementing an OHDF mapper - the SARIF mapper. As in previous examples, we will assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. Like with the JFrog example, we will not be going into too much detail regarding the mapping itself. The goal is to simply provide more examples for reference. + +Here is our developed mapping for SARIF for reference: + +::: details SARIF-to-OHDF Mapping + +```typescript +{ + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id + }, + version: HeimdallToolsVersion, + statistics: { + duration + }, + profiles: [ + { + name, + version: 'version', + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'results.ruleId', // If ID empty, hash the summary + title: 'results.message.text', + desc: 'results.message.text', + descriptions, + impact: 'results.level', + refs, + tags: { + nist: 'results.message.text', // Map to NIST + cci: 'results.message.text', // Map to CCI + cwe: 'results.message.text' + }, + code, + source_location: ['results.locations[0].physicalLocation.artifactLocation.uri', 'results.locations[0].physicalLocation.region.startLine'], + results: [ + { + status: 'Failed', // All reported findings are failures + code_desc: 'results.locations[0].physicalLocation', + message, + run_time, + start_time + } + ] + }, + ], + status: 'loaded' + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details SARIF Source Data + +```json +{ + "$schema": "https://schemastore.azurewebsites.net/schemas/json/sarif-2.1.0-rtm.5.json", + "version": "2.1.0", + "runs": [ + { + "results": [ + { + "ruleId": "FF1014", + "level": "error", + "message": { + "text": "buffer/gets: Does not check for buffer overflows (CWE-120, CWE-20)." + }, + "locations": [ + { + "physicalLocation": { + "artifactLocation": { + "uri": "test/test-patched.c", + "uriBaseId": "SRCROOT" + }, + "region": { + "startLine": 36, + "startColumn": 2, + "endColumn": 10, + "snippet": { + "text": " gets(f);" + } + } + } + } + ], + "fingerprints": { + "contextHash/v1": "6a5bb383fb44030b0d9428b17359e94ba3979bc1ce702be450427f85592c649a" + }, + "rank": 1 + } + ] + } + ] +} +``` + +::: + +First, let us define some common constants that might help us with our code. + +```typescript +const MESSAGE_TEXT = "message.text"; +const CWE_NIST_MAPPING = new CweNistMapping(); +``` + +We will now outline the `IMPACT_MAPPING` for the SARIF mapper: + +```typescript +const IMPACT_MAPPING: Map = new Map([ + ["error", 0.7], + ["warning", 0.5], + ["note", 0.3], +]); + +function impactMapping(severity: unknown): number { + if (typeof severity === "string" || typeof severity === "number") { + return IMPACT_MAPPING.get(severity.toString().toLowerCase()) || 0.1; + } else { + return 0.1; + } +} +``` + +Now, note that we will need to extract the CWEs from the message text, as well as map them to the proper NIST tags. For the CCIs, we can again use the global function `getCCIsForNISTTags()`. + +```typescript +function extractCwe(text: string): string[] { + let output = text.split("(").slice(-1)[0].slice(0, -2).split(", "); + if (output.length === 1) { + output = text.split("(").slice(-1)[0].slice(0, -2).split("!/"); + } + return output; +} +function nistTag(text: string): string[] { + let identifiers = extractCwe(text); + identifiers = identifiers.map((element) => element.split("-")[1]); + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} +``` + +Our last standalone transformer function will format our code description. This part is up to interpretation, but we decided to just concatenate them all with colon-separated key-value pairs + +```typescript +function formatCodeDesc(input: unknown): string { + const output = []; + output.push(`URL : ${_.get(input, "artifactLocation.uri")}`); + output.push(`LINE : ${_.get(input, "region.startLine")}`); + output.push(`COLUMN : ${_.get(input, "region.startColumn")}`); + return output.join(" "); +} +``` + +Now, all that's left is to combine our functions, write some mini-transformers for the small data formatting, and plug it all into the base converter! + +:::details Full Mapper Code + +```typescript +import { ExecJSON } from "inspecjs"; +import * as _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { BaseConverter, ILookupPath, MappedTransform } from "./base-converter"; +import { CweNistMapping } from "./mappings/CweNistMapping"; +import { + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + getCCIsForNISTTags, +} from "./utils/global"; + +const IMPACT_MAPPING: Map = new Map([ + ["error", 0.7], + ["warning", 0.5], + ["note", 0.3], +]); +const MESSAGE_TEXT = "message.text"; +const CWE_NIST_MAPPING = new CweNistMapping(); + +function extractCwe(text: string): string[] { + let output = text.split("(").slice(-1)[0].slice(0, -2).split(", "); + if (output.length === 1) { + output = text.split("(").slice(-1)[0].slice(0, -2).split("!/"); + } + return output; +} +function impactMapping(severity: unknown): number { + if (typeof severity === "string" || typeof severity === "number") { + return IMPACT_MAPPING.get(severity.toString().toLowerCase()) || 0.1; + } else { + return 0.1; + } +} +function formatCodeDesc(input: unknown): string { + const output = []; + output.push(`URL : ${_.get(input, "artifactLocation.uri")}`); + output.push(`LINE : ${_.get(input, "region.startLine")}`); + output.push(`COLUMN : ${_.get(input, "region.startColumn")}`); + return output.join(" "); +} +function nistTag(text: string): string[] { + let identifiers = extractCwe(text); + identifiers = identifiers.map((element) => element.split("-")[1]); + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} + +export class SarifMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + target_id: "Static Analysis Results Interchange Format", + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + path: "runs", + name: "SARIF", + version: { path: "$.version" }, + title: "Static Analysis Results Interchange Format", + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + path: "results", + key: "id", + tags: { + cci: { + path: MESSAGE_TEXT, + transformer: (data: string) => + getCCIsForNISTTags(nistTag(data)), + }, + nist: { path: MESSAGE_TEXT, transformer: nistTag }, + cwe: { + path: MESSAGE_TEXT, + transformer: extractCwe, + }, + }, + refs: [], + source_location: { + transformer: (control: unknown) => { + return _.omitBy( + { + ref: _.get( + control, + "locations[0].physicalLocation.artifactLocation.uri" + ), + line: _.get( + control, + "locations[0].physicalLocation.region.startLine" + ), + }, + (value) => value === "" + ); + }, + }, + title: { + path: MESSAGE_TEXT, + transformer: (text: unknown): string => { + if (typeof text === "string") { + return text.split(": ")[0]; + } else { + return ""; + } + }, + }, + id: { path: "ruleId" }, + desc: { + path: MESSAGE_TEXT, + transformer: (text: unknown): string => { + if (typeof text === "string") { + return text.split(": ")[1]; + } else { + return ""; + } + }, + }, + impact: { path: "level", transformer: impactMapping }, + code: { + transformer: (vulnerability: Record): string => + JSON.stringify(vulnerability, null, 2), + }, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: { + path: "locations[0].physicalLocation", + transformer: formatCodeDesc, + }, + + start_time: "", + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + let runsData = _.get(data, "runs"); + if (Array.isArray(runsData)) { + runsData = runsData.map((run: Record) => + _.omit(run, ["results"]) + ); + } + return { + auxiliary_data: [ + { + name: "SARIF", + data: { + $schema: _.get(data, "$schema"), + runs: runsData, + }, + }, + ], + ...(this.withRaw && { raw: data }), + }; + }, + }, + }; + constructor(sarifJson: string, withRaw = false) { + super(JSON.parse(sarifJson)); + this.withRaw = withRaw; + } +} +``` + +::: + +Now we have a fully implemented SARIF-to-OHDF mapper. diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index 961dde881..f3823a9dd 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -1,1589 +1,49 @@ --- order: 13 next: 14.md -title: Creating a Mapping -author: Charles Hu, Ryan Lin +title: Finalizing the Mapper +author: Charles Hu --- -## Mapping Introduction +## Mapper Finalization -::: note Security Tool Type -This walkthrough is targeted at converting security scans to OHDF. If your security tool provides exports that are not security scans or are APIs, contact the SAF team for further instruction on how to develop those services into an OHDF mapper. -::: +Now that we have a mapper developed that can convert files from \*-to-OHDF, we need to perform some final touches to make sure that our mapper works and can be integrated into OHDF Converters. -We begin the creation of every OHDF mapper by first planning out how we want correlate the fields in the OHDF and security tool's data format. This mapping is important for the following reasons: +### Using Regression Testing -1. It gives us a good framework for guiding how we actually implement the *-to-OHDF mapper. -2. It notifies us of potential knowledge gaps we may have of a security tool's data format. We need to close these gaps as best as we can in order to ensure that we can create field correlations that are as accurate/applicable as possible. -3. It gives us a chance to review our mapping in a format that is still human readable. -4. It helps us reduce the amount of corrections and rewrites we have to perform on the actual mapper implementation due to potential mapping errors. +Regression testing is extremely useful, as we make changes and improvements to mappers over time (for example, if we have new sample files or if the schema of a source format changes). Moreover, internal library changes, like an update to `base-converter`, or major dependency updates could change the behavior of a mapper significantly. If a particular change affects a mapping, we will need to regenerate the sample file through the following process: -As we develop the mappings in the following examples, note that we will break down and analyze the fields according to the OHDF schema structures we previously learned about (profiles, controls, and results). This is not necessarily the only or the best way to do this and you are encouraged to develop your own methods for correlating fields that work best for you. +First, we have to activate the regression testing suite that we created earlier to actually be able to automatically run and review your mapper. -::: note Use of Exported Security Tool Data -The following examples will use generated instances of exported security tool data that do not reflect the entirety of the schemas they are based on. Ideally, you will want to use the full schema when creating a mapping; however, the full schema is always not readily available. To reflect this, we will be using generated export data and will fill in missing schema data when possible. -::: +1. Uncomment out the commented out lines in the `{YOUR-SAMPLE-EXPORT}-hdf.json` file. This will allow the regression tests to automatically generate an OHDF output file whenever you run the tests. These files are needed for the tests to check the output of your mappers. The commented out lines should look similar to the following: -## Mapping Demo - GoSec - -### 1. Breaking Down the Data - -Let's first start with our GoSec sample, which you should be already familiar with: - -::: details GoSec Source Data -```json -{ - "Golang errors": {}, - "Issues": [ - { - "severity": "MEDIUM", - "confidence": "HIGH", - "cwe": { - "id": "22", - "url": "https://cwe.mitre.org/data/definitions/22.html" - }, - "rule_id": "G304", - "details": "Potential file inclusion via variable", - "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", - "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - "line": "83", - "column": "14", - "nosec": false, - "suppressions": null - } - ], - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - }, - "GosecVersion": "dev" -} -``` -::: - -We can begin our mapping process by identifying the purpose of each field in the source data. This is relatively simple in this case as we have a [formal schema for GoSec](https://github.com/securego/gosec/blob/master/issue/issue.go) that defines many of its fields. While we do this, it's also important that we try to tie back each identified purpose to the three general OHDF schema structures that we learned about earlier; that is, in addition to finding the purpose of each field, we should also ask ourselves the following: - -- Is this field recording metadata? -- Is this field recording requirements? -- Is this field recording requirement testing? - -Let's apply this to our GoSec source data. Try to find the answers to these two questions for each field yourself and then refer back to our annotated solution to check your work. - -::: details GoSec Annotated Source Data -```json -{ - // Purpose: Go compilation errors - // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical - "Golang errors": {}, - // Purpose: Container for identified security issues - // Recording: Requirements - This entity records all identified security issues in a Go source code - "Issues": [ - { - // Purpose: The severity of the identified issue - // Recording: Requirements - This is specifically related to the severity level of the requirement - "severity": "MEDIUM", - // Purpose: How sure that the identified issue if applicable to this source code - // Recording: Requirements testing - This field gives the applicability of the issue after source code testing - "confidence": "HIGH", - // Purpose: The associated CWE for the security issue - // Recording: Requirements - This gives the associated CWE for the security issue - "cwe": { - "id": "22", - "url": "https://cwe.mitre.org/data/definitions/22.html" - }, - // Purpose: The internal GoSec ID for the security issue - // Recording: Requirements - This gives an ID for the security issue - "rule_id": "G304", - // Purpose: Explanation of the security issue - // Recording: Requirements - This explains the security issue - "details": "Potential file inclusion via variable", - // Purpose: The offending file - // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing - "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", - // Purpose: The offending code - // Recording: Requirement testing - This specifies the code that fails the requirement after source code testing - "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - // Purpose: The line number of the offending code - // Recording: Requirement testing - This field specifies the location of the failing code - "line": "83", - // Purpose: The column number of the offending code - // Recording: Requirement testing - This field specifies the location of the failing code - "column": "14", - // Purpose: Whether this security issue should be ignored - // Recording: Requirements - Specifies whether this security issue should be ignored - "nosec": false, - // Purpose: The supression level for info on the security issue - // Recording: Requirements - Specifies the info suppression level of the security issue - "suppressions": null - } - ], - // Purpose: The statistics of the GoSec scan on the source code - // Recording: Metadata - Info on the scan itself - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - }, - // Purpose: The version of the GoSec instance currently running - // Recording: Metadata - Info on the scan itself - "GosecVersion": "dev" -} -``` -::: - -Note that this process is subjective and your answers may vary from ours. Don't be so quick to backtrack on your own answers, as your solutions may be as equally valid as ours. There is no objective answer to this process and what's important is that you can identify and break down the source data into useful pieces that we can correlate back to the OHDF schema. - -The purpose of this annotation is to understand the intention of the security tool that produced the source data. By breaking down the source data field by field, we can gain a better understanding of how the security tool structures its export data and intends for it to be read by a user. GoSec, for example, organizes its data by security issues because GoSec is intended for code correction and hardening. This manifests in the real world through the user reading the GoSec report issue by issue and solving them as they go along. We can use this knowledge to help guide us in both correlating the schemas and reconfiguring the structure of the source data to fit OHDF. - -### 2. Correlating the Schemas - -Now that we're familiar with the specifics of the GoSec schema, we can begin to map these fields to the OHDF schema. We'll do this by taking a field in the source data and correlating it to the most applicable OHDF schema field. While performing these correlations, it is important to account for the intention and structure of the source data schema. - -This initial mapping is informal and does not need to adhere to any programming syntax since you're probably annotating the documents by hand. The mapping process entails taking the full field path from the source data and placing it as the corresponding value for the OHDF schema field. Proper implementation of these mappings will be done later in the course. An example of such mapping is as follows: -```typescript -{ - profiles: [ - { - controls: [ - { - title: Issues.details - } - ] - } - ] -} -``` -This shows us a mapping of the field `Issues.details` from the source data to the field `profiles.controls.title` in OHDF. - -Note that sometimes every relevant field within the OHDF schema is addressed, but the source data still contains unmapped data. In such an event, it is good practice to ensure that such data is still passed through to and recorded somewhere within the OHDF schema for data preservation. In most cases, you should place such data in the `passthrough` field. - -Let's first start with an empty OHDF schema as follows: - -::: details Empty OHDF Schema -```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name, - version, - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id, - title, - desc, - descriptions, - impact, - refs, - tags, - code, - source_location, - results: [ - { - status, - code_desc, - message, - run_time, - start_time - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` -::: - -#### Mapping Version 1 - -We can begin our schema correlation by directly porting over fields from the GoSec source data that are obvious: `GosecVersion`, `Issues.rule_id`, `Issues.details`, and `Issues.cwe`. Try to map these fields youself as you follow along and refer to our solution to check your work. - -::: details Correlated Fields -OHDF | Source Data --|- -`profiles.version` | `GosecVersion` -`profiles.controls.id` | `Issues.rule_id` -`profiles.controls.title` | `Issues.details` -`profiles.controls.tags` | `Issues.cwe` -::: - -::: details OHDF Schema Mapping Ver. 1 -```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name, - version: GosecVersion, // Version of GoSec instance - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: Issues.rule_id, // ID of the requirement - title: Issues.details, // Human readable title for the requirement - desc, - descriptions, - impact, - refs, - tags: { - Issues.cwe // Associated CWE for the requirement - }, - code, - source_location, - results: [ - { - status, - code_desc, - message, - run_time, - start_time - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` -::: - -::: details Remaining GoSec Source Data -```json -{ - // Purpose: Go compilation errors - // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical - "Golang errors": {}, - // Purpose: Container for identified security issues - // Recording: Requirements - This entity records all identified security issues in a Go source code - "Issues": [ - { - // Purpose: The severity of the identified issue - // Recording: Requirements - This is specifically related to the severity level of the requirement - "severity": "MEDIUM", - // Purpose: How sure that the identified issue if applicable to this source code - // Recording: Requirements testing - This field gives the applicability of the issue after source code testing - "confidence": "HIGH", - // Purpose: The offending file - // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing - "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", - // Purpose: The offending code - // Recording: Requirement testing - This specifies the code that fails the requirement after source code testing - "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - // Purpose: The line number of the offending code - // Recording: Requirement testing - This field specifies the location of the failing code - "line": "83", - // Purpose: The column number of the offending code - // Recording: Requirement testing - This field specifies the location of the failing code - "column": "14", - // Purpose: Whether this security issue should be ignored - // Recording: Requirements - Specifies whether this security issue should be ignored - "nosec": false, - // Purpose: The supression level for info on the security issue - // Recording: Requirements - Specifies the info suppression level of the security issue - "suppressions": null - } - ], - // Purpose: The statistics of the GoSec scan on the source code - // Recording: Metadata - Info on the scan itself - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - } -} -``` -::: - -::: details Reasoning -- `version: GosecVersion`: We want to specifically place this in `version` in `profiles` because this is metadata on the actual security tool that generated these results. This is different from `version` on the top level since that refers to the platform, or the tool creating the actual OHDF file itself. - -- `id: Issues.rule_id`: `rule_id` gives us an ID used by GoSec to identify each failing requirement in the source code. - -- `title: Issues.details`: The source data doesn't provide a proper title that goes along with the failing requirement. In lieu of this, we can use `Issues.details` which does give us a human readable description of the requirement and repurpose it as a title for our control. - -- `tags: {Issues.cwe}`: `Issues.cwe` provides an association of our GoSec security issue with a known vulnerability database. This can be used in `tags` to act as metadata which can used to filter or organize controls created from these GoSec security issues. -::: - -#### Mapping Version 2 - -Next, let's look at `Issues.code`, which can be a little bit tricky. - -::: details Correlated Fields -OHDF | Source Data --|- -`profiles.controls.results.code_desc` | `Issues.code` -::: - -::: details OHDF Schema Mapping Ver. 2 ```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name, - version: GosecVersion, // Version of GoSec instance - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: Issues.rule_id, // ID of the requirement - title: Issues.details, // Human readable title for the requirement - desc, - descriptions, - impact, - refs, - tags: { - Issues.cwe // Associated CWE for the requirement - }, - code, - source_location, - results: [ - { - status, - code_desc: Issues.code, // The code failing the requirement test - message, - run_time, - start_time - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} +// fs.writeFileSync( +// 'sample_jsons/SKELETON_mapper/SKELETON-hdf.json', +// JSON.stringify(mapper.toHdf(), null, 2) +// ); ``` -::: -::: details Remaining GoSec Source Data -```json -{ - // Purpose: Go compilation errors - // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical - "Golang errors": {}, - // Purpose: Container for identified security issues - // Recording: Requirements - This entity records all identified security issues in a Go source code - "Issues": [ - { - // Purpose: The severity of the identified issue - // Recording: Requirements - This is specifically related to the severity level of the requirement - "severity": "MEDIUM", - // Purpose: How sure that the identified issue if applicable to this source code - // Recording: Requirements testing - This field gives the applicability of the issue after source code testing - "confidence": "HIGH", - // Purpose: The offending file - // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing - "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", - // Purpose: The line number of the offending code - // Recording: Requirement testing - This field specifies the location of the failing code - "line": "83", - // Purpose: The column number of the offending code - // Recording: Requirement testing - This field specifies the location of the failing code - "column": "14", - // Purpose: Whether this security issue should be ignored - // Recording: Requirements - Specifies whether this security issue should be ignored - "nosec": false, - // Purpose: The supression level for info on the security issue - // Recording: Requirements - Specifies the info suppression level of the security issue - "suppressions": null - } - ], - // Purpose: The statistics of the GoSec scan on the source code - // Recording: Metadata - Info on the scan itself - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - } -} -``` -::: - -::: details Reasoning -- `code_desc: Issues.code`: `Issues.code` refers to the source code that is explicitly failing the GoSec requirement. This does not align with our definition for `code_desc` but remember that we always aim to seek parity with the original security tool. GoSec focuses heavily on identifying a security issue and directly pinpointing where that issue occurs for immediate resolution. We want to mirror that behavior by also pinpointing where the security issue occurs at instead of providing a code description of what test went wrong. -::: - -#### Mapping Version 3 - -Next, let's look at the fields `Issues.severity`, `Issues.confidence`, `Issues.nosec`, and `Issues.suppressions`. - -::: details Correlated Fields -OHDF | Source Data --|- -`profiles.controls.tags` | `Issues.severity` -`profiles.controls.tags` | `Issues.confidence` -`profiles.controls.tags` | `Issues.nosec` -`profiles.controls.tags` | `Issues.suppressions` -::: +2. Using the terminal, `cd` into the `hdf-converters` directory and run the following command. This command will run your mapper against the sample export file in `sample_jsons` and tests to see if the output is generated as expected. However, this initial run will be used to create a baseline OHDF file for manual inspection to validate that we wrote the mapper properly and thereafter will be the comparison target for future runs to confirm that no regressions in the mapping occurred. -::: details OHDF Schema Mapping Ver. 3 -```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name, - version: GosecVersion, // Version of GoSec instance - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: Issues.rule_id, // ID of the requirement - title: Issues.details, // Human readable title for the requirement - desc, - descriptions, - impact, - refs, - tags: { - Issues.cwe // Associated CWE for the requirement - Issues.severity, // Severity of the requirement - Issues.confidence, // Applicability of the requirement - Issues.nosec, // Whether to ignore the requirement - Issues.suppressions // Info suppression level of the requirement - }, - code, - source_location, - results: [ - { - status, - code_desc: Issues.code, // The code for the requirement test - message, - run_time, - start_time - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` -::: - -::: details Remaining GoSec Source Data -```json -{ - // Purpose: Go compilation errors - // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical - "Golang errors": {}, - // Purpose: Container for identified security issues - // Recording: Requirements - This entity records all identified security issues in a Go source code - "Issues": [ - { - // Purpose: The offending file - // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing - "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", - // Purpose: The line number of the offending code - // Recording: Requirement testing - This field specifies the location of the failing code - "line": "83", - // Purpose: The column number of the offending code - // Recording: Requirement testing - This field specifies the location of the failing code - "column": "14" - } - ], - // Purpose: The statistics of the GoSec scan on the source code - // Recording: Metadata - Info on the scan itself - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - } -} +```shell +yarn run test --verbose --silent=false ./test/mappers/forward/{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts ``` -::: -::: details Reasoning -We map these fields to `tags` in the OHDF schema due to each of these fields acting as descriptive traits of the control which we can categorize and sort the controls by. +3. After running this command, you should see two files named `SKELETON-hdf.json` and `SKELETON-hdf-withraw.json` appear in the `sample_jsons/SKELETON_mapper/` directory. Check these files to make sure that the OHDF mapper output looks correct and aligns with your mapping. `SKELETON-hdf.json` should match your mapping completely, while `SKELETON-hdf-withraw.json` should also include your original source data in the OHDF output file. -It may be tempting to map `Issues.severity` to `impact`; however, it is important to note that `severity` is not the same as `impact`. These two fields are related but distinct metrics, and while conversion is possible, it is not performed in this case due to uncertainty on how to translate the two metrics properly. -::: +4. Recomment out the lines from step 1. -#### Mapping Version 4 +5. Future uses of the command in step 2 will now leverage the baseline files you generated to perform regression testing. It will compare the contents of these generated files with temporary outputs created by the mapper instance to check for field alignment. Review the test output to ensure that the tests are all passing. -Next, let's look at the fields `Issues.file`, `Issues.line`, and `Issues.column`. +### Documentation -::: details Correlated Fields -OHDF | Source Data --|- -`profiles.controls.results.message` | `Issues.file` -`profiles.controls.results.message` | `Issues.line` -`profiles.controls.results.message` | `Issues.column` -::: +Document your new mapper in the `README.md` file for `hdf-converters` under the `Supported Formats` section. It should be formatted as follows: -::: details OHDF Schema Mapping Ver. 4 -```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name, - version: GosecVersion, // Version of GoSec instance - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: Issues.rule_id, // ID of the requirement - title: Issues.details, // Human readable title for the requirement - desc, - descriptions, - impact, - refs, - tags: { - Issues.cwe // Associated CWE for the requirement - Issues.severity, // Severity of the requirement - Issues.confidence, // Applicability of the requirement - Issues.nosec, // Whether to ignore the requirement - Issues.suppressions // Info suppression level of the requirement - }, - code, - source_location, - results: [ - { - status, - code_desc: Issues.code, // The code for the requirement test - message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred - run_time, - start_time - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} +```markdown +{#}. [{YOUR-EXPORT-NAME-HERE}] - {MAPPER INPUT DESCRIPTION} ``` -::: - -::: details Remaining GoSec Source Data -```json -{ - // Purpose: Go compilation errors - // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical - "Golang errors": {}, - // Purpose: The statistics of the GoSec scan on the source code - // Recording: Metadata - Info on the scan itself - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - } -} -``` -::: - -::: details Reasoning -This is a situation similar to the one `Issues.code` is in. `Issues.file`, `Issues.line`, and `Issues.column` do not fit the definition given for `message` (i.e., they are not explanations for the test status); however, they do elaborate upon the location of the offending code snippet identified by GoSec, which we want to seek parity with. Thus, in lieu of any suitable substitutes, we instead use the locational information of the failing source code snippet as a description for the control result. -::: - -#### Mapping Version 5 - -Next, let's look at the fields `Golang errors` and `Stats`. - -::: details Correlated Fields -OHDF | Source Data --|- -`passthrough.auxiliary_data` | `Golang errors` -`passthrough.auxiliary_data` | `Stats` -::: - -::: details OHDF Schema Mapping Ver. 5 -```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name, - version: GosecVersion, // Version of GoSec instance - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: Issues.rule_id, // ID of the requirement - title: Issues.details, // Human readable title for the requirement - desc, - descriptions, - impact, - refs, - tags: { - Issues.cwe // Associated CWE for the requirement - Issues.severity, // Severity of the requirement - Issues.confidence, // Applicability of the requirement - Issues.nosec, // Whether to ignore the requirement - Issues.suppressions // Info suppression level of the requirement - }, - code, - source_location, - results: [ - { - status, - code_desc: Issues.code, // The code for the requirement test - message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred - run_time, - start_time - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { // Go source data compilation errors; Stats on GoSec scan - name: 'Gosec', - data: Golang errors, Stats - } - ], - raw - } -} -``` -::: - -::: details Reasoning -For these fields, we can place them in `passthrough` as there are no reasonably applicable fields in the OHDF schema to place them in. - -`Golang errors` is not used anywhere in `controls` as it is a description of compilation errors which would've already been flagged by GoSec as security issues if they already occurred. Thus, to avoid duplication, `Golang errors` is omitted from the main OHDF structures. -::: - -#### Mapping Version 6 - -Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. - -::: details Correlated Fields -OHDF | Source Data --|- -`platform.name` | `'Heimdall Tools'` -`platform.release` | `HeimdallToolsVersion` -`version` | `HeimdallToolsVersion` -`profiles.name` | `'Gosec scanner'` -`profiles.title` | `'gosec'` -`profiles.controls.impact` | `0.5` -`profiles.controls.results.status` | `'Failure'` -`profiles.status` | `'loaded'` -::: - -::: details OHDF Schema Mapping Ver. 6 -```typescript -{ - platform: { // We fill in Heimdall for the platform as it handles the generation of this OHDF file - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, // See 'platform' reasoning - statistics: {}, // Not enough info to fill - profiles: [ - { - name: 'Gosec scanner', // We know that this report is generated from GoSec - version: GosecVersion, // Version of GoSec instance - sha256: '', // Leave it empty as OHDF Converters will generate one for us - title: 'gosec', // We know that this report is generated from GoSec - supports: [], // Not enough info to fill - attributes: [], // Not enough info to fill - groups: [], // Not enough info to fill - controls: [ - { - id: Issues.rule_id, // ID of the requirement - title: Issues.details, // Human readable title for the requirement - desc: '', // Not enough info to fill - impact: 0.5, // Have no solid information on impact of security issue, so we default to 0.5 - refs: [], // Not enough info to fill - tags: { - Issues.cwe // Associated CWE for the requirement - Issues.severity, // Severity of the requirement - Issues.confidence, // Applicability of the requirement - Issues.nosec, // Whether to ignore the requirement - Issues.suppressions // Info suppression level of the requirement - }, - source_location: {}, // Not enough info to fill - results: [ - { - status: 'failed', // The security scan only reports failed requirements, so all findings we receive get fail statuses - code_desc: Issues.code, // The code failing the requirement test - message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred - start_time // Not enough info to fill - } - ] - }, - ], - status: 'loaded' // Give loaded status to denote that profile is loaded by OHDF Converters - }, - ], - passthrough: { - auxiliary_data: [ - { // Go source data compilation errors; Stats on GoSec scan - name: 'Gosec', - data: Golang errors, Stats - } - ], - raw - } -} -``` -::: - -::: details Reasoning -Unfilled fields are a result of a lack of sufficent information from the source data that can be used to reasonably associate with these fields. - -The reasoning for the filled fields are as follows: - -- `platform: {name: 'Heimdall Tools'}`: `platform` refers to the instance generating the OHDF file, which in this case is Heimdall2 or Heimdall Tools. - -- `platform: {release: HeimdallToolsVersion}`: Similar reasoning as above. - -- `version: HeimdallToolsVersion`: Similar reasoning as `platform` fields. - -- `name: 'Gosec scanner'`: `profiles` refers to the security tool that generated the original source data. In this case, it is the GoSec security scanning tool. - -- `title: 'gosec'`: We can give a succinct title for the profile here. - -- `impact: 0.5`: We use a default value of `0.5` since we do not have a direct mapping set up to convert the `Issues.severity` field. - -- `status: 'failed'`: GoSec only reports security vulnerabilities if it finds that the scanned source code has such security issues present. As such, every reported issue in a GoSec scan will always be a result of a failed security test. - -- `status: 'loaded'`: The status of a profile is typically `loaded` since it has been ingested and converted to OHDF. -::: - -Now we have a finalized mapping for GoSec to OHDF. - - -## Mapping Demo - DbProtect - -It is also possible to convert XML-based results formats. The OHDF library relies on `fast-xml-parser` to convert these XML files into a JSON-like format for compatibility with the base converter. Let us take a look at one such example: The DbProtect Mapper. - -### 1. Breaking Down the Data - -Let's first start with our DbProtect sample. - -::: details DbProtect Source Data -```xml - - - - - - - - - - - - - - - - - - - - - TEST ORGANIZATION (Local DBP server) - Audit - Microsoft SQL Server - CONDS181 - 10.0.10.204, 1433, MSSQLSERVER - Heimdall Test scan report generation - DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) - Fact - Improper Access Controls - Medium - 2986 - Schema ownership - Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole - Feb 18 2021 15:57 - - - TEST ORGANIZATION (Local DBP server) - Audit - Microsoft SQL Server - CONDS181 - 10.0.10.204, 1433, MSSQLSERVER - Heimdall Test scan report generation - DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) - Fact - Improper Access Controls - Medium - 2986 - Schema ownership - Schema name=db_accessadmin;Database=AppDetective;Owner name=db_accessadmin - Feb 18 2021 15:57 - - ... - - - -``` -::: - -You may notice that the metadata field maps corresponding keys to each of the values in a row of the data field. Consider ways you might try to restructure this data, but focus mainly on the purpose of each of the values for now. We will handle data restructuring in a later portion. - -Unlike with GoSec, DbProtect does not have a published schema. Thus, we must empirically reason the mapping based on our sample data. Because we are reasoning solely off of sample data, even more so than the previous example, this process is subjective and your mapping may vary from ours. One thing we can use to inform ourselves about the purpose of each field in place of a schema, however, is the metadata fields at the top of the sample. - -#### Knowledge Check - -::: details What questions do we ask ourselves when analyzing security data fields? -- What is the purpose of this field? - -- What is this field recording (metadata, requirements, requirement testing)? -::: - -Let us now apply this philosophy to our DbProtect source data. Try to find the answers to these two questions for each field yourself and then refer back to our annotated solution to check your work. - -::: details DbProtect Annotated Source Data -```xml - - - - - - - - - - - - - - - - - - - - - - - - - TEST ORGANIZATION (Local DBP server) - - - Audit - - - Microsoft SQL Server - - - CONDS181 - - - 10.0.10.204, 1433, MSSQLSERVER - - - Heimdall Test scan report generation - - - DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) - - - Fact - - - Improper Access Controls - - - Medium - - - 2986 - - - Schema ownership - - - Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole - - - Feb 18 2021 15:57 - - ... - - -``` -::: - -Note that this process is subjective and your answers may vary from ours. Don't be so quick to backtrack on your own answers, as your solutions may be as equally valid as ours. There is no objective answer to this process and what's important is that you can identify and break down the source data into useful pieces that we can correlate back to the OHDF schema. - -### 2. Correlating the Schemas - -Now that we're familiar with the specifics of the DbProtect report structure, we can begin to map these fields to the OHDF schema. - -Note that since we used an export from DbProtect and are not basing our mapping off the full schema, we will inevitably miss some fields. We can rectify this by adding them into our mapping post hoc whenever needed; however, we can still capture these missed fields without manual intervention by using our `passthrough` field to capture unmapped data. - -Let's first start with an empty OHDF schema as follows: - -::: details Empty OHDF Schema -```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name, - version, - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id, - title, - desc, - descriptions, - impact, - refs, - tags, - code, - source_location, - results: [ - { - status, - code_desc, - message, - run_time, - start_time - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` -::: - -#### Mapping Version 1 - -We can begin our schema correlation by directly porting over fields from the DbProtect source data that are obvious: `Check ID`, `Result Status`, and `Date`. Try to map these fields yourself, and refer to our solution below to check your work. - -As in the previous example, note that these mapping are informal and do not need to adhere to any programming syntax. Proper implementation of these mappings will be done later in the course. - -::: details Correlated Fields -OHDF | Source Data --|- -`profiles.controls.id` | `Check ID` -`profiles.controls.results.status` | `Result Status` -`profiles.controls.results.start_time` | `Date` -::: - -::: details OHDF Schema Mapping Ver. 1 -```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name, - version, - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: 'Check ID', // ID of the requirement - title, - desc, - descriptions, - impact, - refs, - tags: { - nist, - cci - }, - code, - source_location, - results: [ - { - status: 'Result Status', // The result of the scan for that particular control - code_desc, - message, - run_time, - start_time: 'Date' // Some indication of when the scan was run - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` -::: - -::: details Remaining DbProtect Source Data -```xml - - - - - - - ... - - - - - - TEST ORGANIZATION (Local DBP server) - - - Audit - - - Microsoft SQL Server - - - CONDS181 - - - 10.0.10.204, 1433, MSSQLSERVER - - - Heimdall Test scan report generation - - - DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) - - - Improper Access Controls - - - Medium - - - Schema ownership - - - Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole - - ... - - -``` -::: - -::: details Reasoning - -- `id: 'Check ID'`: `Check ID` gives us an ID used by DbProtect to identify each failing requirement. - -- `status: 'Result Status'`: `Result Status` gives us information about the result of the scan, whether it passed or failed or was skipped. - -- `start_time: 'Date'`: `Date` provides information about when the scan was run. -::: - -#### Mapping Version 2 - -Now let us handle some of the more detailed information about the specific controls, namely `Task`, `Check Category`, `Risk DV`, `Check`, and `Details`. - -::: details Correlated Fields -OHDF | Source Data --|- -`profiles.controls.desc` | `Task`, `Check Category` -`profiles.controls.impact` | `Risk DV` -`profiles.controls.title` | `Check` -`profiles.controls.results.code_desc` | `Details` -::: - -::: details OHDF Schema Mapping Ver. 2 -```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name, - version, - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: 'Check ID', // ID of the requirement - title: 'Check', - desc: ['Task', 'Check Category'], - descriptions, - impact: 'Risk DV', - refs, - tags: { - nist, - cci - }, - code, - source_location, - results: [ - { - status: 'Result Status', // The result of the scan for that particular control - code_desc: 'Details', - message, - run_time, - start_time: 'Date' // Some indication of when the scan was run - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` -::: - -::: details Remaining DbProtect Source Data -```xml - - - - - - - ... - - - - - - TEST ORGANIZATION (Local DBP server) - - - Microsoft SQL Server - - - CONDS181 - - - 10.0.10.204, 1433, MSSQLSERVER - - - Heimdall Test scan report generation - - - DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) - - ... - - -``` -::: - -::: details Reasoning - -For the control description, we want to give information about the type of control being run. Thus, it makes sense to store the category of the check, and the particular task it was for (whether it was for an Audit, or for another reason). - -In this case, we can directly map impact to `Risk DV` because there exists an intuitive mapping: High, Medium, Low, and Informational can map to 0.7, 0.5, 0.3, and 0, respectively. - -Note that `Check` appears to also correspond to the `Check ID`, and is a brief desciption of the check being run. Thus, it would make sense to map it to the title field of a control. - -Finally, for the details, recall that the `code_desc` is looking for the test expectations as defined by the particular control. `Details` is telling us about the particular result's associated parameters. -::: - -#### Mapping Version 3 - -Finally, we are left with the more general, report-level information from our DbProtect sample file: `Organization`, `Asset Type`, `Check Asset`, `IP Address, Port, Instance`, `Job Name`, `Policy`. Notice that OHDF does not have fields that correspond to some of this additional info, so consider ways to condense this data and encode it into other fields. - -::: details Correlated Fields -OHDF | Source Data --|- -`profiles.summary` | `Organization`, `Asset`, `Asset Type`, `IP Address, Port, Instance` -`profiles.title` | `Job Name` -`profiles.name` | `Policy` -::: - -::: details OHDF Schema Mapping Ver. 3 -```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name: 'Policy', - version, - sha256, - title: 'Job Name', - maintainer, - summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: 'Check ID', // ID of the requirement - title: 'Check', - desc: ['Task', 'Check Category'], - descriptions, - impact: 'Risk DV', - refs, - tags: { - nist, - cci - }, - code, - source_location, - results: [ - { - status: 'Result Status', // The result of the scan for that particular control - code_desc: 'Details', - message, - run_time, - start_time: 'Date' // Some indication of when the scan was run - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` -::: - -::: details Reasoning -As mentioned previously, OHDF does not have a specific place to put information like the `Organization`, `Asset`, or `Asset Type`. However, we do have a summary field for profiles. Recall our goal of preserving as much data as possible from the source. With this in mind, it would be reasonable to map all these fields to the summary for the sake of preservation. - -The profile name and title fields are a little tricky. Note that the `Policy` field refers to the baseline guidance that the scan tested against. This aligns more with the profile name than the `Job Name`, which is just a name the customer added for the report. Thus, we map the `Policy` field to the `profiles.name` and the `Job Name` field to the `profiles.title` instead. -::: - -#### Mapping Version 4 - -Finally, let's fill the rest of the empty fields using what available information we can use, prioritizing required fields and omitting any applicable unrequired fields. - -::: details Correlated Fields -OHDF | Source Data --|- -`platform.name` | `'Heimdall Tools'` -`platform.release` | `HeimdallToolsVersion` -`version` | `HeimdallToolsVersion` -`profiles.controls.tags.nist` | `DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS` -`profiles.controls.tags.cci` | `DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS` -`profiles.status` | `'loaded'` -::: - -::: details OHDF Schema Mapping Ver. 4 -```typescript -{ - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion, - target_id - }, - version: HeimdallToolsVersion, - statistics: { - duration - }, - profiles: [ - { - name: 'Policy', - version, - sha256, - title: 'Job Name', - maintainer, - summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: 'Check ID', // ID of the requirement - title: 'Check', - desc: ['Task', 'Check Category'], - descriptions, - impact: 'Risk DV', - refs, - tags: { - nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, - cci: DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS - }, - code, - source_location, - results: [ - { - status: 'Result Status', // The result of the scan for that particular control - code_desc: 'Details', - message, - run_time, - start_time: 'Date' // Some indication of when the scan was run - } - ] - }, - ], - status: 'loaded' - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` -::: - -::: details Reasoning -Unfilled fields are a result of a lack of sufficent information from the source data that can be used to reasonably associate with these fields. - -The reasoning for the filled fields are as follows: - -- `platform: {name: 'Heimdall Tools'}`: `platform` refers to the instance generating the OHDF file, which in this case is Heimdall2 or Heimdall Tools. - -- `platform: {release: HeimdallToolsVersion}`: Similar reasoning as above. - -- `version: HeimdallToolsVersion`: Similar reasoning as `platform` fields. - -- `profiles.controls.tags.nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS`: The DbProtect sample does not have any associated NIST tags within it. Thus, we use the default tags for a static code analysis. - -- `profiles.controls.tags.cci: DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS`: Similar reasoning as above. -- `status: 'loaded'`: The status of a profile is typically `loaded` since it has been ingested and converted to OHDF. -::: +### GitHub Merging -Now we have a finalized mapping for DbProtect to OHDF. +Commit your final changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, your mapper will be merged into the main development branch and [scheduled for release](https://github.com/mitre/heimdall2/wiki/How-to-create-a-Heimdall2-release) as an officially supported conversion format for OHDF Converters. diff --git a/src/courses/mappers/14.md b/src/courses/mappers/14.md index ea45f4db5..ce9ad2781 100644 --- a/src/courses/mappers/14.md +++ b/src/courses/mappers/14.md @@ -1,1698 +1,32 @@ --- order: 14 next: 15.md -title: Implementing a Mapper +title: More Practice author: Charles Hu --- -## Mapper Introduction +The following are some practice source data sets to create mappers with. -::: note OHDF Converters Utilities -Special utilities from OHDF Converters are used here. [Refer here](./09.md) for a refresher on OHDF Converters. -::: - -Now that we have developed a mapping, we can implement that mapping as a mapper which applies the mapping to any compatible file for a conversion to OHDF. - -## File Set Up - -A number of crucial files that support and provide the infrastructure needed for the *-to-OHDF mapper have to be set up first before we begin actual mapper development. - -::: note Specialized Security Tools -This guide is geared for security tools that provide scan-based export data. If your security tool provides a specialized form of export data or is an API, contact the SAF team for further guidance. -::: - -### Mapper File - -First, we need to create the file that hosts the mapper and link to it so other files in OHDF Converters can access it. - -1. Create a blank TypeScript file under the `src` directory in `hdf-converters`. It should be named: -``` -{YOUR-EXPORT-NAME-HERE}-mapper.ts -``` - -2. Select the appropriate mapper skeleton (see below) for your export type. Place them in the file created in step 1. Replace names (`SKELETON` by default) as necessary. - -::: details JSON Mapper Skeleton -```typescript -import {ExecJSON} from 'inspecjs'; -import _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - ILookupPath, - impactMapping, - MappedTransform -} from './base-converter'; - -export class SKELETONMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion, - target_id: null //Insert data - }, - version: HeimdallToolsVersion, - statistics: { - duration: null //Insert data - }, - profiles: [ - { - name: '', //Insert data - title: null, //Insert data - version: null, //Insert data - maintainer: null, //Insert data - summary: null, //Insert data - license: null, //Insert data - copyright: null, //Insert data - copyright_email: null, //Insert data - supports: [], //Insert data - attributes: [], //Insert data - depends: [], //Insert data - groups: [], //Insert data - status: 'loaded', //Insert data - controls: [ - { - key: 'id', - tags: {}, //Insert data - descriptions: [], //Insert data - refs: [], //Insert data - source_location: {}, //Insert data - title: null, //Insert data - id: '', //Insert data - desc: null, //Insert data - impact: 0, //Insert data - code: null, //Insert data - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, //Insert data - code_desc: '', //Insert data - message: null, //Insert data - run_time: null, //Insert data - start_time: '' //Insert data - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return { - auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed - ...(this.withRaw && {raw: data}) - }; - } - } - }; - constructor(exportJson: string, withRaw = false) { - super(JSON.parse(exportJson), true); - this.withRaw = withRaw - } -} -``` -::: - -3. Export your mapper class created in the previous steps by specifying its export in the index.ts file. Add the following line: -``` -export * from './src/{YOUR-EXPORT-NAME-HERE}-mapper'; -``` - -### Sample File - -Next, we need to add a sample file for the mapper to ingest when running unit tests on it. - -1. Create a new directory named `{YOUR-EXPORT-NAME-HERE}_mapper` under the `sample_jsons` directory in `hdf-converters`. Create another directory named `sample_input_report` in the directory you just made. The directory structure should look like this: -``` -+-- sample_jsons -| +-- {YOUR-EXPORT-NAME-HERE}-mapper -| | +-- sample_input_report -``` - -2. Place your sample export under the `sample_input_report` directory. Your sample export should be genericized to avoid any leaking of sensitive information. The directory structure should now look like this: -``` -+-- sample_jsons -| +-- {YOUR-EXPORT-NAME-HERE}-mapper -| | +-- sample_input_report -| | | +-- {YOUR-SAMPLE-EXPORT} -``` - -### Regression Testing - -Now that we have a sample file, we can now add some regression tests which automatically test our mapper to ensure that it is producing readable and correct OHDF file outputs. - -1. Create a blank TypeScript file under the `test/mappers/forward` directory in `hdf-converters`. It should be named: -``` -{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts -``` - -2. Select the appropriate mapper test skeleton (see below) for your export type. Place it in the file created in step 1. Replace names (`SKELETON` by default) as necessary. - -::: details JSON Mapper Test Skeleton -```typescript -import fs from 'fs'; -import {SKELETONMapper} from '../../../src/SKELETON-mapper'; -import {omitVersions} from '../../utils'; - -describe('SKELETON_mapper', () => { - it('Successfully converts SKELETON targeted at a local/cloned repository data', () => { - const mapper = new SKELETONMapper( - fs.readFileSync( - 'sample_jsons/SKELETON_mapper/sample_input_report/SKELETON.json', - {encoding: 'utf-8'} - ) - ); - - // fs.writeFileSync( - // 'sample_jsons/SKELETON_mapper/SKELETON-hdf.json', - // JSON.stringify(mapper.toHdf(), null, 2) - // ); - - expect(omitVersions(mapper.toHdf())).toEqual( - omitVersions( - JSON.parse( - fs.readFileSync( - 'sample_jsons/SKELETON_mapper/SKELETON-hdf.json', - { - encoding: 'utf-8' - } - ) - ) - ) - ); - }); -}); - -describe('SKELETON_mapper_withraw', () => { - it('Successfully converts withraw flagged SKELETON targeted at a local/cloned repository data', () => { - const mapper = new SKELETONMapper( - fs.readFileSync( - 'sample_jsons/SKELETON_mapper/sample_input_report/SKELETON.json', - {encoding: 'utf-8'} - ), - true - ); - - // fs.writeFileSync( - // 'sample_jsons/SKELETON_mapper/SKELETON-hdf-withraw.json', - // JSON.stringify(mapper.toHdf(), null, 2) - // ); - - expect(omitVersions(mapper.toHdf())).toEqual( - omitVersions( - JSON.parse( - fs.readFileSync( - 'sample_jsons/SKELETON_mapper/SKELETON-hdf-withraw.json', - { - encoding: 'utf-8' - } - ) - ) - ) - ); - }); -}); -``` -::: - -### Fingerprinting - -OHDF Converters has a fingerprinting service that detects a security tool data format and automatically applies the correct mapper to convert it to OHDF. To enable this feature, we need to explicitly declare keywords unique to the security tool data format as follows: - -1. Go to the file `report_intake.ts` under the `heimdall2/apps/frontend/src/store` directory. - -2. Import your mapper file. You should be able to add the name of your mapper class to a pre-existing import statement pointing at `hdf-converters` as follows: -```typescript -import { - ASFFResults as ASFFResultsMapper, - BurpSuiteMapper, - ... - {YOUR-MAPPER-CLASS-HERE} -} from '@mitre/hdf-converters'; -``` - -3. Instantiate your mapper class in the `convertToHdf` switch block. Add the following lines: -```typescript -case '{YOUR-EXPORT-SERVICE-NAME-HERE}': - return new {YOUR-MAPPER-CLASS-HERE}(convertOptions.data).toHdf(); -``` - -4. Navigate to the file `fingerprinting.ts` in the `src/utils` directory in `hdf-converters`. Add keywords that are unique to your sample export to the `fileTypeFingerprints` variable. It should be formatted as follows: -```typescript -export const fileTypeFingerprints = { - asff: ['Findings', 'AwsAccountId', 'ProductArn'], - ... - {YOUR-EXPORT-SERVICE-NAME-HERE}: [{UNIQUE KEYWORDS AS STRINGS}] -}; -``` - -## Mapper Implementation - -With the necessary files now set up, we can begin the actual creation of the OHDF mapper using the skeleton mapper base in the `{YOUR-EXPORT-NAME-HERE}-mapper.ts` file. The skeleton mapper and the `base-converter` class have been designed to provide the base functionality needed for *-to-HDF mapper generation. For most developers, mapper creation will be limited to assigning objects from the export structure to correlating attributes in the mapper according to the mappings they developed earlier. - -::: warning File Processing - Certain security services produce exports which are not immediately usable by the skeleton mapper. In such case, pre-processing on the export and or post-processing on the generated OHDF file is necessary in order to ensure compatibility. -::: - -While developing the mapper, it's useful to occasionally check on the generated OHDF file to check that the mapper is working as intended. You can do this by starting a local instance of Heimdall with the following command: -```shell -yarn start:dev -``` -Note that the `yarn start:dev` command will dynamically rebuild the application upon changes to the Heimdall frontend. However, if you make any changes to OHDF-Converters, you will have to restart the command entirely. - -Import your source data and then export it as an OHDF JSON to check what your mapper is actually mapping. - -### Mapper Demo - GoSec - -This section is a demonstration on implementing an OHDF mapper for GoSec, assuming that the [appropriate file set up for the mapper](#file-set-up) has been performed. - -Here is our developed mapping for GoSec for reference: - -::: details GoSec-to-OHDF Mapping -```typescript -{ - platform: { // We fill in Heimdall for the platform as it handles the generation of this OHDF file - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, // See 'platform' reasoning - statistics: {}, // Not enough info to fill - profiles: [ - { - name: 'Gosec scanner', // We know that this report is generated from GoSec - version: GosecVersion, // Version of GoSec instance - sha256: '', // Leave it empty as OHDF Converters will generate one for us - title: 'gosec', // We know that this report is generated from GoSec - supports: [], // Not enough info to fill - attributes: [], // Not enough info to fill - groups: [], // Not enough info to fill - controls: [ - { - id: Issues.rule_id, // ID of the requirement - title: Issues.details, // Human readable title for the requirement - desc: '', // Not enough info to fill - impact: 0.5, // Have no solid information on impact of security issue, so we default to 0.5 - refs: [], // Not enough info to fill - tags: { - Issues.cwe // Associated CWE for the requirement - Issues.severity, // Severity of the requirement - Issues.confidence, // Applicability of the requirement - Issues.nosec, // Whether to ignore the requirement - Issues.suppressions // Info suppression level of the requirement - }, - source_location: {}, // Not enough info to fill - results: [ - { - status: 'failed', // The security scan only reports failed requirements, so all findings we receive get fail statuses - code_desc: Issues.code, // The code failing the requirement test - message: Issues.file + Issues.line + Issues.column, // All materials describing where the issue occurred - start_time // Not enough info to fill - } - ] - }, - ], - status: 'loaded' // Give loaded status to denote that profile is loaded by OHDF Converters - }, - ], - passthrough: { - auxiliary_data: [ - { // Go source data compilation errors; Stats on GoSec scan - name: 'Gosec', - data: Golang errors, Stats - } - ], - raw - } -} -``` -::: - -::: details GoSec Annotated Source Data -```json -{ - // Purpose: Go compilation errors - // Recording: Metadata - Not specifically related to the requirements and will be already recorded as a security issue in 'Issues' if critical - "Golang errors": {}, - // Purpose: Container for identified security issues - // Recording: Requirements - This entity records all identified security issues in a Go source code - "Issues": [ - { - // Purpose: The severity of the identified issue - // Recording: Requirements - This is specifically related to the severity level of the requirement - "severity": "MEDIUM", - // Purpose: How sure that the identified issue if applicable to this source code - // Recording: Requirements testing - This field gives the applicability of the issue after source code testing - "confidence": "HIGH", - // Purpose: The associated CWE for the security issue - // Recording: Requirements - This gives the associated CWE for the security issue - "cwe": { - "id": "22", - "url": "https://cwe.mitre.org/data/definitions/22.html" - }, - // Purpose: The internal GoSec ID for the security issue - // Recording: Requirements - This gives an ID for the security issue - "rule_id": "G304", - // Purpose: Explanation of the security issue - // Recording: Requirements - This explains the security issue - "details": "Potential file inclusion via variable", - // Purpose: The offending file - // Recording: Requirement testing - This specifically notes which file fails the requirement after source code testing - "file": "C:\\Users\\AGILLUM\\OneDrive - The MITRE Corporation\\Documents\\Code\\grype-0.34.4\\internal\\file\\tar.go", - // Purpose: The offending code - // Recording: Requirement testing - This specifies the code that fails the requirement after source code testing - "code": "82: \t\tcase tar.TypeReg:\n83: \t\t\tf, err := os.OpenFile(target, os.O_CREATE|os.O_RDWR, os.FileMode(header.Mode))\n84: \t\t\tif err != nil {\n", - // Purpose: The line number of the offending code - // Recording: Requirement testing - This field specifies the location of the failing code - "line": "83", - // Purpose: The column number of the offending code - // Recording: Requirement testing - This field specifies the location of the failing code - "column": "14", - // Purpose: Whether this security issue should be ignored - // Recording: Requirements - Specifies whether this security issue should be ignored - "nosec": false, - // Purpose: The supression level for info on the security issue - // Recording: Requirements - Specifies the info suppression level of the security issue - "suppressions": null - } - ], - // Purpose: The statistics of the GoSec scan on the source code - // Recording: Metadata - Info on the scan itself - "Stats": { - "files": 199, - "lines": 12401, - "nosec": 0, - "found": 7 - }, - // Purpose: The version of the GoSec instance currently running - // Recording: Metadata - Info on the scan itself - "GosecVersion": "dev" -} -``` -::: - -Mapper creation has been streamlined to be as simple as possible for a developer. Most of the work involves simple references to the object path for a field in the source data as so: -```typescript -version: {path: 'GosecVersion'} -``` - -This primarily applies in cases where the field is simply carried over. Some fields from the source data need to be processed or transformed in some way, which will be elaborated upon later. - -#### Unfilled/Omitted and Hard Coded Fields - -First, let's assign mappings which are unfilled/omitted or are not dependent on the source data (i.e., hard coded data). This include fields like our mappings for `profiles.name` and `profiles.sha256` - -::: details GoSec-to-OHDF Mapper -```typescript -import {ExecJSON} from 'inspecjs'; -import _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - ILookupPath, - impactMapping, - MappedTransform -} from './base-converter'; - -export class GoSecMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - name: 'Gosec scanner', - title: 'gosec', - version: null, //Insert data - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - key: 'id', - tags: {}, //Insert data - refs: [], - source_location: {}, - title: null, //Insert data - id: '', //Insert data - desc: '', - impact: 0.5, - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, - code_desc: '', //Insert data - message: null, //Insert data - start_time: '' - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return { - auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed - ...(this.withRaw && {raw: data}) - }; - } - } - }; - constructor(exportJson: string, withRaw = false) { - super(JSON.parse(exportJson), true); - this.withRaw = withRaw - } -} -``` -::: - -::: details Remaining GoSec-to-OHDF Mapping -```typescript -{ - profiles: [ - { - version: GosecVersion, // Version of GoSec instance - controls: [ - { - id: Issues.rule_id, // ID of the requirement - title: Issues.details, // Human readable title for the requirement - tags: { - Issues.cwe // Associated CWE for the requirement - Issues.severity, // Severity of the requirement - Issues.confidence, // Applicability of the requirement - Issues.nosec, // Whether to ignore the requirement - Issues.suppressions // Info suppression level of the requirement - }, - results: [ - { - code_desc: Issues.code, // The code failing the requirement test - message: Issues.file + Issues.line + Issues.column // All materials describing where the issue occurred - } - ] - }, - ] - }, - ], - passthrough: { - auxiliary_data: [ - { // Go source data compilation errors; Stats on GoSec scan - name: 'Gosec', - data: Golang errors, Stats - } - ], - raw - } -} -``` -::: - -#### Simple Portable Fields - -Next, let's look at the fields which can be just simply be directly ported over from the source data like `GosecVersion`. To do this, we just need to invoke the `path` keyword from `base-converter` and feed the direct JSON object path as a value like so: -```typescript -version: {path: 'GosecVersion'} -``` - -For nested fields (i.e., fields requiring traversal through parent fields), we need to have the mapper traverse into the level containing the fields we want to access. Think of this as a similar process as using `cd` to traverse through a directory to access a file. For example, if we can allow the access of fields using `path` in the `Issues` superfield in the source data as follows: -```typescript -path: 'Issues' -``` - -Let's put this into practice and start implementing the mappings for simple fields that don't require transformation or processing: - -::: details GoSec-to-OHDF Mapper -```typescript -import {ExecJSON} from 'inspecjs'; -import _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - ILookupPath, - impactMapping, - MappedTransform -} from './base-converter'; - -export class GoSecMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - name: 'Gosec scanner', - title: 'gosec', - version: {path: 'GosecVersion'}, - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - path: 'Issues', - key: 'id', - tags: { - cwe: {path: 'cwe'}, - nosec: {path: 'nosec'}, - suppressions: {path: 'suppressions'}, - severity: {path: 'severity'}, - confidence: {path: 'confidence'} - }, - refs: [], - source_location: {}, - title: {path: 'details'}, - id: {path: 'rule_id'}, - desc: '', - impact: 0.5, - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, - code_desc: {path: 'code'}, - message: null, //Insert data - start_time: '' - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return { - auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed - ...(this.withRaw && {raw: data}) - }; - } - } - }; - constructor(exportJson: string, withRaw = false) { - super(JSON.parse(exportJson), true); - this.withRaw = withRaw - } -} -``` -::: - -::: details Remaining GoSec-to-OHDF Mapping -```typescript -{ - profiles: [ - { - controls: [ - { - results: [ - { - message: Issues.file + Issues.line + Issues.column // All materials describing where the issue occurred - } - ] - }, - ] - }, - ], - passthrough: { - auxiliary_data: [ - { // Go source data compilation errors; Stats on GoSec scan - name: 'Gosec', - data: Golang errors, Stats - } - ], - raw - } -} -``` -::: - -#### Transformed/Processed Fields - -Finally, let's look at fields that require some level of processing before we can use them in the OHDF mapper. - -The fields like `Issues.file`, `Issues.line`, and `Issues.column` need to be combined to make a coherent locational message. We can combine them using a simple function that concatenates them together. The function to do this is provided: -```typescript -function formatMessage(input: Record): string { - return `${_.get(input, 'file')}, line:${_.get(input, 'line')}, column:${_.get(input, 'column')}`; -} -``` -This function just pulls the three fields and joins them into a single string. - -To invoke this, we can use the `transformer` keyword and feed the function as a value for the transformer to invoke. This is implemented as follows: - -::: details GoSec-to-OHDF Mapper -```typescript -import {ExecJSON} from 'inspecjs'; -import _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - ILookupPath, - impactMapping, - MappedTransform -} from './base-converter'; - -function formatMessage(input: Record): string { - return `${_.get(input, 'file')}, line:${_.get(input, 'line')}, column:${_.get( - input, - 'column' - )}`; -} - -export class GoSecMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - name: 'Gosec scanner', - title: 'gosec', - version: {path: 'GosecVersion'}, - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - path: 'Issues', - key: 'id', - tags: { - cwe: {path: 'cwe'}, - nosec: {path: 'nosec'}, - suppressions: {path: 'suppressions'}, - severity: {path: 'severity'}, - confidence: {path: 'confidence'} - }, - refs: [], - source_location: {}, - title: {path: 'details'}, - id: {path: 'rule_id'}, - desc: '', - impact: 0.5, - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, - code_desc: {path: 'code'}, - message: {transformer: formatMessage}, - start_time: '' - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return { - auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed - ...(this.withRaw && {raw: data}) - }; - } - } - }; - constructor(exportJson: string, withRaw = false) { - super(JSON.parse(exportJson), true); - this.withRaw = withRaw - } -} -``` -::: - -::: details Remaining GoSec-to-OHDF Mapping -```typescript -{ - passthrough: { - auxiliary_data: [ - { // Go source data compilation errors; Stats on GoSec scan - name: 'Gosec', - data: Golang errors, Stats - } - ], - raw - } -} -``` -::: - -We can also combine keywords such as using `path` to traverse to a particular field and then apply a function using `transformer`. For example, we can target the `Issues.cwe` field specifically and apply the following function to create corresponding NIST 800-53s: -```typescript -import {CweNistMapping} from './mappings/CweNistMapping'; - -const CWE_NIST_MAPPING = new CweNistMapping(); -const DEFAULT_NIST_TAG = ['SI-2', 'RA-5']; - -function nistTag(input: Record): string[] { - const cwe = [`${_.get(input, 'id')}`]; - return CWE_NIST_MAPPING.nistFilter(cwe, DEFAULT_NIST_TAG); -} -``` - -We can then correlate it with a `profiles.controls.tags.nist` field in the OHDF mapper as so: - -::: details GoSec-to-OHDF Mapper -```typescript -import {ExecJSON} from 'inspecjs'; -import _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - ILookupPath, - impactMapping, - MappedTransform -} from './base-converter'; -import {CweNistMapping} from './mappings/CweNistMapping'; - -const CWE_NIST_MAPPING = new CweNistMapping(); -const DEFAULT_NIST_TAG = ['SI-2', 'RA-5']; - -function nistTag(input: Record): string[] { - const cwe = [`${_.get(input, 'id')}`]; - return CWE_NIST_MAPPING.nistFilter(cwe, DEFAULT_NIST_TAG); -} - -function formatMessage(input: Record): string { - return `${_.get(input, 'file')}, line:${_.get(input, 'line')}, column:${_.get( - input, - 'column' - )}`; -} - -export class GoSecMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - name: 'Gosec scanner', - title: 'gosec', - version: {path: 'GosecVersion'}, - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - path: 'Issues', - key: 'id', - tags: { - nist: { - path: 'cwe', - transformer: nistTag - }, - cwe: {path: 'cwe'}, - nosec: {path: 'nosec'}, - suppressions: {path: 'suppressions'}, - severity: {path: 'severity'}, - confidence: {path: 'confidence'} - }, - refs: [], - source_location: {}, - title: {path: 'details'}, - id: {path: 'rule_id'}, - desc: '', - impact: 0.5, - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, - code_desc: {path: 'code'}, - message: {transformer: formatMessage}, - start_time: '' - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return { - auxiliary_data: [{name: '', data: _.omit([])}], //Insert service name and mapped fields to be removed - ...(this.withRaw && {raw: data}) - }; - } - } - }; - constructor(exportJson: string, withRaw = false) { - super(JSON.parse(exportJson), true); - this.withRaw = withRaw - } -} -``` -::: - -::: details Remaining GoSec-to-OHDF Mapping -```typescript -{ - passthrough: { - auxiliary_data: [ - { // Go source data compilation errors; Stats on GoSec scan - name: 'Gosec', - data: Golang errors, Stats - } - ], - raw - } -} -``` -::: - -For the remaining fields that we want to place in `passthrough`, we need to use the [lodash library](https://lodash.com/docs/) to preserve the field in its entirety. In particular, we will use the `_.get(OBJECT, FIELD)` command to pull a field from the source data object. - - -::: details GoSec-to-OHDF Mapper -```typescript -import {ExecJSON} from 'inspecjs'; -import _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - ILookupPath, - impactMapping, - MappedTransform -} from './base-converter'; -import {CweNistMapping} from './mappings/CweNistMapping'; - -const CWE_NIST_MAPPING = new CweNistMapping(); -const DEFAULT_NIST_TAG = ['SI-2', 'RA-5']; - -function nistTag(input: Record): string[] { - const cwe = [`${_.get(input, 'id')}`]; - return CWE_NIST_MAPPING.nistFilter(cwe, DEFAULT_NIST_TAG); -} - -function formatMessage(input: Record): string { - return `${_.get(input, 'file')}, line:${_.get(input, 'line')}, column:${_.get( - input, - 'column' - )}`; -} - -export class GoSecMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - name: 'Gosec scanner', - title: 'gosec', - version: {path: 'GosecVersion'}, - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - path: 'Issues', - key: 'id', - tags: { - nist: { - path: 'cwe', - transformer: nistTag - }, - cwe: {path: 'cwe'}, - nosec: {path: 'nosec'}, - suppressions: {path: 'suppressions'}, - severity: {path: 'severity'}, - confidence: {path: 'confidence'} - }, - refs: [], - source_location: {}, - title: {path: 'details'}, - id: {path: 'rule_id'}, - desc: '', - impact: 0.5, - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, - code_desc: {path: 'code'}, - message: {transformer: formatMessage}, - start_time: '' - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return { - auxiliary_data: [ - { - name: 'Gosec', - data: { - 'Golang errors': _.get(data, 'Golang errors'), - 'Stats': _.get(data, 'Stats') - } - } - ], - ...(this.withRaw && {raw: data}) - }; - } - } - }; - constructor(exportJson: string, withRaw = false) { - super(JSON.parse(exportJson), true); - this.withRaw = withRaw - } -} -``` -::: - -Now we have a fully implemented GoSec-to-OHDF mapper. - - -### Mapper Demo - DbProtect - -This section is a demonstration for implementing an OHDF mapper that handles XML-based source data, namely DbProtect. As in the previous section, we assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. - -Here is our developed mapping for DbProtect for reference: - -::: details DbProtect-to-OHDF Mapping -```typescript -{ - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion, - target_id - }, - version: HeimdallToolsVersion, - statistics: { - duration - }, - profiles: [ - { - name: 'Policy', - version, - sha256, - title: 'Job Name', - maintainer, - summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: 'Check ID', // ID of the requirement - title: 'Check', - desc: ['Task', 'Check Category'], - descriptions, - impact: 'Risk DV', - refs, - tags: { - nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, - cci: DEFAULT_STATIC_CODE_ANALYSIS_CCI_TAGS - }, - code, - source_location, - results: [ - { - status: 'Result Status', // The result of the scan for that particular control - code_desc: 'Details', - message, - run_time, - start_time: 'Date' // Some indication of when the scan was run - } - ] - }, - ], - status: 'loaded' - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` -::: - -::: details DbProtect Annotated Source Data -```xml - - - - - - - - - - - - - - - - - - - - - - - - - TEST ORGANIZATION (Local DBP server) - - - Audit - - - Microsoft SQL Server - - - CONDS181 - - - 10.0.10.204, 1433, MSSQLSERVER - - - Heimdall Test scan report generation - - - DISA-STIG SQL Server 2016 V2R1-1 Audit (Built-In) - - - Fact - - - Improper Access Controls - - - Medium - - - 2986 - - - Schema ownership - - - Schema name=DatabaseMailUserRole;Database=msdb;Owner name=DatabaseMailUserRole - - - Feb 18 2021 15:57 - - ... - - -``` -::: - -As in the previous GoSec example, most of the work involves simple references to the object path for a field in the source data. For example: - -```typescript -title: {path: 'Check'} -``` - -Again, some fields from the source data need to be processed or transformed in some way, which will be elaborated upon later. - -#### Unfilled/Omitted and Hard Coded Fields - -First, let's assign mappings which are unfilled/omitted or are not dependent on the source data (i.e., hard coded data). This include fields like our mappings for `platform.name` and `profiles.sha256`. Note that for our tags, we use the global method in the Heimdall repo, `getCCIsForNISTTags`, as well as the global constant `DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS`. We can also just directly put the source data into the passthrough. Also note the `compileFindings` function we wrote to deal with the strange structure of the XML, which has metadata correlated with each row in the data field. No need to worry about this function for now - just think of it as a way of assigning the metadata keys to each data row explicitly, so that our base converter has a way to easily access fields and know what they are. - -::: details DbProtect-to-OHDF Mapper -```typescript -import {ExecJSON} from 'inspecjs'; -import * as _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - ILookupPath, - impactMapping, - MappedTransform, - parseXml -} from './base-converter'; - -function compileFindings( - input: Record -): Record { - const keys = _.get(input, 'dataset.metadata.item'); - const findings = _.get(input, 'dataset.data.row'); - - let output: unknown[] = []; - - if (Array.isArray(keys) && Array.isArray(findings)) { - const keyNames = keys.map((element: Record): string => { - return _.get(element, 'name') as string; - }); - output = findings.map((element: Record) => { - return Object.fromEntries( - keyNames.map(function (name: string, i: number) { - return [name, _.get(element, `value[${i}]`)]; - }) - ); - }); - } - return Object.fromEntries([['data', output]]); -} - -export class DBProtectMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - name: {}, - title: {}, - summary: {}, - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - key: 'id', - tags: { - nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, - cci: getCCIsForNISTTags(DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS) - }, - refs: [], - source_location: {}, - title: {}, - id: {}, - desc: {}, - impact: {}, - code: {}, - results: [ - { - status: {}, - code_desc: {}, - start_time: {}, - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return {...(this.withRaw && {raw: data})}; - } - } - }; - constructor(dbProtectXml: string, withRaw = false) { - super(compileFindings(parseXml(dbProtectXml))); - this.withRaw = withRaw; - } -} -``` -::: - -::: details Remaining DbProtect-to-OHDF Mapping -```typescript -{ - profiles: [ - { - name: 'Policy', - title: 'Job Name', - maintainer, - summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: 'Check ID', // ID of the requirement - title: 'Check', - desc: ['Task', 'Check Category'], - descriptions, - impact: 'Risk DV', - refs, - code, - source_location, - results: [ - { - status: 'Result Status', // The result of the scan for that particular control - code_desc: 'Details', - message, - run_time, - start_time: 'Date' // Some indication of when the scan was run - } - ] - }, - ], - }, - ] -} -``` -::: - -#### Simple Portable Fields - -Next, let's look at the fields which can be just simply be directly ported over from the source data like `Policy`. To do this, we just need to invoke the `path` keyword from `base-converter` and feed the direct JSON object path as a value like so: -```typescript -name: {path: 'data.[0].Policy'} -``` -Note that in this example, we must call the path with `data.[0]`, since even though the Policy is the same for all data rows, we still must specify an element to extract the data from. - -Let's put this into practice and start implementing the mappings for simple fields that don't require transformation or processing: - -::: details DbProtect-to-OHDF Mapper -```typescript -import {ExecJSON} from 'inspecjs'; -import * as _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - ILookupPath, - impactMapping, - MappedTransform, - parseXml -} from './base-converter'; - -function compileFindings( - input: Record -): Record { - const keys = _.get(input, 'dataset.metadata.item'); - const findings = _.get(input, 'dataset.data.row'); - - let output: unknown[] = []; - - if (Array.isArray(keys) && Array.isArray(findings)) { - const keyNames = keys.map((element: Record): string => { - return _.get(element, 'name') as string; - }); - output = findings.map((element: Record) => { - return Object.fromEntries( - keyNames.map(function (name: string, i: number) { - return [name, _.get(element, `value[${i}]`)]; - }) - ); - }); - } - return Object.fromEntries([['data', output]]); -} - -export class DBProtectMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - name: {path: 'data.[0].Policy'}, - title: {path: 'data.[0].Job Name'}, - summary: {}, - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - path: 'data', - key: 'id', - tags: { - nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, - cci: getCCIsForNISTTags(DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS) - }, - refs: [], - source_location: {}, - title: {path: 'Check'}, - id: {}, - desc: {}, - impact: {}, - code: {}, - results: [ - { - status: {}, - code_desc: {path: 'Details'}, - start_time: {path: 'Date'}, - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return {...(this.withRaw && {raw: data})}; - } - } - }; - constructor(dbProtectXml: string, withRaw = false) { - super(compileFindings(parseXml(dbProtectXml))); - this.withRaw = withRaw; - } -} -``` -::: - -::: details Remaining DbProtect-to-OHDF Mapping -```typescript -{ - profiles: [ - { - maintainer, - summary: ['Organization', 'Asset', 'Asset Type', 'IP Address, Port, Instance'], - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: 'Check ID', // ID of the requirement - desc: ['Task', 'Check Category'], - descriptions, - impact: 'Risk DV', - refs, - code, - source_location, - results: [ - { - status: 'Result Status', // The result of the scan for that particular control - message, - run_time, - } - ] - }, - ], - }, - ] -} -``` -::: - -#### Transformed/Processed Fields - -As in the previous example, there are several fields that need to be processed further. To do so, we can make use of the `transformer` field supported by the OHDF Converters library. Some simple transformers include casting the `id` field to a string, and mapping the `impact` fields properly (by creating a mapping and passing it into the `impactMapping` function in `base-converter`): - -```typescript -const IMPACT_MAPPING: Map = new Map([ - ['high', 0.7], - ['medium', 0.5], - ['low', 0.3], - ['informational', 0] -]); - -function idToString(id: unknown): string { - if (typeof id === 'string' || typeof id === 'number') { - return id.toString(); - } else { - return ''; - } -} -``` - -For the OHDF fields that concatenate information from multiple DbProtect fields, we must write corresponding transformers that format these strings: -```typescript -function formatSummary(entry: unknown): string { - const text = []; - text.push(`Organization : ${_.get(entry, 'Organization')}`); - text.push(`Asset : ${_.get(entry, 'Check Asset')}`); - text.push(`Asset Type : ${_.get(entry, 'Asset Type')}`); - text.push(`IP Address, Port, Instance : ${_.get(entry, 'Asset Type')}`); - text.push( - `IP Address, Port, Instance : ${_.get( - entry, - 'IP Address, Port, Instance' - )} ` - ); - return text.join('\n'); -} - -function formatDesc(entry: unknown): string { - const text = []; - text.push(`Task : ${_.get(entry, 'Task')}`); - text.push(`Check Category : ${_.get(entry, 'Check Category')}`); - return text.join('; '); -} -``` -Finally, we write one more function to map the `Result Status` to the proper `ExecJSON` statuses: -```typescript -function getStatus(input: unknown): ExecJSON.ControlResultStatus { - switch (input) { - case 'Fact': - return ExecJSON.ControlResultStatus.Skipped; - case 'Failed': - return ExecJSON.ControlResultStatus.Failed; - case 'Finding': - return ExecJSON.ControlResultStatus.Failed; - case 'Not A Finding': - return ExecJSON.ControlResultStatus.Passed; - } - return ExecJSON.ControlResultStatus.Skipped; -} -``` -Writing out all these transformers and applying them to the mapping fed into `base-converter` looks something like this: - -:::details Full Mapper Code -```typescript -import {ExecJSON} from 'inspecjs'; -import * as _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - ILookupPath, - impactMapping, - MappedTransform, - parseXml -} from './base-converter'; -import { - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, - getCCIsForNISTTags -} from './utils/global'; - -const IMPACT_MAPPING: Map = new Map([ - ['high', 0.7], - ['medium', 0.5], - ['low', 0.3], - ['informational', 0] -]); - -function compileFindings( - input: Record -): Record { - const keys = _.get(input, 'dataset.metadata.item'); - const findings = _.get(input, 'dataset.data.row'); - - let output: unknown[] = []; - - if (Array.isArray(keys) && Array.isArray(findings)) { - const keyNames = keys.map((element: Record): string => { - return _.get(element, 'name') as string; - }); - output = findings.map((element: Record) => { - return Object.fromEntries( - keyNames.map(function (name: string, i: number) { - return [name, _.get(element, `value[${i}]`)]; - }) - ); - }); - } - return Object.fromEntries([['data', output]]); -} - -function formatSummary(entry: unknown): string { - const text = []; - text.push(`Organization : ${_.get(entry, 'Organization')}`); - text.push(`Asset : ${_.get(entry, 'Check Asset')}`); - text.push(`Asset Type : ${_.get(entry, 'Asset Type')}`); - text.push(`IP Address, Port, Instance : ${_.get(entry, 'Asset Type')}`); - text.push( - `IP Address, Port, Instance : ${_.get( - entry, - 'IP Address, Port, Instance' - )} ` - ); - return text.join('\n'); -} - -function formatDesc(entry: unknown): string { - const text = []; - text.push(`Task : ${_.get(entry, 'Task')}`); - text.push(`Check Category : ${_.get(entry, 'Check Category')}`); - return text.join('; '); -} - -function getStatus(input: unknown): ExecJSON.ControlResultStatus { - switch (input) { - case 'Fact': - return ExecJSON.ControlResultStatus.Skipped; - case 'Failed': - return ExecJSON.ControlResultStatus.Failed; - case 'Finding': - return ExecJSON.ControlResultStatus.Failed; - case 'Not A Finding': - return ExecJSON.ControlResultStatus.Passed; - } - return ExecJSON.ControlResultStatus.Skipped; -} - -function idToString(id: unknown): string { - if (typeof id === 'string' || typeof id === 'number') { - return id.toString(); - } else { - return ''; - } -} - -export class DBProtectMapper extends BaseConverter { - withRaw: boolean; +Before you begin, recall the steps we took previously to develop our GoSec and DBProtect mappers: - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - name: {path: 'data.[0].Policy'}, - title: {path: 'data.[0].Job Name'}, - summary: {path: 'data.[0]', transformer: formatSummary}, - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - path: 'data', - key: 'id', - tags: { - nist: DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, - cci: getCCIsForNISTTags(DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS) - }, - refs: [], - source_location: {}, - title: {path: 'Check'}, - id: {path: 'Check ID', transformer: idToString}, - desc: {transformer: formatDesc}, - impact: { - path: 'Risk DV', - transformer: impactMapping(IMPACT_MAPPING) - }, - code: { - transformer: (vulnerability: Record): string => - JSON.stringify(vulnerability, null, 2) - }, - results: [ - { - status: {path: 'Result Status', transformer: getStatus}, - code_desc: {path: 'Details'}, - start_time: {path: 'Date'}, - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return {...(this.withRaw && {raw: data})}; - } - } - }; - constructor(dbProtectXml: string, withRaw = false) { - super(compileFindings(parseXml(dbProtectXml))); - this.withRaw = withRaw; - } -} -``` -::: +1. Examine and break down the security data format. Remember to ask yourself the following questions while analyzing the fields of your security data: -Now we have a fully implemented DbProtect-to-OHDF mapper. +- What is the purpose of this field? -### Mapper Demo - JFrog +- What is this field recording (i.e., metadata, requirements, requirement testing)? -This section is yet another example of implementing an OHDF mapper, namely the JFrog-Xray mapper. Again, we will assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. Because we have already gone through several examples, this section will not explain too many things in detail. The goal is to simply provide more examples for reference. +2. Correlate your security data to the OHDF schema. Focus on correlating fields from order of obvious to less obvious. -Here is our developed mapping for JFrog-Xray for reference: +::: details Empty OHDF Schema -::: details JFrog-to-OHDF Mapping ```typescript { platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion, + name, + release, target_id }, - version: HeimdallToolsVersion, + version, statistics: { duration }, @@ -1712,23 +46,19 @@ Here is our developed mapping for JFrog-Xray for reference: groups, controls: [ { - id: 'data.id', // If ID empty, hash the summary - title: 'data.summary', - desc: 'component_versions.more_details', + id, + title, + desc, descriptions, - impact: 'data.severity', + impact, refs, - tags: { - nist: 'data.component_versions.more_details.cves[0].cwe', // Map to NIST - cci: 'data.component_versions.more_details.cves[0].cwe', // Map to CCI - cweid: 'data.component_versions.more_details.cves[0].cwe' - }, + tags, code, source_location, results: [ { - status: 'Failed', // All reported findings are failures - code_desc: ['data.source_comp_id', 'data.component_versions.vulnerable_versions', 'data.component_versions.fixed_versions', 'data.issue_type', 'data.provider'], + status, + code_desc, message, run_time, start_time @@ -1736,7 +66,7 @@ Here is our developed mapping for JFrog-Xray for reference: ] }, ], - status: 'loaded' + status }, ], passthrough: { @@ -1750,728 +80,140 @@ Here is our developed mapping for JFrog-Xray for reference: } } ``` -::: -::: details JFrog Source Data -```json -{ - "total_count": 30, - "data": [ - { - "id": "", - "severity": "High", - "summary": "Acorn regexp.js Regular Expression Validation UTF-16 Surrogate Handling Infinite Loop DoS", - "issue_type": "security", - "provider": "JFrog", - "component": "acorn", - "source_id": "npm://acorn", - "source_comp_id": "npm://acorn:5.7.3", - "component_versions": { - "id": "acorn", - "vulnerable_versions": [ - "5.5.0 ≤ Version < 5.7.4", - "6.0.0 ≤ Version < 6.4.1", - "7.0.0", - "7.1.0" - ], - "fixed_versions": [ - "5.7.4", - "6.4.1", - "7.1.1" - ], - "more_details": { - "cves": [ - { - "cvss_v2": "7.1/AV:N/AC:M/Au:N/C:N/I:N/A:C", - "cvss_v3": "7.5/CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H" - } - ], - "description": "Acorn contains an infinite loop condition in regexp.js that is triggered when handling UTF_16 surrogates while validating regular expressions. This may allow a context-dependent attacker to hang a process using the library.", - "provider": "JFrog" - } - }, - "edited": "2020-11-03T19:30:42-05:00" - }, - ] -} -``` ::: -We will now go over the mapper code that allows us to shape this data properly. Firstly, let us handle the ID. Sometimes, JFrog source files will not have an ID field. In this case, it is appropriate to generate a hash based on the `summary` as follows: - -```typescript -function hashId(vulnerability: unknown): string { - if (_.get(vulnerability, 'id') === '') { - return generateHash( - (_.get(vulnerability, 'summary') as unknown as string).toString(), - 'md5' - ); - } else { - return _.get(vulnerability, 'id') as unknown as string; - } -} -``` - -As with most mappers, we must also define an impact mapping: - -```typescript -const IMPACT_MAPPING: Map = new Map([ - ['high', 0.7], - ['medium', 0.5], - ['low', 0.3] -]); -``` - -Recall that we wanted to format the `desc` field based on the data in the source file's `component_versions.more_details`. We can write a simple transformer function to concatenate all these keys: -```typescript -function formatDesc(vulnerability: unknown): string { - const text = []; - if (_.has(vulnerability, 'description')) { - text.push( - (_.get(vulnerability, 'description') as unknown as string).toString() - ); - } - if (_.has(vulnerability, 'cves')) { - const re1 = /":/gi; - const re2 = /,/gi; - text.push( - `cves: ${JSON.stringify(_.get(vulnerability, 'cves')) - .replace(re1, '"=>') - .replace(re2, ', ')}` - ); - } - return text.join('
'); -} -``` - -We also must properly handle the mappings to NIST and CCI tags. Luckily, we can make use of the library's existing mappings, as well as an existing global function called `getCCIsForNISTTags()` in `global.ts`. -```typescript -const CWE_PATH = 'component_versions.more_details.cves[0].cwe'; -const CWE_NIST_MAPPING = new CweNistMapping(); - -function nistTag(identifier: Record): string[] { - const identifiers: string[] = []; - if (Array.isArray(identifier)) { - identifier.forEach((element) => { - if (element.split('CWE-')[1]) { - identifiers.push(element.split('CWE-')[1]); - } - }); - } - return CWE_NIST_MAPPING.nistFilter( - identifiers, - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS - ); -} -``` - -Finally, we can implement the transformer function for the `code_desc`. Some of these fields are optional, so it is important to implement a base case to ensure our `code_desc` outputs are all consistent. -```typescript -function formatCodeDesc(vulnerability: unknown): string { - const codeDescArray: string[] = []; - const re = /,/gi; - if (_.has(vulnerability, 'source_comp_id')) { - codeDescArray.push( - `source_comp_id : ${_.get(vulnerability, 'source_comp_id')}` - ); - } else { - codeDescArray.push('source_comp_id : '); - } - if (_.has(vulnerability, 'component_versions.vulnerable_versions')) { - codeDescArray.push( - `vulnerable_versions : ${JSON.stringify( - _.get(vulnerability, 'component_versions.vulnerable_versions') - )}` - ); - } else { - codeDescArray.push('vulnerable_versions : '); - } - if (_.has(vulnerability, 'component_versions.fixed_versions')) { - codeDescArray.push( - `fixed_versions : ${JSON.stringify( - _.get(vulnerability, 'component_versions.fixed_versions') - )}` - ); - } else { - codeDescArray.push('fixed_versions : '); - } - if (_.has(vulnerability, 'issue_type')) { - codeDescArray.push(`issue_type : ${_.get(vulnerability, 'issue_type')}`); - } else { - codeDescArray.push('issue_type : '); - } - if (_.has(vulnerability, 'provider')) { - codeDescArray.push(`provider : ${_.get(vulnerability, 'provider')}`); - } else { - codeDescArray.push('provider : '); - } - return codeDescArray.join('\n').replace(re, ', '); -} -``` - -All that's left is to incoporate all these functions into our `base-converter` structure, write some smaller transformer functions for the simpler data formatting tasks, and combine it all together! - -:::details Full Mapper Code -```typescript -import {ExecJSON} from 'inspecjs'; -import * as _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import { - BaseConverter, - generateHash, - ILookupPath, - impactMapping, - MappedTransform -} from './base-converter'; -import {CweNistMapping} from './mappings/CweNistMapping'; -import { - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, - getCCIsForNISTTags -} from './utils/global'; - -// Constants -const IMPACT_MAPPING: Map = new Map([ - ['high', 0.7], - ['medium', 0.5], - ['low', 0.3] -]); - -const CWE_PATH = 'component_versions.more_details.cves[0].cwe'; +3. Implement your mapping using the tools and resources provided in the [previous section](./14.md). -const CWE_NIST_MAPPING = new CweNistMapping(); +## JFrog Xray -// Transformation Functions -function hashId(vulnerability: unknown): string { - if (_.get(vulnerability, 'id') === '') { - return generateHash( - (_.get(vulnerability, 'summary') as unknown as string).toString(), - 'md5' - ); - } else { - return _.get(vulnerability, 'id') as unknown as string; - } -} -function formatDesc(vulnerability: unknown): string { - const text = []; - if (_.has(vulnerability, 'description')) { - text.push( - (_.get(vulnerability, 'description') as unknown as string).toString() - ); - } - if (_.has(vulnerability, 'cves')) { - const re1 = /":/gi; - const re2 = /,/gi; - text.push( - `cves: ${JSON.stringify(_.get(vulnerability, 'cves')) - .replace(re1, '"=>') - .replace(re2, ', ')}` - ); - } - return text.join('
'); -} -function formatCodeDesc(vulnerability: unknown): string { - const codeDescArray: string[] = []; - const re = /,/gi; - if (_.has(vulnerability, 'source_comp_id')) { - codeDescArray.push( - `source_comp_id : ${_.get(vulnerability, 'source_comp_id')}` - ); - } else { - codeDescArray.push('source_comp_id : '); - } - if (_.has(vulnerability, 'component_versions.vulnerable_versions')) { - codeDescArray.push( - `vulnerable_versions : ${JSON.stringify( - _.get(vulnerability, 'component_versions.vulnerable_versions') - )}` - ); - } else { - codeDescArray.push('vulnerable_versions : '); - } - if (_.has(vulnerability, 'component_versions.fixed_versions')) { - codeDescArray.push( - `fixed_versions : ${JSON.stringify( - _.get(vulnerability, 'component_versions.fixed_versions') - )}` - ); - } else { - codeDescArray.push('fixed_versions : '); - } - if (_.has(vulnerability, 'issue_type')) { - codeDescArray.push(`issue_type : ${_.get(vulnerability, 'issue_type')}`); - } else { - codeDescArray.push('issue_type : '); - } - if (_.has(vulnerability, 'provider')) { - codeDescArray.push(`provider : ${_.get(vulnerability, 'provider')}`); - } else { - codeDescArray.push('provider : '); - } - return codeDescArray.join('\n').replace(re, ', '); -} -function nistTag(identifier: Record): string[] { - const identifiers: string[] = []; - if (Array.isArray(identifier)) { - identifier.forEach((element) => { - if (element.split('CWE-')[1]) { - identifiers.push(element.split('CWE-')[1]); - } - }); - } - return CWE_NIST_MAPPING.nistFilter( - identifiers, - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS - ); -} +[Based on this mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/jfrog-xray-mapper.ts). -// Mappings -export class JfrogXrayMapper extends BaseConverter { - withRaw: boolean; +::: details Source Data - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - name: 'JFrog Xray Scan', - title: 'JFrog Xray Scan', - summary: 'Continuous Security and Universal Artifact Analysis', - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - path: 'data', - key: 'id', - tags: { - cci: { - path: CWE_PATH, - transformer: (identifier: Record) => - getCCIsForNISTTags(nistTag(identifier)) - }, - nist: { - path: CWE_PATH, - transformer: nistTag - }, - cweid: {path: CWE_PATH} - }, - refs: [], - source_location: {}, - id: {transformer: hashId}, - title: {path: 'summary'}, - desc: { - path: 'component_versions.more_details', - transformer: formatDesc - }, - impact: { - path: 'severity', - transformer: impactMapping(IMPACT_MAPPING) - }, - code: { - transformer: (vulnerability: Record): string => { - return JSON.stringify(vulnerability, null, 2); - } - }, - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, - code_desc: {transformer: formatCodeDesc}, - start_time: '' - } - ] - } +```json +{ + "total_count": 1, + "data": [ + { + "id": "", + "severity": "High", + "summary": "Acorn regexp.js Regular Expression Validation UTF-16 Surrogate Handling Infinite Loop DoS", + "issue_type": "security", + "provider": "JFrog", + "component": "acorn", + "source_id": "npm://acorn", + "source_comp_id": "npm://acorn:5.7.3", + "component_versions": { + "id": "acorn", + "vulnerable_versions": [ + "5.5.0 ≤ Version < 5.7.4", + "6.0.0 ≤ Version < 6.4.1", + "7.0.0", + "7.1.0" ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - return { - auxiliary_data: [ + "fixed_versions": ["5.7.4", "6.4.1", "7.1.1"], + "more_details": { + "cves": [ { - name: 'JFrog Xray', - data: _.pick(data, ['total_count']) + "cvss_v2": "7.1/AV:N/AC:M/Au:N/C:N/I:N/A:C", + "cvss_v3": "7.5/CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H" } ], - ...(this.withRaw && {raw: data}) - }; - } + "description": "Acorn contains an infinite loop condition in regexp.js that is triggered when handling UTF_16 surrogates while validating regular expressions. This may allow a context-dependent attacker to hang a process using the library.", + "provider": "JFrog" + } + }, + "edited": "2020-11-03T19:30:42-05:00" } - }; - constructor(xrayJson: string, withRaw = false) { - super(JSON.parse(xrayJson), true); - this.withRaw = withRaw; - } + ] } ``` ::: -Now we have a fully implemented JFrog-to-OHDF mapper. - +## Twistlock -### Mapper Demo - SARIF +[Based on this mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/twistlock-mapper.ts). -Here is one last example of implementing an OHDF mapper - the SARIF mapper. As in previous examples, we will assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. Like with the JFrog example, we will not be going into too much detail regarding the mapping itself. The goal is to simply provide more examples for reference. +::: details Source Data -Here is our developed mapping for SARIF for reference: - -::: details SARIF-to-OHDF Mapping -```typescript +```json { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion, - target_id - }, - version: HeimdallToolsVersion, - statistics: { - duration - }, - profiles: [ + "results": [ { - name, - version: 'version', - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ + "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", + "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", + "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", + "distroRelease": "RHEL8", + "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", + "collections": ["All", "TEST-COLLECTION"], + "packages": [ { - id: 'results.ruleId', // If ID empty, hash the summary - title: 'results.message.text', - desc: 'results.message.text', - descriptions, - impact: 'results.level', - refs, - tags: { - nist: 'results.message.text', // Map to NIST - cci: 'results.message.text', // Map to CCI - cwe: 'results.message.text' - }, - code, - source_location: ['results.locations[0].physicalLocation.artifactLocation.uri', 'results.locations[0].physicalLocation.region.startLine'], - results: [ - { - status: 'Failed', // All reported findings are failures - code_desc: 'results.locations[0].physicalLocation', - message, - run_time, - start_time - } - ] - }, + "type": "os", + "name": "nss-util", + "version": "3.67.0-7.el8_5", + "licenses": ["MPLv2.0"] + } ], - status: 'loaded' - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data + "applications": [ + { + "name": ".net-core", + "version": "5.0.17", + "path": "/usr/lib64/dotnet/dotnet" + } + ], + "complianceDistribution": { + "critical": 0, + "high": 0, + "medium": 0, + "low": 0, + "total": 0 }, - ], - raw - } -} -``` -::: - -::: details SARIF Source Data -```json -{ - "$schema": "https://schemastore.azurewebsites.net/schemas/json/sarif-2.1.0-rtm.5.json", - "version": "2.1.0", - "runs": [ + "complianceScanPassed": true, + "vulnerabilities": [ { - "results": [ - { - "ruleId": "FF1014", - "level": "error", - "message": { - "text": "buffer/gets: Does not check for buffer overflows (CWE-120, CWE-20)." - }, - "locations": [ - { - "physicalLocation": { - "artifactLocation": { - "uri": "test/test-patched.c", - "uriBaseId": "SRCROOT" - }, - "region": { - "startLine": 36, - "startColumn": 2, - "endColumn": 10, - "snippet": { - "text": " gets(f);" - } - } - } - } - ], - "fingerprints": { - "contextHash/v1": "6a5bb383fb44030b0d9428b17359e94ba3979bc1ce702be450427f85592c649a" - }, - "rank": 1 - }, - ] + "id": "CVE-2021-43529", + "status": "affected", + "cvss": 9.8, + "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", + "severity": "critical", + "packageName": "nss-util", + "packageVersion": "3.67.0-7.el8_5", + "link": "https://access.redhat.com/security/cve/CVE-2021-43529", + "riskFactors": [ + "Remote execution", + "Attack complexity: low", + "Attack vector: network", + "Critical severity", + "Recent vulnerability" + ], + "impactedVersions": ["*"], + "publishedDate": "2021-12-01T00:00:00Z", + "discoveredDate": "2022-05-18T12:24:22Z", + "layerTime": "2022-05-16T23:12:25Z" } - ] -} -``` -::: - -First, let us define some common constants that might help us with our code. -```typescript -const MESSAGE_TEXT = 'message.text'; -const CWE_NIST_MAPPING = new CweNistMapping(); -``` - -We will now outline the `IMPACT_MAPPING` for the SARIF mapper: -```typescript -const IMPACT_MAPPING: Map = new Map([ - ['error', 0.7], - ['warning', 0.5], - ['note', 0.3] -]); - -function impactMapping(severity: unknown): number { - if (typeof severity === 'string' || typeof severity === 'number') { - return IMPACT_MAPPING.get(severity.toString().toLowerCase()) || 0.1; - } else { - return 0.1; - } -} -``` - -Now, note that we will need to extract the CWEs from the message text, as well as map them to the proper NIST tags. For the CCIs, we can again use the global function `getCCIsForNISTTags()`. - -```typescript -function extractCwe(text: string): string[] { - let output = text.split('(').slice(-1)[0].slice(0, -2).split(', '); - if (output.length === 1) { - output = text.split('(').slice(-1)[0].slice(0, -2).split('!/'); - } - return output; -} -function nistTag(text: string): string[] { - let identifiers = extractCwe(text); - identifiers = identifiers.map((element) => element.split('-')[1]); - return CWE_NIST_MAPPING.nistFilter( - identifiers, - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS - ); -} -``` - -Our last standalone transformer function will format our code description. This part is up to interpretation, but we decided to just concatenate them all with colon-separated key-value pairs -```typescript -function formatCodeDesc(input: unknown): string { - const output = []; - output.push(`URL : ${_.get(input, 'artifactLocation.uri')}`); - output.push(`LINE : ${_.get(input, 'region.startLine')}`); - output.push(`COLUMN : ${_.get(input, 'region.startColumn')}`); - return output.join(' '); -} -``` - -Now, all that's left is to combine our functions, write some mini-transformers for the small data formatting, and plug it all into the base converter! - - -:::details Full Mapper Code -```typescript -import {ExecJSON} from 'inspecjs'; -import * as _ from 'lodash'; -import {version as HeimdallToolsVersion} from '../package.json'; -import {BaseConverter, ILookupPath, MappedTransform} from './base-converter'; -import {CweNistMapping} from './mappings/CweNistMapping'; -import { - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, - getCCIsForNISTTags -} from './utils/global'; - -const IMPACT_MAPPING: Map = new Map([ - ['error', 0.7], - ['warning', 0.5], - ['note', 0.3] -]); -const MESSAGE_TEXT = 'message.text'; -const CWE_NIST_MAPPING = new CweNistMapping(); - -function extractCwe(text: string): string[] { - let output = text.split('(').slice(-1)[0].slice(0, -2).split(', '); - if (output.length === 1) { - output = text.split('(').slice(-1)[0].slice(0, -2).split('!/'); - } - return output; -} -function impactMapping(severity: unknown): number { - if (typeof severity === 'string' || typeof severity === 'number') { - return IMPACT_MAPPING.get(severity.toString().toLowerCase()) || 0.1; - } else { - return 0.1; - } -} -function formatCodeDesc(input: unknown): string { - const output = []; - output.push(`URL : ${_.get(input, 'artifactLocation.uri')}`); - output.push(`LINE : ${_.get(input, 'region.startLine')}`); - output.push(`COLUMN : ${_.get(input, 'region.startColumn')}`); - return output.join(' '); -} -function nistTag(text: string): string[] { - let identifiers = extractCwe(text); - identifiers = identifiers.map((element) => element.split('-')[1]); - return CWE_NIST_MAPPING.nistFilter( - identifiers, - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS - ); -} - -export class SarifMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & {passthrough: unknown}, - ILookupPath - > = { - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion, - target_id: 'Static Analysis Results Interchange Format' - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - path: 'runs', - name: 'SARIF', - version: {path: '$.version'}, - title: 'Static Analysis Results Interchange Format', - supports: [], - attributes: [], - groups: [], - status: 'loaded', - controls: [ - { - path: 'results', - key: 'id', - tags: { - cci: { - path: MESSAGE_TEXT, - transformer: (data: string) => getCCIsForNISTTags(nistTag(data)) - }, - nist: {path: MESSAGE_TEXT, transformer: nistTag}, - cwe: { - path: MESSAGE_TEXT, - transformer: extractCwe - } - }, - refs: [], - source_location: { - transformer: (control: unknown) => { - return _.omitBy( - { - ref: _.get( - control, - 'locations[0].physicalLocation.artifactLocation.uri' - ), - line: _.get( - control, - 'locations[0].physicalLocation.region.startLine' - ) - }, - (value) => value === '' - ); - } - }, - title: { - path: MESSAGE_TEXT, - transformer: (text: unknown): string => { - if (typeof text === 'string') { - return text.split(': ')[0]; - } else { - return ''; - } - } - }, - id: {path: 'ruleId'}, - desc: { - path: MESSAGE_TEXT, - transformer: (text: unknown): string => { - if (typeof text === 'string') { - return text.split(': ')[1]; - } else { - return ''; - } - } - }, - impact: {path: 'level', transformer: impactMapping}, - code: { - transformer: (vulnerability: Record): string => - JSON.stringify(vulnerability, null, 2) - }, - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, - code_desc: { - path: 'locations[0].physicalLocation', - transformer: formatCodeDesc - }, - - start_time: '' - } - ] - } - ], - sha256: '' - } - ], - passthrough: { - transformer: (data: Record): Record => { - let runsData = _.get(data, 'runs'); - if (Array.isArray(runsData)) { - runsData = runsData.map((run: Record) => - _.omit(run, ['results']) - ); + ], + "vulnerabilityDistribution": { + "critical": 1, + "high": 0, + "medium": 0, + "low": 0, + "total": 1 + }, + "vulnerabilityScanPassed": true, + "history": [ + { + "created": "2022-05-16T23:12:02Z", + "instruction": "ARG GOPROXY=http://nexus-repository-manager.nexus-repository-manager.svc.cluster.local:8081/repository/goproxy/ HTTP_PROXY=http://localhost:3128 http_proxy=http://localhost:3128" } - return { - auxiliary_data: [ - { - name: 'SARIF', - data: { - $schema: _.get(data, '$schema'), - runs: runsData - } - } - ], - ...(this.withRaw && {raw: data}) - }; - } + ], + "scanTime": "2022-05-18T12:24:32.855444532Z", + "scanID": "6284e580d9600f8d0db159e2" } - }; - constructor(sarifJson: string, withRaw = false) { - super(JSON.parse(sarifJson)); - this.withRaw = withRaw; - } + ], + "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" } ``` ::: - -Now we have a fully implemented SARIF-to-OHDF mapper. diff --git a/src/courses/mappers/15.md b/src/courses/mappers/15.md index 2de68883a..7884f90a0 100644 --- a/src/courses/mappers/15.md +++ b/src/courses/mappers/15.md @@ -1,46 +1,24 @@ --- order: 15 next: 16.md -title: Finalizing the Mapper +title: Next Steps author: Charles Hu --- -## Mapper Finalization +## Next Steps -Now that we have a mapper developed that can convert files from *-to-OHDF, we need to perform some final touches to make sure that our mapper works and can be integrated into OHDF Converters. +### Take Our Survey -### Using Regression Testing +Take our brief, anonymous [survey](https://forms.office.com/g/6JnMN8tYnD) to help improve the class. -Regression testing is extremely useful, as we make changes and improvements to mappers over time (for example, if we have new sample files or if the schema of a source format changes). Moreover, internal library changes, like an update to `base-converter`, or major dependency updates could change the behavior of a mapper significantly. If a particular change affects a mapping, we will need to regenerate the sample file through the following process: +### Take Our Other Security Automation Framework Classes -First, we have to activate the regression testing suite that we created earlier to actually be able to automatically run and review your mapper. +This class is part of a series of security automation content classes offered by the MITRE SAF team. If you found this content interesting and want to learn about more topics, like writing InSpec resources, we encourage you to check out the other classes provided (shown in the side bar on the left). -1. Uncomment out the commented out lines in the `{YOUR-SAMPLE-EXPORT}-hdf.json` file. This will allow the regression tests to automatically generate an OHDF output file whenever you run the tests. These files are needed for the tests to check the output of your mappers. The commented out lines should look similar to the following: -```typescript -// fs.writeFileSync( -// 'sample_jsons/SKELETON_mapper/SKELETON-hdf.json', -// JSON.stringify(mapper.toHdf(), null, 2) -// ); -``` +### Check Out the Rest of MITRE SAF's Content -2. Using the terminal, `cd` into the `hdf-converters` directory and run the following command. This command will run your mapper against the sample export file in `sample_jsons` and tests to see if the output is generated as expected. However, this initial run will be used to create a baseline OHDF file for manual inspection to validate that we wrote the mapper properly and thereafter will be the comparison target for future runs to confirm that no regressions in the mapping occurred. -```shell -yarn run test --verbose --silent=false ./test/mappers/forward/{YOUR-EXPORT-NAME-HERE}_mapper.spec.ts -``` +MITRE SAF is a large collection of tools and techniques for security automation in addition to those discussed in this class. You can find utilities and libraries to support any step of the software development lifecycle by browsing our offerings at [saf.mitre.org](https://saf.mitre.org). Note that everything offered by MITRE SAF is open-source and available to use free of charge. You can also reference all of the resources listed from this class in the [Resources page](../../resources/README.md). -3. After running this command, you should see two files named `SKELETON-hdf.json` and `SKELETON-hdf-withraw.json` appear in the `sample_jsons/SKELETON_mapper/` directory. Check these files to make sure that the OHDF mapper output looks correct and aligns with your mapping. `SKELETON-hdf.json` should match your mapping completely, while `SKELETON-hdf-withraw.json` should also include your original source data in the OHDF output file. +### Contact Us -4. Recomment out the lines from step 1. - -3. Future uses of the command in step 2 will now leverage the baseline files you generated to perform regression testing. It will compare the contents of these generated files with temporary outputs created by the mapper instance to check for field alignment. Review the test output to ensure that the tests are all passing. - -### Documentation - -Document your new mapper in the `README.md` file for `hdf-converters` under the `Supported Formats` section. It should be formatted as follows: -```markdown -{#}. [{YOUR-EXPORT-NAME-HERE}] - {MAPPER INPUT DESCRIPTION} -``` - -### GitHub Merging - -Commit your final changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, your mapper will be merged into the main development branch and [scheduled for release](https://github.com/mitre/heimdall2/wiki/How-to-create-a-Heimdall2-release) as an officially supported conversion format for OHDF Converters. +The MITRE SAF team supports U.S. government sponsors in developing new tools for the Framework and implementing existing ones in DevSecOps pipelines. If you have a question about how you can use any of the content you saw in this class in your own environment, contact us at [saf@groups.mitre.org](mailto:saf@groups.mitre.org). diff --git a/src/courses/mappers/16.md b/src/courses/mappers/16.md index 6c4b6ec51..5a5e2961f 100644 --- a/src/courses/mappers/16.md +++ b/src/courses/mappers/16.md @@ -1,213 +1,291 @@ --- order: 16 -next: 17.md -title: More Practice +title: Appendix - SAF CLI Integration author: Charles Hu --- -The following are some practice source data sets to create mappers with. +## SAF CLI Integration -Before you begin, recall the steps we took previously to develop our GoSec and DBProtect mappers: +The following is a supplemental lesson on how to integrate your developed mapper with the SAF CLI. Integration with the SAF CLI will allow your mapper to be used in a command line environment, independent of Heimdall2 throughout. -1. Examine and break down the security data format. Remember to ask yourself the following questions while analyzing the fields of your security data: +If you have not yet created a mapper, please follow the primary course and do so. Once completed, you will be able to continue with this lesson. -- What is the purpose of this field? +### Set Up -- What is this field recording (i.e., metadata, requirements, requirement testing)? +First, we need set up the necessary files to begin integrating your mapper with the SAF CLI. -2. Correlate your security data to the OHDF schema. Focus on correlating fields from order of obvious to less obvious. +1. Create a development branch against the [SAF CLI repository](https://github.com/mitre/saf) and create a draft pull request for your new branch. + +2. In the `package.json` file, update the versions of `@mitre/hdf-converters` and `@mitre/heimdall-lite` to the [latest release of Heimdall2](https://github.com/mitre/heimdall2/releases). + +3. In the `src/commands/convert` directory, create a blank TypeScript file. It should be named: + +``` +{YOUR-EXPORT-NAME-HERE}2hdf.ts +``` + +4. In the `test/sample_data` directory, create a directory named `{YOUR-EXPORT-NAME-HERE}`. Underneath it, create a directory named `sample_input_report`. The file structure should now look like this: + +``` ++-- sample_data +| +-- {YOUR-EXPORT-NAME-HERE} +| | +-- sample_input_report +``` + +5. Place your sample export under the `sample_input_report` directory. Your sample export should be genericized to avoid any leaking of sensitive information. Under the `{YOUR-EXPORT-NAME-HERE}` directory, place your output OHDF files generated during the original testing phase of your mapper development. The file structure should now look like this: + +``` ++-- sample_data +| +-- {YOUR-EXPORT-NAME-HERE} +| | +-- sample_input_report +| | | +-- {YOUR-SAMPLE-EXPORT} +| | +-- {YOUR-EXPORT-NAME-HERE}-hdf.json +| | +-- {YOUR-EXPORT-NAME-HERE}-hdf-withraw.json +``` + +6. In the `test/commands/convert` directory, create a blank TypeScript file. It should be named: + +``` +{YOUR-EXPORT-NAME-HERE}2hdf.test.ts +``` + +### Integration + +::: note APIs +If your security tool provides an API instead of a security data export, you will need to explore the API to determine what information may need to be collected and collated for use in the `convert` command. For further guidance, refer to [previous API-based command implementations](https://github.com/mitre/saf/tree/main/src/commands/convert) or contact the SAF team for help. +::: + +With file set up out of the way, we can begin filling out the necessary files to create a `saf convert` command for our mapper. + +::: info +For further guidance on writing good usage strings for command line interfaces, refer [here](http://docopt.org/). +::: + +1. Insert the skeleton convert command file (see below) in the file `{YOUR-EXPORT-NAME-HERE}2hdf.ts` which you created earlier. Replace names (`SKELETON` by default) as necessary. + +::: details Skeleton Convert Command File -::: details Empty OHDF Schema ```typescript -{ - platform: { - name, - release, - target_id - }, - version, - statistics: { - duration - }, - profiles: [ - { - name, - version, - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id, - title, - desc, - descriptions, - impact, - refs, - tags, - code, - source_location, - results: [ - { - status, - code_desc, - message, - run_time, - start_time - } - ] - }, - ], - status - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw +import {Command, Flags} from '@oclif/core' +import fs from 'fs' +import {SKELETONMapper as Mapper} from '@mitre/hdf-converters' +import {checkSuffix} from '../../utils/global' + +export default class SKELETON2HDF extends Command { + static usage = 'convert SKELETON2hdf -i -o ' + + static description = 'Translate a SKELETON output file into an HDF results set' + + static examples = ['saf convert SKELETON2hdf -i SKELETON.json -o output-hdf-name.json'] + + static flags = { + help: Flags.help({char: 'h'}), + input: Flags.string({char: 'i', required: true, description: 'Input SKELETON file'}), + output: Flags.string({char: 'o', required: true, description: 'Output HDF file'}), + 'with-raw': Flags.boolean({char: 'w', required: false}), + } + + async run() { + const {flags} = await this.parse(SKELETON2HDF) + const input = fs.readFileSync(flags.input, 'utf8') + + const converter = new Mapper(input, flags.['with-raw']) + fs.writeFileSync(checkSuffix(flags.output), JSON.stringify(converter.toHdf())) } } ``` + +::: + +2. Insert the appropriate skeleton convert command test file (see below) in the file `{YOUR-EXPORT-NAME-HERE}2hdf.test.ts` which you created earlier. Replace names (`SKELETON` by default) as necessary. + +::: details JSON Skeleton Convert Command Test File + +```typescript +import { expect, test } from "@oclif/test"; +import tmp from "tmp"; +import path from "path"; +import fs from "fs"; +import { omitHDFChangingFields } from "../utils"; + +describe("Test SKELETON", () => { + const tmpobj = tmp.dirSync({ unsafeCleanup: true }); + + test + .stdout() + .command([ + "convert SKELETON2hdf", + "-i", + path.resolve( + "./test/sample_data/SKELETON/sample_input_report/SKELETON_sample.json" + ), + "-o", + `${tmpobj.name}/SKELETONtest.json`, + ]) + .it("hdf-converter output test", () => { + const converted = JSON.parse( + fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, "utf8") + ); + const sample = JSON.parse( + fs.readFileSync( + path.resolve("./test/sample_data/SKELETON/SKELETON-hdf.json"), + "utf8" + ) + ); + expect(omitHDFChangingFields(converted)).to.eql( + omitHDFChangingFields(sample) + ); + }); +}); + +describe("Test SKELETON withraw flag", () => { + const tmpobj = tmp.dirSync({ unsafeCleanup: true }); + + test + .stdout() + .command([ + "convert SKELETON2hdf", + "-i", + path.resolve( + "./test/sample_data/SKELETON/sample_input_report/SKELETON_sample.json" + ), + "-o", + `${tmpobj.name}/SKELETONtest.json`, + "-w", + ]) + .it("hdf-converter withraw output test", () => { + const converted = JSON.parse( + fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, "utf8") + ); + const sample = JSON.parse( + fs.readFileSync( + path.resolve("./test/sample_data/SKELETON/SKELETON-hdf-withraw.json"), + "utf8" + ) + ); + expect(omitHDFChangingFields(converted)).to.eql( + omitHDFChangingFields(sample) + ); + }); +}); +``` + ::: -3. Implement your mapping using the tools and resources provided in the [previous section](./14.md). - -## JFrog Xray - -[Based on this mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/jfrog-xray-mapper.ts). - -::: details Source Data -```json -{ - "total_count": 1, - "data": [ - { - "id": "", - "severity": "High", - "summary": "Acorn regexp.js Regular Expression Validation UTF-16 Surrogate Handling Infinite Loop DoS", - "issue_type": "security", - "provider": "JFrog", - "component": "acorn", - "source_id": "npm://acorn", - "source_comp_id": "npm://acorn:5.7.3", - "component_versions": { - "id": "acorn", - "vulnerable_versions": [ - "5.5.0 ≤ Version < 5.7.4", - "6.0.0 ≤ Version < 6.4.1", - "7.0.0", - "7.1.0" - ], - "fixed_versions": ["5.7.4", "6.4.1", "7.1.1"], - "more_details": { - "cves": [ - { - "cvss_v2": "7.1/AV:N/AC:M/Au:N/C:N/I:N/A:C", - "cvss_v3": "7.5/CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H" - } - ], - "description": "Acorn contains an infinite loop condition in regexp.js that is triggered when handling UTF_16 surrogates while validating regular expressions. This may allow a context-dependent attacker to hang a process using the library.", - "provider": "JFrog" - } - }, - "edited": "2020-11-03T19:30:42-05:00" - } - ] -} +::: details XML Skeleton Convert Command Test File + +```typescript +import { expect, test } from "@oclif/test"; +import tmp from "tmp"; +import path from "path"; +import fs from "fs"; +import { omitHDFChangingFields } from "../utils"; + +describe("Test SKELETON", () => { + const tmpobj = tmp.dirSync({ unsafeCleanup: true }); + + test + .stdout() + .command([ + "convert SKELETON2hdf", + "-i", + path.resolve( + "./test/sample_data/SKELETON/sample_input_report/SKELETON_sample.xml" + ), + "-o", + `${tmpobj.name}/SKELETONtest.json`, + ]) + .it("hdf-converter output test", () => { + const converted = JSON.parse( + fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, "utf8") + ); + const sample = JSON.parse( + fs.readFileSync( + path.resolve("./test/sample_data/SKELETON/SKELETON-hdf.json"), + "utf8" + ) + ); + expect(omitHDFChangingFields(converted)).to.eql( + omitHDFChangingFields(sample) + ); + }); +}); + +describe("Test SKELETON withraw flag", () => { + const tmpobj = tmp.dirSync({ unsafeCleanup: true }); + + test + .stdout() + .command([ + "convert SKELETON2hdf", + "-i", + path.resolve( + "./test/sample_data/SKELETON/sample_input_report/SKELETON_sample.xml" + ), + "-o", + `${tmpobj.name}/SKELETONtest.json`, + "-w", + ]) + .it("hdf-converter withraw output test", () => { + const converted = JSON.parse( + fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, "utf8") + ); + const sample = JSON.parse( + fs.readFileSync( + path.resolve("./test/sample_data/SKELETON/SKELETON-hdf-withraw.json"), + "utf8" + ) + ); + expect(omitHDFChangingFields(converted)).to.eql( + omitHDFChangingFields(sample) + ); + }); +}); ``` + ::: -## Twistlock - -[Based on this mapper](https://github.com/mitre/heimdall2/blob/master/libs/hdf-converters/src/twistlock-mapper.ts). - -::: details Source Data -```json -{ - "results": [ - { - "id": "sha256:b1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b", - "name": "registry.io/test:1a7a431a105aa04632f5f5fbe8f753bd245add0a", - "distro": "Red Hat Enterprise Linux release 8.6 (Ootpa)", - "distroRelease": "RHEL8", - "digest": "sha256:c0274cb1e0c6e92d2ccc1e23bd19b7dddedbaa2da26861c225d4ad6cec5047f4", - "collections": ["All", "TEST-COLLECTION"], - "packages": [ - { - "type": "os", - "name": "nss-util", - "version": "3.67.0-7.el8_5", - "licenses": ["MPLv2.0"] - } - ], - "applications": [ - { - "name": ".net-core", - "version": "5.0.17", - "path": "/usr/lib64/dotnet/dotnet" - } - ], - "complianceDistribution": { - "critical": 0, - "high": 0, - "medium": 0, - "low": 0, - "total": 0 - }, - "complianceScanPassed": true, - "vulnerabilities": [ - { - "id": "CVE-2021-43529", - "status": "affected", - "cvss": 9.8, - "description": "DOCUMENTATION: A remote code execution flaw was found in the way NSS verifies certificates. This flaw allows an attacker posing as an SSL/TLS server to trigger this issue in a client application compiled with NSS when it tries to initiate an SSL/TLS connection. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client, triggering the flaw. The highest threat to this vulnerability is confidentiality, integrity, as well as system availability. STATEMENT: The issue is not limited to TLS. Any applications that use NSS certificate verification are vulnerable; S/MIME is impacted as well. Similarly, a server application compiled with NSS, which processes client certificates, can receive a malicious certificate via a client. Firefox is not vulnerable to this flaw as it uses the mozilla::pkix for certificate verification. Thunderbird is affected when parsing email with the S/MIME signature. Thunderbird on Red Hat Enterprise Linux 8.4 and later does not need to be updated since it uses the system NSS library, but earlier Red Hat Enterprise Linux 8 extended life streams will need to update Thunderbird as well as NSS. MITIGATION: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affec", - "severity": "critical", - "packageName": "nss-util", - "packageVersion": "3.67.0-7.el8_5", - "link": "https://access.redhat.com/security/cve/CVE-2021-43529", - "riskFactors": [ - "Remote execution", - "Attack complexity: low", - "Attack vector: network", - "Critical severity", - "Recent vulnerability" - ], - "impactedVersions": ["*"], - "publishedDate": "2021-12-01T00:00:00Z", - "discoveredDate": "2022-05-18T12:24:22Z", - "layerTime": "2022-05-16T23:12:25Z" - } - ], - "vulnerabilityDistribution": { - "critical": 1, - "high": 0, - "medium": 0, - "low": 0, - "total": 1 - }, - "vulnerabilityScanPassed": true, - "history": [ - { - "created": "2022-05-16T23:12:02Z", - "instruction": "ARG GOPROXY=http://nexus-repository-manager.nexus-repository-manager.svc.cluster.local:8081/repository/goproxy/ HTTP_PROXY=http://localhost:3128 http_proxy=http://localhost:3128" - } - ], - "scanTime": "2022-05-18T12:24:32.855444532Z", - "scanID": "6284e580d9600f8d0db159e2" - } - ], - "consoleURL": "https://twistlock.test.net/#!/monitor/vulnerabilities/images/ci?search=sha256%3Ab1c0237ebd29860066656372da10d8d7da33b34715986f74b3d5a7e4ba060d1b" +3. Navigate to the `index.ts` file under the `src/commands/convert` directory. Import your mapper using the existing import block as follows: + +```typescript +import { + ASFFResults, + ... + {YOUR-MAPPER-CLASS-HERE} +} from '@mitre/hdf-converters' +``` + +4. Under the switch block in the `getFlagsForInputFile` function, add your mapper class as it is defined for fingerprinting for the generic convert command. If the convert command for your mapper has any additional flags beyond the standard `--input` and `--output` flags, return the entire flag block in the switch case. This is demonstrated as follows: + +```typescript +switch (Convert.detectedType) { + ... + case {YOUR-EXPORT-SERVICE-NAME-HERE}: + return {YOUR-CLI-CONVERT-CLASS}.flags //Only add if special flags exist + ... + return {} } ``` -::: + +5. Edit the `README.md` file to reflect your newly added conversion command under the `Convert To HDF` section. It should be formatted as follows: + +````markdown +##### {YOUR-EXPORT-NAME-HERE} to HDF + +\``` +convert {YOUR-EXPORT-NAME-HERE}2hdf Translate a {YOUR-EXPORT-NAME-HERE} results {EXPORT-TYPE} into an HDF results set + +USAGE +$ saf convert {YOUR-EXPORT-NAME-HERE}hdf -i <{INPUT-NAME}> -o + +OPTIONS +-i, --input=input Input {EXPORT-TYPE} File +-o, --output=output Output HDF JSON File +-w, --with-raw Include raw input file in HDF JSON file + +EXAMPLES +$ saf convert {YOUR-EXPORT-NAME-HERE}2hdf -i {INPUT-NAME} -o output-hdf-name.json +\``` +```` + +5. Commit your changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, merged, and [released](https://github.com/mitre/saf/wiki/Creating-a-Release-of-the-SAF-CLI), your mapper will be callable using the SAF CLI. diff --git a/src/courses/mappers/17.md b/src/courses/mappers/17.md deleted file mode 100644 index 42dcfd1de..000000000 --- a/src/courses/mappers/17.md +++ /dev/null @@ -1,24 +0,0 @@ ---- -order: 17 -next: 18.md -title: Next Steps -author: Charles Hu ---- - -## Next Steps - -### Take Our Survey - -Take our brief, anonymous [survey](https://forms.office.com/g/6JnMN8tYnD) to help improve the class. - -### Take Our Other Security Automation Framework Classes - -This class is part of a series of security automation content classes offered by the MITRE SAF team. If you found this content interesting and want to learn about more topics, like writing InSpec resources, we encourage you to check out the other classes provided (shown in the side bar on the left). - -### Check Out the Rest of MITRE SAF's Content - -MITRE SAF is a large collection of tools and techniques for security automation in addition to those discussed in this class. You can find utilities and libraries to support any step of the software development lifecycle by browsing our offerings at [saf.mitre.org](https://saf.mitre.org). Note that everything offered by MITRE SAF is open-source and available to use free of charge. You can also reference all of the resources listed from this class in the [Resources page](../../resources/README.md). - -### Contact Us - -The MITRE SAF team supports U.S. government sponsors in developing new tools for the Framework and implementing existing ones in DevSecOps pipelines. If you have a question about how you can use any of the content you saw in this class in your own environment, contact us at [saf@groups.mitre.org](mailto:saf@groups.mitre.org). diff --git a/src/courses/mappers/18.md b/src/courses/mappers/18.md deleted file mode 100644 index 08e6adfaa..000000000 --- a/src/courses/mappers/18.md +++ /dev/null @@ -1,279 +0,0 @@ ---- -order: 18 -title: Appendix - SAF CLI Integration -author: Charles Hu ---- - -## SAF CLI Integration - -The following is a supplemental lesson on how to integrate your developed mapper with the SAF CLI. Integration with the SAF CLI will allow your mapper to be used in a command line environment, independent of Heimdall2 throughout. - -If you have not yet created a mapper, please follow the primary course and do so. Once completed, you will be able to continue with this lesson. - -### Set Up - -First, we need set up the necessary files to begin integrating your mapper with the SAF CLI. - -1. Create a development branch against the [SAF CLI repository](https://github.com/mitre/saf) and create a draft pull request for your new branch. - -2. In the `package.json` file, update the versions of `@mitre/hdf-converters` and `@mitre/heimdall-lite` to the [latest release of Heimdall2](https://github.com/mitre/heimdall2/releases). - -3. In the `src/commands/convert` directory, create a blank TypeScript file. It should be named: -``` -{YOUR-EXPORT-NAME-HERE}2hdf.ts -``` - -4. In the `test/sample_data` directory, create a directory named `{YOUR-EXPORT-NAME-HERE}`. Underneath it, create a directory named `sample_input_report`. The file structure should now look like this: -``` -+-- sample_data -| +-- {YOUR-EXPORT-NAME-HERE} -| | +-- sample_input_report -``` - -5. Place your sample export under the `sample_input_report` directory. Your sample export should be genericized to avoid any leaking of sensitive information. Under the `{YOUR-EXPORT-NAME-HERE}` directory, place your output OHDF files generated during the original testing phase of your mapper development. The file structure should now look like this: -``` -+-- sample_data -| +-- {YOUR-EXPORT-NAME-HERE} -| | +-- sample_input_report -| | | +-- {YOUR-SAMPLE-EXPORT} -| | +-- {YOUR-EXPORT-NAME-HERE}-hdf.json -| | +-- {YOUR-EXPORT-NAME-HERE}-hdf-withraw.json -``` - -6. In the `test/commands/convert` directory, create a blank TypeScript file. It should be named: -``` -{YOUR-EXPORT-NAME-HERE}2hdf.test.ts -``` - -### Integration - -::: note APIs -If your security tool provides an API instead of a security data export, you will need to explore the API to determine what information may need to be collected and collated for use in the `convert` command. For further guidance, refer to [previous API-based command implementations](https://github.com/mitre/saf/tree/main/src/commands/convert) or contact the SAF team for help. -::: - -With file set up out of the way, we can begin filling out the necessary files to create a `saf convert` command for our mapper. - -::: info -For further guidance on writing good usage strings for command line interfaces, refer [here](http://docopt.org/). -::: - -1. Insert the skeleton convert command file (see below) in the file `{YOUR-EXPORT-NAME-HERE}2hdf.ts` which you created earlier. Replace names (`SKELETON` by default) as necessary. - -::: details Skeleton Convert Command File -```typescript -import {Command, Flags} from '@oclif/core' -import fs from 'fs' -import {SKELETONMapper as Mapper} from '@mitre/hdf-converters' -import {checkSuffix} from '../../utils/global' - -export default class SKELETON2HDF extends Command { - static usage = 'convert SKELETON2hdf -i -o ' - - static description = 'Translate a SKELETON output file into an HDF results set' - - static examples = ['saf convert SKELETON2hdf -i SKELETON.json -o output-hdf-name.json'] - - static flags = { - help: Flags.help({char: 'h'}), - input: Flags.string({char: 'i', required: true, description: 'Input SKELETON file'}), - output: Flags.string({char: 'o', required: true, description: 'Output HDF file'}), - 'with-raw': Flags.boolean({char: 'w', required: false}), - } - - async run() { - const {flags} = await this.parse(SKELETON2HDF) - const input = fs.readFileSync(flags.input, 'utf8') - - const converter = new Mapper(input, flags.['with-raw']) - fs.writeFileSync(checkSuffix(flags.output), JSON.stringify(converter.toHdf())) - } -} -``` -::: - -2. Insert the appropriate skeleton convert command test file (see below) in the file `{YOUR-EXPORT-NAME-HERE}2hdf.test.ts` which you created earlier. Replace names (`SKELETON` by default) as necessary. - -::: details JSON Skeleton Convert Command Test File -```typescript -import {expect, test} from '@oclif/test' -import tmp from 'tmp' -import path from 'path' -import fs from 'fs' -import {omitHDFChangingFields} from '../utils' - -describe('Test SKELETON', () => { - const tmpobj = tmp.dirSync({unsafeCleanup: true}) - - test - .stdout() - .command([ - 'convert SKELETON2hdf', - '-i', - path.resolve( - './test/sample_data/SKELETON/sample_input_report/SKELETON_sample.json', - ), - '-o', - `${tmpobj.name}/SKELETONtest.json`, - ]) - .it('hdf-converter output test', () => { - const converted = JSON.parse( - fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, 'utf8'), - ) - const sample = JSON.parse( - fs.readFileSync( - path.resolve('./test/sample_data/SKELETON/SKELETON-hdf.json'), - 'utf8', - ), - ) - expect(omitHDFChangingFields(converted)).to.eql( - omitHDFChangingFields(sample), - ) - }) -}) - -describe('Test SKELETON withraw flag', () => { - const tmpobj = tmp.dirSync({unsafeCleanup: true}) - - test - .stdout() - .command([ - 'convert SKELETON2hdf', - '-i', - path.resolve( - './test/sample_data/SKELETON/sample_input_report/SKELETON_sample.json', - ), - '-o', - `${tmpobj.name}/SKELETONtest.json`, - '-w', - ]) - .it('hdf-converter withraw output test', () => { - const converted = JSON.parse( - fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, 'utf8'), - ) - const sample = JSON.parse( - fs.readFileSync( - path.resolve('./test/sample_data/SKELETON/SKELETON-hdf-withraw.json'), - 'utf8', - ), - ) - expect(omitHDFChangingFields(converted)).to.eql( - omitHDFChangingFields(sample), - ) - }) -}) -``` -::: - -::: details XML Skeleton Convert Command Test File -```typescript -import {expect, test} from '@oclif/test' -import tmp from 'tmp' -import path from 'path' -import fs from 'fs' -import {omitHDFChangingFields} from '../utils' - -describe('Test SKELETON', () => { - const tmpobj = tmp.dirSync({unsafeCleanup: true}) - - test - .stdout() - .command([ - 'convert SKELETON2hdf', - '-i', - path.resolve( - './test/sample_data/SKELETON/sample_input_report/SKELETON_sample.xml', - ), - '-o', - `${tmpobj.name}/SKELETONtest.json`, - ]) - .it('hdf-converter output test', () => { - const converted = JSON.parse( - fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, 'utf8'), - ) - const sample = JSON.parse( - fs.readFileSync( - path.resolve('./test/sample_data/SKELETON/SKELETON-hdf.json'), - 'utf8', - ), - ) - expect(omitHDFChangingFields(converted)).to.eql( - omitHDFChangingFields(sample), - ) - }) -}) - -describe('Test SKELETON withraw flag', () => { - const tmpobj = tmp.dirSync({unsafeCleanup: true}) - - test - .stdout() - .command([ - 'convert SKELETON2hdf', - '-i', - path.resolve( - './test/sample_data/SKELETON/sample_input_report/SKELETON_sample.xml', - ), - '-o', - `${tmpobj.name}/SKELETONtest.json`, - '-w', - ]) - .it('hdf-converter withraw output test', () => { - const converted = JSON.parse( - fs.readFileSync(`${tmpobj.name}/SKELETONtest.json`, 'utf8'), - ) - const sample = JSON.parse( - fs.readFileSync( - path.resolve('./test/sample_data/SKELETON/SKELETON-hdf-withraw.json'), - 'utf8', - ), - ) - expect(omitHDFChangingFields(converted)).to.eql( - omitHDFChangingFields(sample), - ) - }) -}) -``` -::: - -3. Navigate to the `index.ts` file under the `src/commands/convert` directory. Import your mapper using the existing import block as follows: -```typescript -import { - ASFFResults, - ... - {YOUR-MAPPER-CLASS-HERE} -} from '@mitre/hdf-converters' -``` - -4. Under the switch block in the `getFlagsForInputFile` function, add your mapper class as it is defined for fingerprinting for the generic convert command. If the convert command for your mapper has any additional flags beyond the standard `--input` and `--output` flags, return the entire flag block in the switch case. This is demonstrated as follows: -```typescript -switch (Convert.detectedType) { - ... - case {YOUR-EXPORT-SERVICE-NAME-HERE}: - return {YOUR-CLI-CONVERT-CLASS}.flags //Only add if special flags exist - ... - return {} -} -``` - -5. Edit the `README.md` file to reflect your newly added conversion command under the `Convert To HDF` section. It should be formatted as follows: - -```markdown -##### {YOUR-EXPORT-NAME-HERE} to HDF - -\``` -convert {YOUR-EXPORT-NAME-HERE}2hdf Translate a {YOUR-EXPORT-NAME-HERE} results {EXPORT-TYPE} into an HDF results set - - USAGE - $ saf convert {YOUR-EXPORT-NAME-HERE}hdf -i <{INPUT-NAME}> -o - - OPTIONS - -i, --input=input Input {EXPORT-TYPE} File - -o, --output=output Output HDF JSON File - -w, --with-raw Include raw input file in HDF JSON file - - EXAMPLES - $ saf convert {YOUR-EXPORT-NAME-HERE}2hdf -i {INPUT-NAME} -o output-hdf-name.json -\``` -``` - -5. Commit your changes and mark your pull request as 'ready for review'. You should request for a code review from members of the SAF team and edit your code as necessary. Once approved, merged, and [released](https://github.com/mitre/saf/wiki/Creating-a-Release-of-the-SAF-CLI), your mapper will be callable using the SAF CLI. From 8945984b8916b78d71e42de7cb4c198a058ab960 Mon Sep 17 00:00:00 2001 From: Charles Hu Date: Fri, 23 Aug 2024 14:16:36 -0400 Subject: [PATCH 69/71] Env set up rework Signed-off-by: Charles Hu --- src/courses/mappers/10.md | 72 ++- src/courses/mappers/12.md | 809 ------------------------ src/courses/mappers/nonguided-labs.txt | 810 +++++++++++++++++++++++++ 3 files changed, 874 insertions(+), 817 deletions(-) create mode 100644 src/courses/mappers/nonguided-labs.txt diff --git a/src/courses/mappers/10.md b/src/courses/mappers/10.md index a49a2354c..6a75252b0 100644 --- a/src/courses/mappers/10.md +++ b/src/courses/mappers/10.md @@ -9,11 +9,31 @@ author: Charles Hu In this section, we will cover: -## Environment Set Up +- How to set up an environment for OHDF mapper development via: + - [GitHub Codespaces](#github-codespaces-environment-set-up) + - [Local installation](#local-environment-set-up) -Node.js (a runtime environment for JavaScript) and Yarn (a package manager for JavaScript/TypeScript) are external utilities which are utilized extensively within this guide. The following section details their installation process. +## Overview -Linux/Mac OS: +The rest of this course will involve a mix of hands-on guided and unguided labs to teach you the basics of the technical implementation of OHDF mappers. To facilitate this, we provide two installation guides for setting up the environment necessary for these upcoming labs: A GitHub Codespaces environment set up (recommended for beginners) and a local environment set up (recommended for experienced developers or individuals interested in manually installing to their local system). + +## GitHub Codespaces Environment Set Up + +We provide a [GitHub Codespaces environment](https://github.com/mitre/saf-training-lab-environment) that includes a simple build script that installs the necessary repositories and packages to begin OHDF mapper development. + +Follow the instructions listed in the README and you should have a verified working environment with the Heimdall and SAF CLI repositories pulled down into the `/dev_repos/` directory. Heimdall can be found under `/dev_repos/heimdall2/`, the SAF CLI can be found under `/dev_repos/saf/`, and OHDF Converters can be found under `/dev_repos/heimdall2/libs/hdf-converters/`. + +## Local Environment Set Up + +To set up the environment locally, we will need to pull down the GitHub repositories for Heimdall and the SAF CLI using Git and install their necessary dependencies using a package manager. + +You can install Git [here](https://git-scm.com/downloads). Choose your OS and follow the installation guide as necessary. + +Node.js (a runtime environment for JavaScript), NPM (a package manager for JavaScript/TypeScript), and Yarn (another package manager for JavaScript/TypeScript) are external utilities which are utilized extensively within this guide. The following section details their installation process. + +### Runtime & Package Managers + +#### Linux/Mac OS 1. Install [nvm](https://github.com/nvm-sh/nvm#install--update-script). @@ -41,22 +61,58 @@ nvm install 18 3. Install [Yarn](https://yarnpkg.com/getting-started/install) -Windows: +#### Windows 1. Install [Node.js v18 via the installer](https://nodejs.org/en/download/). 2. Install [Yarn](https://yarnpkg.com/getting-started/install): -## Repository Set Up +### Repository Set Up + +Now that we have the runtime and package managers for Javascript installed, we can pull down the necessary GitHub repositories and install their dependencies. 1. Fork/branch a development repository from the main [Heimdall2 GitHub repository](https://github.com/mitre/heimdall2). - SAF team developers have write access to the main repository and should [create a branch](https://docs.github.com/en/desktop/contributing-and-collaborating-using-github-desktop/making-changes-in-a-branch/managing-branches#creating-a-branch) on the primary development repository. Non-SAF team developers should instead [create a fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo#forking-a-repository) of the main repository and create a development branch there. -2. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. +2. Pull down your development branch from GitHub using the following command: + +```shell +git clone {URL-TO-REPO-HERE} +``` + +3. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. + +4. Install the necessary dependencies for Heimdall2. Under the `heimdall2` directory, enter the following command in the terminal: + +```shell +yarn install --frozen-lockfile +``` + +5. Fork/branch a development repository from the main [SAF CLI GitHub repository](https://github.com/mitre/saf). + + - SAF team developers have write access to the main repository and should [create a branch](https://docs.github.com/en/desktop/contributing-and-collaborating-using-github-desktop/making-changes-in-a-branch/managing-branches#creating-a-branch) on the primary development repository. Non-SAF team developers should instead [create a fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo#forking-a-repository) of the main repository and create a development branch there. + +6. Pull down your development branch from GitHub using the following command: -3. Install the necessary dependencies for Heimdall2. Under the `heimdall2` directory, enter the following command in the terminal: +```shell +git clone {URL-TO-REPO-HERE} +``` + +7. Create a draft [pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#creating-the-pull-request) for your development branch against the main repository branch. + +8. Install the necessary dependencies for the SAF CLI. Under the `saf` directory, enter the following command in the terminal: ```shell -yarn install +npm install ``` + +You should now have a working environment with the Heimdall and SAF CLI repositories. Heimdall can be found under `/heimdall2/`, the SAF CLI can be found under `/saf/`, and OHDF Converters can be found under `/heimdall2/libs/hdf-converters/`. + +## A Look Back + +In this section, we covered: + +- How to set up an environment for OHDF mapper development via: + - [GitHub Codespaces](#github-codespaces-environment-set-up) + - [Local installation](#local-environment-set-up) diff --git a/src/courses/mappers/12.md b/src/courses/mappers/12.md index d8ef8cc5d..4a4a8af65 100644 --- a/src/courses/mappers/12.md +++ b/src/courses/mappers/12.md @@ -1755,812 +1755,3 @@ export class DBProtectMapper extends BaseConverter { ::: Now we have a fully implemented DbProtect-to-OHDF mapper. - -### Mapper Demo - JFrog - -This section is yet another example of implementing an OHDF mapper, namely the JFrog-Xray mapper. Again, we will assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. Because we have already gone through several examples, this section will not explain too many things in detail. The goal is to simply provide more examples for reference. - -Here is our developed mapping for JFrog-Xray for reference: - -::: details JFrog-to-OHDF Mapping - -```typescript -{ - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion, - target_id - }, - version: HeimdallToolsVersion, - statistics: { - duration - }, - profiles: [ - { - name, - version, - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: 'data.id', // If ID empty, hash the summary - title: 'data.summary', - desc: 'component_versions.more_details', - descriptions, - impact: 'data.severity', - refs, - tags: { - nist: 'data.component_versions.more_details.cves[0].cwe', // Map to NIST - cci: 'data.component_versions.more_details.cves[0].cwe', // Map to CCI - cweid: 'data.component_versions.more_details.cves[0].cwe' - }, - code, - source_location, - results: [ - { - status: 'Failed', // All reported findings are failures - code_desc: ['data.source_comp_id', 'data.component_versions.vulnerable_versions', 'data.component_versions.fixed_versions', 'data.issue_type', 'data.provider'], - message, - run_time, - start_time - } - ] - }, - ], - status: 'loaded' - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` - -::: - -::: details JFrog Source Data - -```json -{ - "total_count": 30, - "data": [ - { - "id": "", - "severity": "High", - "summary": "Acorn regexp.js Regular Expression Validation UTF-16 Surrogate Handling Infinite Loop DoS", - "issue_type": "security", - "provider": "JFrog", - "component": "acorn", - "source_id": "npm://acorn", - "source_comp_id": "npm://acorn:5.7.3", - "component_versions": { - "id": "acorn", - "vulnerable_versions": [ - "5.5.0 ≤ Version < 5.7.4", - "6.0.0 ≤ Version < 6.4.1", - "7.0.0", - "7.1.0" - ], - "fixed_versions": ["5.7.4", "6.4.1", "7.1.1"], - "more_details": { - "cves": [ - { - "cvss_v2": "7.1/AV:N/AC:M/Au:N/C:N/I:N/A:C", - "cvss_v3": "7.5/CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H" - } - ], - "description": "Acorn contains an infinite loop condition in regexp.js that is triggered when handling UTF_16 surrogates while validating regular expressions. This may allow a context-dependent attacker to hang a process using the library.", - "provider": "JFrog" - } - }, - "edited": "2020-11-03T19:30:42-05:00" - } - ] -} -``` - -::: - -We will now go over the mapper code that allows us to shape this data properly. Firstly, let us handle the ID. Sometimes, JFrog source files will not have an ID field. In this case, it is appropriate to generate a hash based on the `summary` as follows: - -```typescript -function hashId(vulnerability: unknown): string { - if (_.get(vulnerability, "id") === "") { - return generateHash( - (_.get(vulnerability, "summary") as unknown as string).toString(), - "md5" - ); - } else { - return _.get(vulnerability, "id") as unknown as string; - } -} -``` - -As with most mappers, we must also define an impact mapping: - -```typescript -const IMPACT_MAPPING: Map = new Map([ - ["high", 0.7], - ["medium", 0.5], - ["low", 0.3], -]); -``` - -Recall that we wanted to format the `desc` field based on the data in the source file's `component_versions.more_details`. We can write a simple transformer function to concatenate all these keys: - -```typescript -function formatDesc(vulnerability: unknown): string { - const text = []; - if (_.has(vulnerability, "description")) { - text.push( - (_.get(vulnerability, "description") as unknown as string).toString() - ); - } - if (_.has(vulnerability, "cves")) { - const re1 = /":/gi; - const re2 = /,/gi; - text.push( - `cves: ${JSON.stringify(_.get(vulnerability, "cves")) - .replace(re1, '"=>') - .replace(re2, ", ")}` - ); - } - return text.join("
"); -} -``` - -We also must properly handle the mappings to NIST and CCI tags. Luckily, we can make use of the library's existing mappings, as well as an existing global function called `getCCIsForNISTTags()` in `global.ts`. - -```typescript -const CWE_PATH = "component_versions.more_details.cves[0].cwe"; -const CWE_NIST_MAPPING = new CweNistMapping(); - -function nistTag(identifier: Record): string[] { - const identifiers: string[] = []; - if (Array.isArray(identifier)) { - identifier.forEach((element) => { - if (element.split("CWE-")[1]) { - identifiers.push(element.split("CWE-")[1]); - } - }); - } - return CWE_NIST_MAPPING.nistFilter( - identifiers, - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS - ); -} -``` - -Finally, we can implement the transformer function for the `code_desc`. Some of these fields are optional, so it is important to implement a base case to ensure our `code_desc` outputs are all consistent. - -```typescript -function formatCodeDesc(vulnerability: unknown): string { - const codeDescArray: string[] = []; - const re = /,/gi; - if (_.has(vulnerability, "source_comp_id")) { - codeDescArray.push( - `source_comp_id : ${_.get(vulnerability, "source_comp_id")}` - ); - } else { - codeDescArray.push("source_comp_id : "); - } - if (_.has(vulnerability, "component_versions.vulnerable_versions")) { - codeDescArray.push( - `vulnerable_versions : ${JSON.stringify( - _.get(vulnerability, "component_versions.vulnerable_versions") - )}` - ); - } else { - codeDescArray.push("vulnerable_versions : "); - } - if (_.has(vulnerability, "component_versions.fixed_versions")) { - codeDescArray.push( - `fixed_versions : ${JSON.stringify( - _.get(vulnerability, "component_versions.fixed_versions") - )}` - ); - } else { - codeDescArray.push("fixed_versions : "); - } - if (_.has(vulnerability, "issue_type")) { - codeDescArray.push(`issue_type : ${_.get(vulnerability, "issue_type")}`); - } else { - codeDescArray.push("issue_type : "); - } - if (_.has(vulnerability, "provider")) { - codeDescArray.push(`provider : ${_.get(vulnerability, "provider")}`); - } else { - codeDescArray.push("provider : "); - } - return codeDescArray.join("\n").replace(re, ", "); -} -``` - -All that's left is to incoporate all these functions into our `base-converter` structure, write some smaller transformer functions for the simpler data formatting tasks, and combine it all together! - -:::details Full Mapper Code - -```typescript -import { ExecJSON } from "inspecjs"; -import * as _ from "lodash"; -import { version as HeimdallToolsVersion } from "../package.json"; -import { - BaseConverter, - generateHash, - ILookupPath, - impactMapping, - MappedTransform, -} from "./base-converter"; -import { CweNistMapping } from "./mappings/CweNistMapping"; -import { - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, - getCCIsForNISTTags, -} from "./utils/global"; - -// Constants -const IMPACT_MAPPING: Map = new Map([ - ["high", 0.7], - ["medium", 0.5], - ["low", 0.3], -]); - -const CWE_PATH = "component_versions.more_details.cves[0].cwe"; - -const CWE_NIST_MAPPING = new CweNistMapping(); - -// Transformation Functions -function hashId(vulnerability: unknown): string { - if (_.get(vulnerability, "id") === "") { - return generateHash( - (_.get(vulnerability, "summary") as unknown as string).toString(), - "md5" - ); - } else { - return _.get(vulnerability, "id") as unknown as string; - } -} -function formatDesc(vulnerability: unknown): string { - const text = []; - if (_.has(vulnerability, "description")) { - text.push( - (_.get(vulnerability, "description") as unknown as string).toString() - ); - } - if (_.has(vulnerability, "cves")) { - const re1 = /":/gi; - const re2 = /,/gi; - text.push( - `cves: ${JSON.stringify(_.get(vulnerability, "cves")) - .replace(re1, '"=>') - .replace(re2, ", ")}` - ); - } - return text.join("
"); -} -function formatCodeDesc(vulnerability: unknown): string { - const codeDescArray: string[] = []; - const re = /,/gi; - if (_.has(vulnerability, "source_comp_id")) { - codeDescArray.push( - `source_comp_id : ${_.get(vulnerability, "source_comp_id")}` - ); - } else { - codeDescArray.push("source_comp_id : "); - } - if (_.has(vulnerability, "component_versions.vulnerable_versions")) { - codeDescArray.push( - `vulnerable_versions : ${JSON.stringify( - _.get(vulnerability, "component_versions.vulnerable_versions") - )}` - ); - } else { - codeDescArray.push("vulnerable_versions : "); - } - if (_.has(vulnerability, "component_versions.fixed_versions")) { - codeDescArray.push( - `fixed_versions : ${JSON.stringify( - _.get(vulnerability, "component_versions.fixed_versions") - )}` - ); - } else { - codeDescArray.push("fixed_versions : "); - } - if (_.has(vulnerability, "issue_type")) { - codeDescArray.push(`issue_type : ${_.get(vulnerability, "issue_type")}`); - } else { - codeDescArray.push("issue_type : "); - } - if (_.has(vulnerability, "provider")) { - codeDescArray.push(`provider : ${_.get(vulnerability, "provider")}`); - } else { - codeDescArray.push("provider : "); - } - return codeDescArray.join("\n").replace(re, ", "); -} -function nistTag(identifier: Record): string[] { - const identifiers: string[] = []; - if (Array.isArray(identifier)) { - identifier.forEach((element) => { - if (element.split("CWE-")[1]) { - identifiers.push(element.split("CWE-")[1]); - } - }); - } - return CWE_NIST_MAPPING.nistFilter( - identifiers, - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS - ); -} - -// Mappings -export class JfrogXrayMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & { passthrough: unknown }, - ILookupPath - > = { - platform: { - name: "Heimdall Tools", - release: HeimdallToolsVersion, - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - name: "JFrog Xray Scan", - title: "JFrog Xray Scan", - summary: "Continuous Security and Universal Artifact Analysis", - supports: [], - attributes: [], - groups: [], - status: "loaded", - controls: [ - { - path: "data", - key: "id", - tags: { - cci: { - path: CWE_PATH, - transformer: (identifier: Record) => - getCCIsForNISTTags(nistTag(identifier)), - }, - nist: { - path: CWE_PATH, - transformer: nistTag, - }, - cweid: { path: CWE_PATH }, - }, - refs: [], - source_location: {}, - id: { transformer: hashId }, - title: { path: "summary" }, - desc: { - path: "component_versions.more_details", - transformer: formatDesc, - }, - impact: { - path: "severity", - transformer: impactMapping(IMPACT_MAPPING), - }, - code: { - transformer: (vulnerability: Record): string => { - return JSON.stringify(vulnerability, null, 2); - }, - }, - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, - code_desc: { transformer: formatCodeDesc }, - start_time: "", - }, - ], - }, - ], - sha256: "", - }, - ], - passthrough: { - transformer: (data: Record): Record => { - return { - auxiliary_data: [ - { - name: "JFrog Xray", - data: _.pick(data, ["total_count"]), - }, - ], - ...(this.withRaw && { raw: data }), - }; - }, - }, - }; - constructor(xrayJson: string, withRaw = false) { - super(JSON.parse(xrayJson), true); - this.withRaw = withRaw; - } -} -``` - -::: - -Now we have a fully implemented JFrog-to-OHDF mapper. - -### Mapper Demo - SARIF - -Here is one last example of implementing an OHDF mapper - the SARIF mapper. As in previous examples, we will assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. Like with the JFrog example, we will not be going into too much detail regarding the mapping itself. The goal is to simply provide more examples for reference. - -Here is our developed mapping for SARIF for reference: - -::: details SARIF-to-OHDF Mapping - -```typescript -{ - platform: { - name: 'Heimdall Tools', - release: HeimdallToolsVersion, - target_id - }, - version: HeimdallToolsVersion, - statistics: { - duration - }, - profiles: [ - { - name, - version: 'version', - sha256, - title, - maintainer, - summary, - license, - copyright, - copyright_email, - supports, - attributes, - groups, - controls: [ - { - id: 'results.ruleId', // If ID empty, hash the summary - title: 'results.message.text', - desc: 'results.message.text', - descriptions, - impact: 'results.level', - refs, - tags: { - nist: 'results.message.text', // Map to NIST - cci: 'results.message.text', // Map to CCI - cwe: 'results.message.text' - }, - code, - source_location: ['results.locations[0].physicalLocation.artifactLocation.uri', 'results.locations[0].physicalLocation.region.startLine'], - results: [ - { - status: 'Failed', // All reported findings are failures - code_desc: 'results.locations[0].physicalLocation', - message, - run_time, - start_time - } - ] - }, - ], - status: 'loaded' - }, - ], - passthrough: { - auxiliary_data: [ - { - name, - data - }, - ], - raw - } -} -``` - -::: - -::: details SARIF Source Data - -```json -{ - "$schema": "https://schemastore.azurewebsites.net/schemas/json/sarif-2.1.0-rtm.5.json", - "version": "2.1.0", - "runs": [ - { - "results": [ - { - "ruleId": "FF1014", - "level": "error", - "message": { - "text": "buffer/gets: Does not check for buffer overflows (CWE-120, CWE-20)." - }, - "locations": [ - { - "physicalLocation": { - "artifactLocation": { - "uri": "test/test-patched.c", - "uriBaseId": "SRCROOT" - }, - "region": { - "startLine": 36, - "startColumn": 2, - "endColumn": 10, - "snippet": { - "text": " gets(f);" - } - } - } - } - ], - "fingerprints": { - "contextHash/v1": "6a5bb383fb44030b0d9428b17359e94ba3979bc1ce702be450427f85592c649a" - }, - "rank": 1 - } - ] - } - ] -} -``` - -::: - -First, let us define some common constants that might help us with our code. - -```typescript -const MESSAGE_TEXT = "message.text"; -const CWE_NIST_MAPPING = new CweNistMapping(); -``` - -We will now outline the `IMPACT_MAPPING` for the SARIF mapper: - -```typescript -const IMPACT_MAPPING: Map = new Map([ - ["error", 0.7], - ["warning", 0.5], - ["note", 0.3], -]); - -function impactMapping(severity: unknown): number { - if (typeof severity === "string" || typeof severity === "number") { - return IMPACT_MAPPING.get(severity.toString().toLowerCase()) || 0.1; - } else { - return 0.1; - } -} -``` - -Now, note that we will need to extract the CWEs from the message text, as well as map them to the proper NIST tags. For the CCIs, we can again use the global function `getCCIsForNISTTags()`. - -```typescript -function extractCwe(text: string): string[] { - let output = text.split("(").slice(-1)[0].slice(0, -2).split(", "); - if (output.length === 1) { - output = text.split("(").slice(-1)[0].slice(0, -2).split("!/"); - } - return output; -} -function nistTag(text: string): string[] { - let identifiers = extractCwe(text); - identifiers = identifiers.map((element) => element.split("-")[1]); - return CWE_NIST_MAPPING.nistFilter( - identifiers, - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS - ); -} -``` - -Our last standalone transformer function will format our code description. This part is up to interpretation, but we decided to just concatenate them all with colon-separated key-value pairs - -```typescript -function formatCodeDesc(input: unknown): string { - const output = []; - output.push(`URL : ${_.get(input, "artifactLocation.uri")}`); - output.push(`LINE : ${_.get(input, "region.startLine")}`); - output.push(`COLUMN : ${_.get(input, "region.startColumn")}`); - return output.join(" "); -} -``` - -Now, all that's left is to combine our functions, write some mini-transformers for the small data formatting, and plug it all into the base converter! - -:::details Full Mapper Code - -```typescript -import { ExecJSON } from "inspecjs"; -import * as _ from "lodash"; -import { version as HeimdallToolsVersion } from "../package.json"; -import { BaseConverter, ILookupPath, MappedTransform } from "./base-converter"; -import { CweNistMapping } from "./mappings/CweNistMapping"; -import { - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, - getCCIsForNISTTags, -} from "./utils/global"; - -const IMPACT_MAPPING: Map = new Map([ - ["error", 0.7], - ["warning", 0.5], - ["note", 0.3], -]); -const MESSAGE_TEXT = "message.text"; -const CWE_NIST_MAPPING = new CweNistMapping(); - -function extractCwe(text: string): string[] { - let output = text.split("(").slice(-1)[0].slice(0, -2).split(", "); - if (output.length === 1) { - output = text.split("(").slice(-1)[0].slice(0, -2).split("!/"); - } - return output; -} -function impactMapping(severity: unknown): number { - if (typeof severity === "string" || typeof severity === "number") { - return IMPACT_MAPPING.get(severity.toString().toLowerCase()) || 0.1; - } else { - return 0.1; - } -} -function formatCodeDesc(input: unknown): string { - const output = []; - output.push(`URL : ${_.get(input, "artifactLocation.uri")}`); - output.push(`LINE : ${_.get(input, "region.startLine")}`); - output.push(`COLUMN : ${_.get(input, "region.startColumn")}`); - return output.join(" "); -} -function nistTag(text: string): string[] { - let identifiers = extractCwe(text); - identifiers = identifiers.map((element) => element.split("-")[1]); - return CWE_NIST_MAPPING.nistFilter( - identifiers, - DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS - ); -} - -export class SarifMapper extends BaseConverter { - withRaw: boolean; - - mappings: MappedTransform< - ExecJSON.Execution & { passthrough: unknown }, - ILookupPath - > = { - platform: { - name: "Heimdall Tools", - release: HeimdallToolsVersion, - target_id: "Static Analysis Results Interchange Format", - }, - version: HeimdallToolsVersion, - statistics: {}, - profiles: [ - { - path: "runs", - name: "SARIF", - version: { path: "$.version" }, - title: "Static Analysis Results Interchange Format", - supports: [], - attributes: [], - groups: [], - status: "loaded", - controls: [ - { - path: "results", - key: "id", - tags: { - cci: { - path: MESSAGE_TEXT, - transformer: (data: string) => - getCCIsForNISTTags(nistTag(data)), - }, - nist: { path: MESSAGE_TEXT, transformer: nistTag }, - cwe: { - path: MESSAGE_TEXT, - transformer: extractCwe, - }, - }, - refs: [], - source_location: { - transformer: (control: unknown) => { - return _.omitBy( - { - ref: _.get( - control, - "locations[0].physicalLocation.artifactLocation.uri" - ), - line: _.get( - control, - "locations[0].physicalLocation.region.startLine" - ), - }, - (value) => value === "" - ); - }, - }, - title: { - path: MESSAGE_TEXT, - transformer: (text: unknown): string => { - if (typeof text === "string") { - return text.split(": ")[0]; - } else { - return ""; - } - }, - }, - id: { path: "ruleId" }, - desc: { - path: MESSAGE_TEXT, - transformer: (text: unknown): string => { - if (typeof text === "string") { - return text.split(": ")[1]; - } else { - return ""; - } - }, - }, - impact: { path: "level", transformer: impactMapping }, - code: { - transformer: (vulnerability: Record): string => - JSON.stringify(vulnerability, null, 2), - }, - results: [ - { - status: ExecJSON.ControlResultStatus.Failed, - code_desc: { - path: "locations[0].physicalLocation", - transformer: formatCodeDesc, - }, - - start_time: "", - }, - ], - }, - ], - sha256: "", - }, - ], - passthrough: { - transformer: (data: Record): Record => { - let runsData = _.get(data, "runs"); - if (Array.isArray(runsData)) { - runsData = runsData.map((run: Record) => - _.omit(run, ["results"]) - ); - } - return { - auxiliary_data: [ - { - name: "SARIF", - data: { - $schema: _.get(data, "$schema"), - runs: runsData, - }, - }, - ], - ...(this.withRaw && { raw: data }), - }; - }, - }, - }; - constructor(sarifJson: string, withRaw = false) { - super(JSON.parse(sarifJson)); - this.withRaw = withRaw; - } -} -``` - -::: - -Now we have a fully implemented SARIF-to-OHDF mapper. diff --git a/src/courses/mappers/nonguided-labs.txt b/src/courses/mappers/nonguided-labs.txt new file mode 100644 index 000000000..b840ff1bb --- /dev/null +++ b/src/courses/mappers/nonguided-labs.txt @@ -0,0 +1,810 @@ +TEMP STORAGE FOR NONGUIDED LABS TO BE ADDED LATER + +### Mapper Demo - JFrog + +This section is yet another example of implementing an OHDF mapper, namely the JFrog-Xray mapper. Again, we will assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. Because we have already gone through several examples, this section will not explain too many things in detail. The goal is to simply provide more examples for reference. + +Here is our developed mapping for JFrog-Xray for reference: + +::: details JFrog-to-OHDF Mapping + +```typescript +{ + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id + }, + version: HeimdallToolsVersion, + statistics: { + duration + }, + profiles: [ + { + name, + version, + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'data.id', // If ID empty, hash the summary + title: 'data.summary', + desc: 'component_versions.more_details', + descriptions, + impact: 'data.severity', + refs, + tags: { + nist: 'data.component_versions.more_details.cves[0].cwe', // Map to NIST + cci: 'data.component_versions.more_details.cves[0].cwe', // Map to CCI + cweid: 'data.component_versions.more_details.cves[0].cwe' + }, + code, + source_location, + results: [ + { + status: 'Failed', // All reported findings are failures + code_desc: ['data.source_comp_id', 'data.component_versions.vulnerable_versions', 'data.component_versions.fixed_versions', 'data.issue_type', 'data.provider'], + message, + run_time, + start_time + } + ] + }, + ], + status: 'loaded' + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details JFrog Source Data + +```json +{ + "total_count": 30, + "data": [ + { + "id": "", + "severity": "High", + "summary": "Acorn regexp.js Regular Expression Validation UTF-16 Surrogate Handling Infinite Loop DoS", + "issue_type": "security", + "provider": "JFrog", + "component": "acorn", + "source_id": "npm://acorn", + "source_comp_id": "npm://acorn:5.7.3", + "component_versions": { + "id": "acorn", + "vulnerable_versions": [ + "5.5.0 ≤ Version < 5.7.4", + "6.0.0 ≤ Version < 6.4.1", + "7.0.0", + "7.1.0" + ], + "fixed_versions": ["5.7.4", "6.4.1", "7.1.1"], + "more_details": { + "cves": [ + { + "cvss_v2": "7.1/AV:N/AC:M/Au:N/C:N/I:N/A:C", + "cvss_v3": "7.5/CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H" + } + ], + "description": "Acorn contains an infinite loop condition in regexp.js that is triggered when handling UTF_16 surrogates while validating regular expressions. This may allow a context-dependent attacker to hang a process using the library.", + "provider": "JFrog" + } + }, + "edited": "2020-11-03T19:30:42-05:00" + } + ] +} +``` + +::: + +We will now go over the mapper code that allows us to shape this data properly. Firstly, let us handle the ID. Sometimes, JFrog source files will not have an ID field. In this case, it is appropriate to generate a hash based on the `summary` as follows: + +```typescript +function hashId(vulnerability: unknown): string { + if (_.get(vulnerability, "id") === "") { + return generateHash( + (_.get(vulnerability, "summary") as unknown as string).toString(), + "md5" + ); + } else { + return _.get(vulnerability, "id") as unknown as string; + } +} +``` + +As with most mappers, we must also define an impact mapping: + +```typescript +const IMPACT_MAPPING: Map = new Map([ + ["high", 0.7], + ["medium", 0.5], + ["low", 0.3], +]); +``` + +Recall that we wanted to format the `desc` field based on the data in the source file's `component_versions.more_details`. We can write a simple transformer function to concatenate all these keys: + +```typescript +function formatDesc(vulnerability: unknown): string { + const text = []; + if (_.has(vulnerability, "description")) { + text.push( + (_.get(vulnerability, "description") as unknown as string).toString() + ); + } + if (_.has(vulnerability, "cves")) { + const re1 = /":/gi; + const re2 = /,/gi; + text.push( + `cves: ${JSON.stringify(_.get(vulnerability, "cves")) + .replace(re1, '"=>') + .replace(re2, ", ")}` + ); + } + return text.join("
"); +} +``` + +We also must properly handle the mappings to NIST and CCI tags. Luckily, we can make use of the library's existing mappings, as well as an existing global function called `getCCIsForNISTTags()` in `global.ts`. + +```typescript +const CWE_PATH = "component_versions.more_details.cves[0].cwe"; +const CWE_NIST_MAPPING = new CweNistMapping(); + +function nistTag(identifier: Record): string[] { + const identifiers: string[] = []; + if (Array.isArray(identifier)) { + identifier.forEach((element) => { + if (element.split("CWE-")[1]) { + identifiers.push(element.split("CWE-")[1]); + } + }); + } + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} +``` + +Finally, we can implement the transformer function for the `code_desc`. Some of these fields are optional, so it is important to implement a base case to ensure our `code_desc` outputs are all consistent. + +```typescript +function formatCodeDesc(vulnerability: unknown): string { + const codeDescArray: string[] = []; + const re = /,/gi; + if (_.has(vulnerability, "source_comp_id")) { + codeDescArray.push( + `source_comp_id : ${_.get(vulnerability, "source_comp_id")}` + ); + } else { + codeDescArray.push("source_comp_id : "); + } + if (_.has(vulnerability, "component_versions.vulnerable_versions")) { + codeDescArray.push( + `vulnerable_versions : ${JSON.stringify( + _.get(vulnerability, "component_versions.vulnerable_versions") + )}` + ); + } else { + codeDescArray.push("vulnerable_versions : "); + } + if (_.has(vulnerability, "component_versions.fixed_versions")) { + codeDescArray.push( + `fixed_versions : ${JSON.stringify( + _.get(vulnerability, "component_versions.fixed_versions") + )}` + ); + } else { + codeDescArray.push("fixed_versions : "); + } + if (_.has(vulnerability, "issue_type")) { + codeDescArray.push(`issue_type : ${_.get(vulnerability, "issue_type")}`); + } else { + codeDescArray.push("issue_type : "); + } + if (_.has(vulnerability, "provider")) { + codeDescArray.push(`provider : ${_.get(vulnerability, "provider")}`); + } else { + codeDescArray.push("provider : "); + } + return codeDescArray.join("\n").replace(re, ", "); +} +``` + +All that's left is to incoporate all these functions into our `base-converter` structure, write some smaller transformer functions for the simpler data formatting tasks, and combine it all together! + +:::details Full Mapper Code + +```typescript +import { ExecJSON } from "inspecjs"; +import * as _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { + BaseConverter, + generateHash, + ILookupPath, + impactMapping, + MappedTransform, +} from "./base-converter"; +import { CweNistMapping } from "./mappings/CweNistMapping"; +import { + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + getCCIsForNISTTags, +} from "./utils/global"; + +// Constants +const IMPACT_MAPPING: Map = new Map([ + ["high", 0.7], + ["medium", 0.5], + ["low", 0.3], +]); + +const CWE_PATH = "component_versions.more_details.cves[0].cwe"; + +const CWE_NIST_MAPPING = new CweNistMapping(); + +// Transformation Functions +function hashId(vulnerability: unknown): string { + if (_.get(vulnerability, "id") === "") { + return generateHash( + (_.get(vulnerability, "summary") as unknown as string).toString(), + "md5" + ); + } else { + return _.get(vulnerability, "id") as unknown as string; + } +} +function formatDesc(vulnerability: unknown): string { + const text = []; + if (_.has(vulnerability, "description")) { + text.push( + (_.get(vulnerability, "description") as unknown as string).toString() + ); + } + if (_.has(vulnerability, "cves")) { + const re1 = /":/gi; + const re2 = /,/gi; + text.push( + `cves: ${JSON.stringify(_.get(vulnerability, "cves")) + .replace(re1, '"=>') + .replace(re2, ", ")}` + ); + } + return text.join("
"); +} +function formatCodeDesc(vulnerability: unknown): string { + const codeDescArray: string[] = []; + const re = /,/gi; + if (_.has(vulnerability, "source_comp_id")) { + codeDescArray.push( + `source_comp_id : ${_.get(vulnerability, "source_comp_id")}` + ); + } else { + codeDescArray.push("source_comp_id : "); + } + if (_.has(vulnerability, "component_versions.vulnerable_versions")) { + codeDescArray.push( + `vulnerable_versions : ${JSON.stringify( + _.get(vulnerability, "component_versions.vulnerable_versions") + )}` + ); + } else { + codeDescArray.push("vulnerable_versions : "); + } + if (_.has(vulnerability, "component_versions.fixed_versions")) { + codeDescArray.push( + `fixed_versions : ${JSON.stringify( + _.get(vulnerability, "component_versions.fixed_versions") + )}` + ); + } else { + codeDescArray.push("fixed_versions : "); + } + if (_.has(vulnerability, "issue_type")) { + codeDescArray.push(`issue_type : ${_.get(vulnerability, "issue_type")}`); + } else { + codeDescArray.push("issue_type : "); + } + if (_.has(vulnerability, "provider")) { + codeDescArray.push(`provider : ${_.get(vulnerability, "provider")}`); + } else { + codeDescArray.push("provider : "); + } + return codeDescArray.join("\n").replace(re, ", "); +} +function nistTag(identifier: Record): string[] { + const identifiers: string[] = []; + if (Array.isArray(identifier)) { + identifier.forEach((element) => { + if (element.split("CWE-")[1]) { + identifiers.push(element.split("CWE-")[1]); + } + }); + } + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} + +// Mappings +export class JfrogXrayMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + name: "JFrog Xray Scan", + title: "JFrog Xray Scan", + summary: "Continuous Security and Universal Artifact Analysis", + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + path: "data", + key: "id", + tags: { + cci: { + path: CWE_PATH, + transformer: (identifier: Record) => + getCCIsForNISTTags(nistTag(identifier)), + }, + nist: { + path: CWE_PATH, + transformer: nistTag, + }, + cweid: { path: CWE_PATH }, + }, + refs: [], + source_location: {}, + id: { transformer: hashId }, + title: { path: "summary" }, + desc: { + path: "component_versions.more_details", + transformer: formatDesc, + }, + impact: { + path: "severity", + transformer: impactMapping(IMPACT_MAPPING), + }, + code: { + transformer: (vulnerability: Record): string => { + return JSON.stringify(vulnerability, null, 2); + }, + }, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: { transformer: formatCodeDesc }, + start_time: "", + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + return { + auxiliary_data: [ + { + name: "JFrog Xray", + data: _.pick(data, ["total_count"]), + }, + ], + ...(this.withRaw && { raw: data }), + }; + }, + }, + }; + constructor(xrayJson: string, withRaw = false) { + super(JSON.parse(xrayJson), true); + this.withRaw = withRaw; + } +} +``` + +::: + +Now we have a fully implemented JFrog-to-OHDF mapper. + +### Mapper Demo - SARIF + +Here is one last example of implementing an OHDF mapper - the SARIF mapper. As in previous examples, we will assume that the [appropriate file set up for the mapper](#file-set-up) has been performed. Like with the JFrog example, we will not be going into too much detail regarding the mapping itself. The goal is to simply provide more examples for reference. + +Here is our developed mapping for SARIF for reference: + +::: details SARIF-to-OHDF Mapping + +```typescript +{ + platform: { + name: 'Heimdall Tools', + release: HeimdallToolsVersion, + target_id + }, + version: HeimdallToolsVersion, + statistics: { + duration + }, + profiles: [ + { + name, + version: 'version', + sha256, + title, + maintainer, + summary, + license, + copyright, + copyright_email, + supports, + attributes, + groups, + controls: [ + { + id: 'results.ruleId', // If ID empty, hash the summary + title: 'results.message.text', + desc: 'results.message.text', + descriptions, + impact: 'results.level', + refs, + tags: { + nist: 'results.message.text', // Map to NIST + cci: 'results.message.text', // Map to CCI + cwe: 'results.message.text' + }, + code, + source_location: ['results.locations[0].physicalLocation.artifactLocation.uri', 'results.locations[0].physicalLocation.region.startLine'], + results: [ + { + status: 'Failed', // All reported findings are failures + code_desc: 'results.locations[0].physicalLocation', + message, + run_time, + start_time + } + ] + }, + ], + status: 'loaded' + }, + ], + passthrough: { + auxiliary_data: [ + { + name, + data + }, + ], + raw + } +} +``` + +::: + +::: details SARIF Source Data + +```json +{ + "$schema": "https://schemastore.azurewebsites.net/schemas/json/sarif-2.1.0-rtm.5.json", + "version": "2.1.0", + "runs": [ + { + "results": [ + { + "ruleId": "FF1014", + "level": "error", + "message": { + "text": "buffer/gets: Does not check for buffer overflows (CWE-120, CWE-20)." + }, + "locations": [ + { + "physicalLocation": { + "artifactLocation": { + "uri": "test/test-patched.c", + "uriBaseId": "SRCROOT" + }, + "region": { + "startLine": 36, + "startColumn": 2, + "endColumn": 10, + "snippet": { + "text": " gets(f);" + } + } + } + } + ], + "fingerprints": { + "contextHash/v1": "6a5bb383fb44030b0d9428b17359e94ba3979bc1ce702be450427f85592c649a" + }, + "rank": 1 + } + ] + } + ] +} +``` + +::: + +First, let us define some common constants that might help us with our code. + +```typescript +const MESSAGE_TEXT = "message.text"; +const CWE_NIST_MAPPING = new CweNistMapping(); +``` + +We will now outline the `IMPACT_MAPPING` for the SARIF mapper: + +```typescript +const IMPACT_MAPPING: Map = new Map([ + ["error", 0.7], + ["warning", 0.5], + ["note", 0.3], +]); + +function impactMapping(severity: unknown): number { + if (typeof severity === "string" || typeof severity === "number") { + return IMPACT_MAPPING.get(severity.toString().toLowerCase()) || 0.1; + } else { + return 0.1; + } +} +``` + +Now, note that we will need to extract the CWEs from the message text, as well as map them to the proper NIST tags. For the CCIs, we can again use the global function `getCCIsForNISTTags()`. + +```typescript +function extractCwe(text: string): string[] { + let output = text.split("(").slice(-1)[0].slice(0, -2).split(", "); + if (output.length === 1) { + output = text.split("(").slice(-1)[0].slice(0, -2).split("!/"); + } + return output; +} +function nistTag(text: string): string[] { + let identifiers = extractCwe(text); + identifiers = identifiers.map((element) => element.split("-")[1]); + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} +``` + +Our last standalone transformer function will format our code description. This part is up to interpretation, but we decided to just concatenate them all with colon-separated key-value pairs + +```typescript +function formatCodeDesc(input: unknown): string { + const output = []; + output.push(`URL : ${_.get(input, "artifactLocation.uri")}`); + output.push(`LINE : ${_.get(input, "region.startLine")}`); + output.push(`COLUMN : ${_.get(input, "region.startColumn")}`); + return output.join(" "); +} +``` + +Now, all that's left is to combine our functions, write some mini-transformers for the small data formatting, and plug it all into the base converter! + +:::details Full Mapper Code + +```typescript +import { ExecJSON } from "inspecjs"; +import * as _ from "lodash"; +import { version as HeimdallToolsVersion } from "../package.json"; +import { BaseConverter, ILookupPath, MappedTransform } from "./base-converter"; +import { CweNistMapping } from "./mappings/CweNistMapping"; +import { + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS, + getCCIsForNISTTags, +} from "./utils/global"; + +const IMPACT_MAPPING: Map = new Map([ + ["error", 0.7], + ["warning", 0.5], + ["note", 0.3], +]); +const MESSAGE_TEXT = "message.text"; +const CWE_NIST_MAPPING = new CweNistMapping(); + +function extractCwe(text: string): string[] { + let output = text.split("(").slice(-1)[0].slice(0, -2).split(", "); + if (output.length === 1) { + output = text.split("(").slice(-1)[0].slice(0, -2).split("!/"); + } + return output; +} +function impactMapping(severity: unknown): number { + if (typeof severity === "string" || typeof severity === "number") { + return IMPACT_MAPPING.get(severity.toString().toLowerCase()) || 0.1; + } else { + return 0.1; + } +} +function formatCodeDesc(input: unknown): string { + const output = []; + output.push(`URL : ${_.get(input, "artifactLocation.uri")}`); + output.push(`LINE : ${_.get(input, "region.startLine")}`); + output.push(`COLUMN : ${_.get(input, "region.startColumn")}`); + return output.join(" "); +} +function nistTag(text: string): string[] { + let identifiers = extractCwe(text); + identifiers = identifiers.map((element) => element.split("-")[1]); + return CWE_NIST_MAPPING.nistFilter( + identifiers, + DEFAULT_STATIC_CODE_ANALYSIS_NIST_TAGS + ); +} + +export class SarifMapper extends BaseConverter { + withRaw: boolean; + + mappings: MappedTransform< + ExecJSON.Execution & { passthrough: unknown }, + ILookupPath + > = { + platform: { + name: "Heimdall Tools", + release: HeimdallToolsVersion, + target_id: "Static Analysis Results Interchange Format", + }, + version: HeimdallToolsVersion, + statistics: {}, + profiles: [ + { + path: "runs", + name: "SARIF", + version: { path: "$.version" }, + title: "Static Analysis Results Interchange Format", + supports: [], + attributes: [], + groups: [], + status: "loaded", + controls: [ + { + path: "results", + key: "id", + tags: { + cci: { + path: MESSAGE_TEXT, + transformer: (data: string) => + getCCIsForNISTTags(nistTag(data)), + }, + nist: { path: MESSAGE_TEXT, transformer: nistTag }, + cwe: { + path: MESSAGE_TEXT, + transformer: extractCwe, + }, + }, + refs: [], + source_location: { + transformer: (control: unknown) => { + return _.omitBy( + { + ref: _.get( + control, + "locations[0].physicalLocation.artifactLocation.uri" + ), + line: _.get( + control, + "locations[0].physicalLocation.region.startLine" + ), + }, + (value) => value === "" + ); + }, + }, + title: { + path: MESSAGE_TEXT, + transformer: (text: unknown): string => { + if (typeof text === "string") { + return text.split(": ")[0]; + } else { + return ""; + } + }, + }, + id: { path: "ruleId" }, + desc: { + path: MESSAGE_TEXT, + transformer: (text: unknown): string => { + if (typeof text === "string") { + return text.split(": ")[1]; + } else { + return ""; + } + }, + }, + impact: { path: "level", transformer: impactMapping }, + code: { + transformer: (vulnerability: Record): string => + JSON.stringify(vulnerability, null, 2), + }, + results: [ + { + status: ExecJSON.ControlResultStatus.Failed, + code_desc: { + path: "locations[0].physicalLocation", + transformer: formatCodeDesc, + }, + + start_time: "", + }, + ], + }, + ], + sha256: "", + }, + ], + passthrough: { + transformer: (data: Record): Record => { + let runsData = _.get(data, "runs"); + if (Array.isArray(runsData)) { + runsData = runsData.map((run: Record) => + _.omit(run, ["results"]) + ); + } + return { + auxiliary_data: [ + { + name: "SARIF", + data: { + $schema: _.get(data, "$schema"), + runs: runsData, + }, + }, + ], + ...(this.withRaw && { raw: data }), + }; + }, + }, + }; + constructor(sarifJson: string, withRaw = false) { + super(JSON.parse(sarifJson)); + this.withRaw = withRaw; + } +} +``` + +::: + +Now we have a fully implemented SARIF-to-OHDF mapper. From 0f9b7d3f75c83da9cb6b753cce2227602ba646d0 Mon Sep 17 00:00:00 2001 From: Aaron Lippold Date: Sun, 1 Dec 2024 21:49:44 -0600 Subject: [PATCH 70/71] Update src/courses/mappers/13.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Signed-off-by: Aaron Lippold --- src/courses/mappers/13.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index f3823a9dd..25326abf3 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -32,7 +32,7 @@ yarn run test --verbose --silent=false ./test/mappers/forward/{YOUR-EXPORT-NAME- 3. After running this command, you should see two files named `SKELETON-hdf.json` and `SKELETON-hdf-withraw.json` appear in the `sample_jsons/SKELETON_mapper/` directory. Check these files to make sure that the OHDF mapper output looks correct and aligns with your mapping. `SKELETON-hdf.json` should match your mapping completely, while `SKELETON-hdf-withraw.json` should also include your original source data in the OHDF output file. -4. Recomment out the lines from step 1. +4. Re-comment out the lines from step 1. 5. Future uses of the command in step 2 will now leverage the baseline files you generated to perform regression testing. It will compare the contents of these generated files with temporary outputs created by the mapper instance to check for field alignment. Review the test output to ensure that the tests are all passing. From 1882b69f3c1589b2bd0f500a47853880fce49630 Mon Sep 17 00:00:00 2001 From: Aaron Lippold Date: Sun, 1 Dec 2024 21:50:18 -0600 Subject: [PATCH 71/71] Update src/courses/mappers/13.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Signed-off-by: Aaron Lippold --- src/courses/mappers/13.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/courses/mappers/13.md b/src/courses/mappers/13.md index 25326abf3..a5ead72d2 100644 --- a/src/courses/mappers/13.md +++ b/src/courses/mappers/13.md @@ -15,7 +15,7 @@ Regression testing is extremely useful, as we make changes and improvements to m First, we have to activate the regression testing suite that we created earlier to actually be able to automatically run and review your mapper. -1. Uncomment out the commented out lines in the `{YOUR-SAMPLE-EXPORT}-hdf.json` file. This will allow the regression tests to automatically generate an OHDF output file whenever you run the tests. These files are needed for the tests to check the output of your mappers. The commented out lines should look similar to the following: +1. Uncomment the lines in the `{YOUR-SAMPLE-EXPORT}-hdf.json` file. This will allow the regression tests to automatically generate an OHDF output file whenever you run the tests. These files are needed for the tests to check the output of your mappers. The commented out lines should look similar to the following: ```typescript // fs.writeFileSync(

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