From 76b9a12035f18828188e2a790054e884198e1b64 Mon Sep 17 00:00:00 2001 From: Paul Hutelmyer Date: Tue, 2 Apr 2024 09:20:27 -0400 Subject: [PATCH 1/5] Adding Broken Email Test --- src/python/strelka/scanners/scan_email.py | 270 +++++++----------- .../strelka/tests/fixtures/test_broken.eml | 33 +++ src/python/strelka/tests/test_scan_email.py | 44 ++- 3 files changed, 179 insertions(+), 168 deletions(-) create mode 100644 src/python/strelka/tests/fixtures/test_broken.eml diff --git a/src/python/strelka/scanners/scan_email.py b/src/python/strelka/scanners/scan_email.py index b5bea6a8..7f5e8152 100644 --- a/src/python/strelka/scanners/scan_email.py +++ b/src/python/strelka/scanners/scan_email.py @@ -51,11 +51,7 @@ def scan(self, data, file, options, expire_at): thumbnail_header = options.get("thumbnail_header", False) thumbnail_size = options.get("thumbnail_size", (500, 500)) - # ---------------- - # Thumbnail - # ---------------- - # Create a thumbnail from the image. - # Stores as a base64 value in the key: base64_thumbnail + # Attempt to create a thumbnail from the email if create_thumbnail: try: image = self.create_email_thumbnail(data, thumbnail_header) @@ -67,184 +63,124 @@ def scan(self, data, file, options, expire_at): self.event["base64_thumbnail"] = base64_image else: self.flags.append( - f"{self.__class__.__name__}: image_thumbnail_error: Could not generate thumbnail." + f"{self.__class__.__name__}: image_thumbnail_error: Could not generate thumbnail. No HTML found." ) except Exception as e: self.flags.append( f"{self.__class__.__name__}: image_thumbnail_error: {str(e)[:50]}" ) - # ---------------- - # Parse Email Contents - # ------------------- + # Parse email contents try: # Open and parse email byte string - # If fail to open, return. - try: - ep = eml_parser.EmlParser( - include_attachment_data=True, include_raw_body=True - ) - parsed_eml = ep.decode_email_bytes(data) - except strelka.ScannerTimeout: - raise - except Exception as e: - self.flags.append( - f"{self.__class__.__name__}: email_parse_error: {str(e)[:50]}" - ) + ep = eml_parser.EmlParser( + include_attachment_data=True, include_raw_body=True + ) + parsed_eml = ep.decode_email_bytes(data) # Check if email was parsed properly and attempt to deconflict and reload. - # If fail to reparse, return. - try: - if not ( - parsed_eml["header"]["subject"] and parsed_eml["header"]["header"] - ): - if b"\nReceived: from " in data: - data = ( - data.rpartition(b"\nReceived: from ")[1] - + data.rpartition(b"\nReceived: from ")[2] - )[1:] - elif b"Start mail input; end with .\n" in data: - data = data.rpartition( - b"Start mail input; end with .\n" - )[2] - parsed_eml = ep.decode_email_bytes(data) - if not ( - parsed_eml["header"]["subject"] - and parsed_eml["header"]["header"] - ): - self.flags.append( - f"{self.__class__.__name__}: email_parse_error" - ) - return - except strelka.ScannerTimeout: - raise - except Exception as e: - self.flags.append( - f"{self.__class__.__name__}: email_parse_error: {str(e)[:50]}" - ) + if not (parsed_eml["header"]["subject"] and parsed_eml["header"]["header"]): + if b"\nReceived: from " in data: + data = ( + data.rpartition(b"\nReceived: from ")[1] + + data.rpartition(b"\nReceived: from ")[2] + )[1:] + elif b"Start mail input; end with .\n" in data: + data = data.rpartition( + b"Start mail input; end with .\n" + )[2] + parsed_eml = ep.decode_email_bytes(data) - # Body - # If body exists in email, collect partial message contents and domains - try: - if "body" in parsed_eml: - for body in parsed_eml["body"]: - if "content_type" in body: - if body["content_type"] == "text/plain": - if len(body["content"]) <= 200: - self.event["body"] = body["content"] - else: - self.event["body"] = ( - body["content"][:100] - + "..." - + body["content"][-100:] - ) - else: - self.event["body"] = ( - body["content"][:100] + "..." + body["content"][-100:] - ) - if "domain" in body: - if "domain" in self.event: - self.event["domains"] += body["domain"] + # Extract body content and domains + if "body" in parsed_eml: + for body in parsed_eml["body"]: + if "content_type" in body: + if body["content_type"] == "text/plain": + if len(body["content"]) <= 200: + self.event["body"] = body["content"] else: - self.event["domains"] = body["domain"] - except strelka.ScannerTimeout: - raise - except Exception as e: - self.flags.append( - f"{self.__class__.__name__}: email_parse_body_error: {str(e)[:50]}" - ) - - # Attachments - # If attachments exist in email, collect attachment details and raw data to be resubmitted to pipeline. - try: - if "attachment" in parsed_eml: - self.event["attachments"] = {} - self.event["attachments"]["filenames"] = [] - self.event["attachments"]["hashes"] = [] - self.event["attachments"]["totalsize"] = 0 - for attachment in parsed_eml["attachment"]: - self.event["attachments"]["filenames"].append( - attachment["filename"] - ) - self.event["attachments"]["hashes"].append( - attachment["hash"]["md5"] - ) - self.event["attachments"]["totalsize"] += attachment["size"] - attachments.append( - { - "name": attachment["filename"], - "content-type": attachment["content_header"][ - "content-type" - ][0], - "raw": base64.b64decode(attachment["raw"]), - } + self.event["body"] = ( + body["content"][:100] + + "..." + + body["content"][-100:] + ) + else: + self.event["body"] = ( + body["content"][:100] + "..." + body["content"][-100:] ) - except strelka.ScannerTimeout: - raise - except Exception as e: - self.flags.append( - f"{self.__class__.__name__}: email_parse_attachment_error: {str(e)[:50]}" - ) + if "domain" in body: + if "domain" in self.event: + self.event["domains"] += body["domain"] + else: + self.event["domains"] = body["domain"] + + # Extract attachment details and raw data + if "attachment" in parsed_eml: + self.event["attachments"] = { + "filenames": [], + "hashes": [], + "totalsize": 0, + } + for attachment in parsed_eml["attachment"]: + self.event["attachments"]["filenames"].append( + attachment["filename"] + ) + self.event["attachments"]["hashes"].append( + attachment["hash"]["md5"] + ) + self.event["attachments"]["totalsize"] += attachment["size"] + attachments.append( + { + "name": attachment["filename"], + "content-type": attachment["content_header"][ + "content-type" + ][0], + "raw": base64.b64decode(attachment["raw"]), + } + ) - # Header - # Collect email header information - try: - self.event["subject"] = parsed_eml["header"]["subject"] - self.event["to"] = parsed_eml["header"]["to"] - self.event["from"] = parsed_eml["header"]["from"] + # Extract email header information + self.event["subject"] = parsed_eml["header"].get("subject", "") + self.event["to"] = parsed_eml["header"].get("to", "") + self.event["from"] = parsed_eml["header"].get("from", "") + date_header = parsed_eml["header"].get("date") + if date_header: self.event["date_utc"] = ( - parsed_eml["header"]["date"].astimezone(pytz.utc).isoformat()[:-6] - + ".000Z" + date_header.astimezone(pytz.utc).isoformat()[:-6] + ".000Z" ) - self.event["message_id"] = str( - parsed_eml["header"]["header"]["message-id"][0] - .lstrip("<") - .rstrip(">") - ) - if "received_domain" in parsed_eml["header"]: - self.event["received_domain"] = parsed_eml["header"][ - "received_domain" - ] - if "received_ip" in parsed_eml["header"]: - self.event["received_ip"] = parsed_eml["header"]["received_ip"] - except strelka.ScannerTimeout: - raise - except Exception as e: - self.flags.append( - f"{self.__class__.__name__}: email_parse_header_error: {str(e)[:50]}" - ) - - # If attachments were found, submit back into pipeline - try: - if attachments: - for attachment in attachments: - self.event["total"]["attachments"] += 1 - - name = attachment["name"] - try: - flavors = [ - attachment["content-type"] - .encode("utf-8") - .partition(b";")[0] - ] - except Exception as e: - self.flags.append( - f"{self.__class__.__name__}: email_extract_attachment_error: {str(e)[:50]}" - ) - - # Send extracted file back to Strelka - self.emit_file(attachment["raw"], name=name, flavors=flavors) - - self.event["total"]["extracted"] += 1 - except strelka.ScannerTimeout: - raise - except Exception as e: - self.flags.append( - f"{self.__class__.__name__}: email_extract_attachment_error: {str(e)[:50]}" - ) - - except AssertionError: - self.flags.append(f"{self.__class__.__name__}: email_assertion_error") + header = parsed_eml.get("header", {}).get("header", {}) + message_id = header.get("message-id", [])[0] if header else None + self.event["message_id"] = ( + str(message_id.lstrip("<").rstrip(">")) if message_id else "" + ) + self.event["received_domain"] = parsed_eml["header"].get( + "received_domain", [] + ) + self.event["received_ip"] = parsed_eml["header"].get("received_ip", []) + + # Process attachments + if attachments: + for attachment in attachments: + self.event["total"]["attachments"] += 1 + name = attachment["name"] + try: + flavors = [ + attachment["content-type"] + .encode("utf-8") + .partition(b";")[0] + ] + except Exception as e: + self.flags.append( + f"{self.__class__.__name__}: email_extract_attachment_error: {str(e)[:50]}" + ) + # Send extracted file back to Strelka + self.emit_file(attachment["raw"], name=name, flavors=flavors) + self.event["total"]["extracted"] += 1 + + except Exception as e: + self.flags.append( + f"{self.__class__.__name__}: email_parse_error: {str(e)[:50]}" + ) def create_email_thumbnail(self, data, show_header): """ diff --git a/src/python/strelka/tests/fixtures/test_broken.eml b/src/python/strelka/tests/fixtures/test_broken.eml new file mode 100644 index 00000000..d065450f --- /dev/null +++ b/src/python/strelka/tests/fixtures/test_broken.eml @@ -0,0 +1,33 @@ +Hi Placeholder, + +Can I have access? + +Thanks, +John + + +From: Placeholder Smith > +Date: Thursday, March 28, 2024 at 1:45 PM +To: "Jane.Doe" +Subject: Fwd: [EXTERNAL] Folder shared with you: "Strelka Details" + +Begin forwarded message: +From: "Placeholder Smith (via Acme Share)" +Date: March 27, 2024 at 6:47:31 PM EST +To: "Jane.Doe" +Cc: "John.Doe" +Subject: [EXTERNAL] Folder shared with you: "Strelka Details" +Reply-To: Placeholder Smith (placeholder@acme.com + +Placeholder shared a folder +Placeholder Smith (placeholder@acme.com) added you as an editor. Verify your email to securely start contributing to this folder. You will need to verify your email every 7 days. +Hello, attached is the shared folder. +Best, +Placeholder + +Open + +Use is subject to the Google Privacy Policy. + +ACME LLC, 123 Fake Street, USA +You have received this email because placeholder@acme.com shared a file or folder located in Acme Share with you. Delete visitor session diff --git a/src/python/strelka/tests/test_scan_email.py b/src/python/strelka/tests/test_scan_email.py index ce026617..10e3be1d 100644 --- a/src/python/strelka/tests/test_scan_email.py +++ b/src/python/strelka/tests/test_scan_email.py @@ -142,7 +142,11 @@ def test_scan_email_with_thumbnail(mocker): "2002:a05:6500:11d0:b0:17b:2a20:6c32", ] ), - "base64_thumbnail": "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", } scanner_event = run_test_scan( @@ -156,3 +160,41 @@ def test_scan_email_with_thumbnail(mocker): TestCase.maxDiff = None TestCase().assertDictEqual(test_scan_event, scanner_event) + + +def test_scan_email_incomplete(mocker): + """ + Pass: Sample event matches output of scanner. + Failure: Unable to load file or sample event fails to match. + """ + + test_scan_event = { + "elapsed": mock.ANY, + "flags": [ + "ScanEmail: image_thumbnail_error: Could not generate thumbnail. No HTML found." + ], + "total": {"attachments": 0, "extracted": 0}, + "body": "Hi Placeholder,\n\nCan I have access?\n\nThanks,\nJohn\n\n\nFrom: Placeholder Smith " + " shared a file or folder located in Acme Share with you. Delete visitor " + "session\n", + "domains": ["acme.com", "share.acme.com"], + "subject": "", + "to": [], + "from": "", + "date_utc": "1970-01-01T00:00:00.000Z", + "message_id": "", + "received_domain": [], + "received_ip": [], + } + + scanner_event = run_test_scan( + mocker=mocker, + scan_class=ScanUnderTest, + fixture_path=Path(__file__).parent / "fixtures/test_broken.eml", + options={ + "create_thumbnail": True, + }, + ) + + TestCase.maxDiff = None + TestCase().assertDictEqual(test_scan_event, scanner_event) From 99fefeb24a5f6ac0a5d283b36e4b8d83637d5551 Mon Sep 17 00:00:00 2001 From: Paul Hutelmyer Date: Tue, 2 Apr 2024 10:50:56 -0400 Subject: [PATCH 2/5] Updating tastes --- configs/python/backend/backend.yaml | 3 ++- configs/python/backend/taste/taste.yara | 17 +++++++++++++++++ src/python/strelka/tests/test_scan_email.py | 11 ++++++----- 3 files changed, 25 insertions(+), 6 deletions(-) diff --git a/configs/python/backend/backend.yaml b/configs/python/backend/backend.yaml index f8bb6847..92400677 100644 --- a/configs/python/backend/backend.yaml +++ b/configs/python/backend/backend.yaml @@ -1,4 +1,4 @@ -version: 2024.02.01.01 +version: 2024.04.02.01 logging_cfg: '/etc/strelka/logging.yaml' limits: max_files: 5000 @@ -107,6 +107,7 @@ scanners: - 'application/vnd.ms-outlook' - 'message/rfc822' - 'email_file' + - 'email_file_broad' priority: 5 options: create_thumbnail: True diff --git a/configs/python/backend/taste/taste.yara b/configs/python/backend/taste/taste.yara index baa5047e..5064d82d 100644 --- a/configs/python/backend/taste/taste.yara +++ b/configs/python/backend/taste/taste.yara @@ -464,6 +464,23 @@ rule email_file { $e in (0..2048) } +rule email_file_broad +{ + meta: + type = "email" + strings: + $ = "Received: " + $ = "Origin-messageId: " + $ = "Return-Path: " + $ = "From: " + $ = "To: " + $ = "Subject: " + $ = "Date: " + condition: + magic.mime_type() == "message/rfc822" or + all of them +} + rule tnef_file { meta: description = "Transport Neutral Encapsulation Format" diff --git a/src/python/strelka/tests/test_scan_email.py b/src/python/strelka/tests/test_scan_email.py index 10e3be1d..b3ddfab1 100644 --- a/src/python/strelka/tests/test_scan_email.py +++ b/src/python/strelka/tests/test_scan_email.py @@ -142,11 +142,12 @@ def test_scan_email_with_thumbnail(mocker): "2002:a05:6500:11d0:b0:17b:2a20:6c32", ] ), - "base64_thumbnail": "UklGRnJAAABXRUJQVlA4IGZAAAAQBwGdASqCAfQBPxF+tVOsKCSkKfxJuYAiCWlu/GwZq+tQzPE/4V/qf7/4s" - "+XXkN+//s04j7Vv7X8/vNb//+Bfyy//f3p9wXz36Vj4TrDQF+l/7798/UM/O81/3Xmu/1n7feUJ9y/3H7ifAT" - "/Vf896av3l6S/4T/4fvp8CH+K/7/7/ldkkCIGW+8Nid8kgRAy33hsTvkkCIGW+8Nid8kgRAy33hsTvkkCIGW" - "+8Nid8kfIoTYHLouMkva2/n6FHGZMLvDYnfJIEQMsbA0RoornnZFBRZqselPM/Ve" - 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} scanner_event = run_test_scan( From 88abc625dea321ebb1152d526cab0424385ae8fe Mon Sep 17 00:00:00 2001 From: Paul Hutelmyer Date: Tue, 2 Apr 2024 10:53:43 -0400 Subject: [PATCH 3/5] Update test_scan_email.py --- src/python/strelka/tests/test_scan_email.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/python/strelka/tests/test_scan_email.py b/src/python/strelka/tests/test_scan_email.py index b3ddfab1..1dc145b3 100644 --- a/src/python/strelka/tests/test_scan_email.py +++ b/src/python/strelka/tests/test_scan_email.py @@ -143,11 +143,11 @@ def test_scan_email_with_thumbnail(mocker): ] ), "base64_thumbnail": "UklGRgQ+AABXRUJQVlA4IPg9AADw/ACdASqCAfQBPxF+tFQsKCUjKfw5WYAiCWlu/F+5jutQzvEJ4w" - "/pvBHyNfRf3X/I////kchr3//S82P6//If/nrE/rO8n56f/3qBfs3789Kx771c5++wR5A/en1Jfx/Nn928trzn" - "/1n7feTf9p/2H7afAP/T/9H6bH3p6Uf4T/6/vv8C/+b/9n75FL7nZ5mu4gd9zs8zXcQO" - "+52eZruIHfc7PM13EDvudnma7iB33OzzNdxA77nZ3+e5IriyfRIt/vg3" - "+pSaeYt4QBPM13EDvuS8U1MkohIJ9SAbDbgdtEaNdcub66DxvHIoijT9sn+Ue" - 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} scanner_event = run_test_scan( From 141478689717a32cc1e9abbd7c64be7b4f0516c7 Mon Sep 17 00:00:00 2001 From: Sara Kalupa Date: Thu, 18 Apr 2024 13:48:21 -0500 Subject: [PATCH 4/5] Adding in ScanJNLP --- docs/README.md | 3 +- src/python/strelka/scanners/scan_jnlp.py | 106 ++++++++++++++++++++ src/python/strelka/tests/fixtures/test.jnlp | 20 ++++ src/python/strelka/tests/test_scan_jnlp.py | 26 +++++ 4 files changed, 154 insertions(+), 1 deletion(-) create mode 100644 src/python/strelka/scanners/scan_jnlp.py create mode 100644 src/python/strelka/tests/fixtures/test.jnlp create mode 100644 src/python/strelka/tests/test_scan_jnlp.py diff --git a/docs/README.md b/docs/README.md index 73d36e2f..4a1998c3 100644 --- a/docs/README.md +++ b/docs/README.md @@ -798,7 +798,8 @@ The table below describes each scanner and its options. Each scanner has the hid | ScanIso | Collects and extracts files from ISO files | `limit` -- maximum number of files to extract (defaults to `0`) | | ScanJarManifest | Collects metadata from JAR manifest files | N/A | | ScanJavascript | Collects metadata from Javascript files | `beautify` -- beautifies JavaScript before parsing (defaults to `True`) | -| ScanJpeg | Extracts data embedded in JPEG files | N/A | +| ScanJpeg | Extracts data embedded in JPEG files | N/A +| ScanJnlp | Identifies JNLP files that reference external HTTP resources, particularly those not associated with trusted domains | N/A | Ryan Borre, [Paul Hutelmyer](https://github.com/phutelmyer) | | ScanJson | Collects keys from JSON files | N/A | | ScanLibarchive | Extracts files from libarchive-compatible archives. | `limit` -- maximum number of files to extract (defaults to `1000`) | | ScanLnk | Collects metadata from lnk files. | N/A | Ryan Borre, [DerekT2](https://github.com/Derekt2), [Nathan Icart](https://github.com/nateicart) diff --git a/src/python/strelka/scanners/scan_jnlp.py b/src/python/strelka/scanners/scan_jnlp.py new file mode 100644 index 00000000..6c365ab1 --- /dev/null +++ b/src/python/strelka/scanners/scan_jnlp.py @@ -0,0 +1,106 @@ +from io import BytesIO + +from lxml import etree + +from strelka import strelka + + +class ScanJnlp(strelka.Scanner): + """ + Analyzes Java Network Launch Protocol (JNLP) files. + + JNLP files, used by Java Web Start technology, can launch Java applications from a web browser. While facilitating + legitimate applications, they can also be abused for malicious purposes such as distributing malware or executing + phishing attacks. + + Scanner Type: Collection + + Attributes: + event (dict): Stores extracted data during the scan for further analysis. + + Detection Use Cases: + - **External Resource Reference** + - Identify JNLP files that reference external HTTP resources, particularly those not associated with trusted + domains. + + Known Limitations: + - **Java Dependence** + - Effectiveness is contingent on the presence and version of Java installed on the target system. + + Todo: + - Improve detection of obfuscated or sophisticated threats within JNLP files. + - Extract any other potential JNLP content / headers. + + References: + - **File Structure** + - https://docs.oracle.com/javase/tutorial/deployment/deploymentInDepth/jnlpFileSyntax.html + - **Malicious Usage** + - https://www.forcepoint.com/blog/x-labs/java-network-launch-protocol + - https://newtonpaul.com/analysing-fileless-malware-cobalt-strike-beacon + """ + + def scan(self, data, file, options, expire_at): + """ + Scans the given data for JNLP-related information. + + Extracts 'codebase' and 'href' attributes from JNLP and JAR tags to detect potential malicious activities. + + Args: + data (bytes): Data of the file being scanned. + file (File): File object being scanned. + options (dict): Options for the scanner. + expire_at (datetime): Expiration time of the scan result. + """ + # Initialize variables for 'codebase' and 'href' attributes + codebase = "" + href = "" + + # Parse the XML to find 'jnlp' and 'jar' elements + for elem, _ in iterate_xml_elements(data, tags=["jnlp", "jar"]): + if elem.tag == "jnlp": + codebase = elem.get("codebase", "").rstrip("/") + elif elem.tag == "jar": + href = elem.get("href", "").lstrip("/") + + # If both 'codebase' and 'href' are found, construct the full resource URL + if codebase and href: + self.event["resource"] = f"{codebase}/{href}" + + +def iterate_xml_elements(data, tags=None): + """ + Iterates over XML data, yielding elements with specified tags. + + This method parses the XML data byte by byte and yields elements that match the specified tags. This is useful + for extracting specific information from structured XML documents. + + Args: + data (bytes): The XML data to parse. + tags (list): List of XML tags to filter elements by. + + Yields: + tuple: A tuple containing the XML element and its depth in the XML tree. + """ + # Define the events to listen for during XML parsing + events = ("start", "end") + depth = 0 + inside_tags = [] + + # Parse the XML data + for event, elem in etree.iterparse(BytesIO(data), events=events): + if event == "start": + # If the element's tag is one we're interested in, track it and its depth + if tags is None or elem.tag in tags: + inside_tags.append((elem.tag, depth)) + depth += 1 + elif event == "end": + # On end tag, reduce depth and check if the closing tag is one we're tracking + depth -= 1 + if depth < 0: + continue + + # Check if the current element should be yielded + is_wanted = tags is None or elem.tag in tags + if is_wanted and inside_tags and inside_tags[-1][0] == elem.tag: + inside_tags.pop() + yield elem, depth diff --git a/src/python/strelka/tests/fixtures/test.jnlp b/src/python/strelka/tests/fixtures/test.jnlp new file mode 100644 index 00000000..13969e77 --- /dev/null +++ b/src/python/strelka/tests/fixtures/test.jnlp @@ -0,0 +1,20 @@ + + + + SECURE DOCUMENT VIEWER + Microsoft + + Secure document viewer app + + + + + + + + + + + +1234abcdeF56789 + \ No newline at end of file diff --git a/src/python/strelka/tests/test_scan_jnlp.py b/src/python/strelka/tests/test_scan_jnlp.py new file mode 100644 index 00000000..c6c14bb4 --- /dev/null +++ b/src/python/strelka/tests/test_scan_jnlp.py @@ -0,0 +1,26 @@ +from pathlib import Path +from unittest import TestCase, mock + +from strelka.scanners.scan_jnlp import ScanJnlp as ScanUnderTest +from strelka.tests import run_test_scan + + +def test_scan_jnlp(mocker): + """ + Pass: Sample event matches output of scanner. + Failure: Unable to load file or sample event fails to match. + """ + test_scan_event = { + "elapsed": mock.ANY, + "flags": [], + "resource": "https://example.com/uplib.jar", + } + + scanner_event = run_test_scan( + mocker=mocker, + scan_class=ScanUnderTest, + fixture_path=Path(__file__).parent / "fixtures/test.jnlp", + ) + + TestCase.maxDiff = None + TestCase().assertDictEqual(test_scan_event, scanner_event) From a8d847aeebf4dab7ac277716bc47ccf54b9e9675 Mon Sep 17 00:00:00 2001 From: Sara Kalupa Date: Thu, 18 Apr 2024 14:03:00 -0500 Subject: [PATCH 5/5] Enabling ScanJnlp in backend.yaml --- configs/python/backend/backend.yaml | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/configs/python/backend/backend.yaml b/configs/python/backend/backend.yaml index f8bb6847..b48ed40f 100644 --- a/configs/python/backend/backend.yaml +++ b/configs/python/backend/backend.yaml @@ -272,6 +272,11 @@ scanners: - 'application/json' - 'json_file' priority: 5 + 'ScanJnlp': + - positive: + flavors: + - "jnlp_file" + priority: 5 'ScanLibarchive': - positive: flavors: