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Untrusted search path under some conditions on Windows allows arbitrary code execution

High severity GitHub Reviewed Published Jan 10, 2024 in gitpython-developers/GitPython • Updated Sep 20, 2024

Package

pip GitPython (pip)

Affected versions

< 3.1.41

Patched versions

3.1.41

Description

Summary

This issue exists because of an incomplete fix for CVE-2023-40590. On Windows, GitPython uses an untrusted search path if it uses a shell to run git, as well as when it runs bash.exe to interpret hooks. If either of those features are used on Windows, a malicious git.exe or bash.exe may be run from an untrusted repository.

Details

Although GitPython often avoids executing programs found in an untrusted search path since 3.1.33, two situations remain where this still occurs. Either can allow arbitrary code execution under some circumstances.

When a shell is used

GitPython can be told to run git commands through a shell rather than as direct subprocesses, by passing shell=True to any method that accepts it, or by both setting Git.USE_SHELL = True and not passing shell=False. Then the Windows cmd.exe shell process performs the path search, and GitPython does not prevent that shell from finding and running git in the current directory.

When GitPython runs git directly rather than through a shell, the GitPython process performs the path search, and currently omits the current directory by setting NoDefaultCurrentDirectoryInExePath in its own environment during the Popen call. Although the cmd.exe shell will honor this environment variable when present, GitPython does not currently pass it into the shell subprocess's environment.

Furthermore, because GitPython sets the subprocess CWD to the root of a repository's working tree, using a shell will run a malicious git.exe in an untrusted repository even if GitPython itself is run from a trusted location.

This also applies if Git.execute is called directly with shell=True (or after Git.USE_SHELL = True) to run any command.

When hook scripts are run

On Windows, GitPython uses bash.exe to run hooks that appear to be scripts. However, unlike when running git, no steps are taken to avoid finding and running bash.exe in the current directory.

This allows the author of an untrusted fork or branch to cause a malicious bash.exe to be run in some otherwise safe workflows. An example of such a scenario is if the user installs a trusted hook while on a trusted branch, then switches to an untrusted feature branch (possibly from a fork) to review proposed changes. If the untrusted feature branch contains a malicious bash.exe and the user's current working directory is the working tree, and the user performs an action that runs the hook, then although the hook itself is uncorrupted, it runs with the malicious bash.exe.

Note that, while bash.exe is a shell, this is a separate scenario from when git is run using the unrelated Windows cmd.exe shell.

PoC

On Windows, create a git.exe file in a repository. Then create a Repo object, and call any method through it (directly or indirectly) that supports the shell keyword argument with shell=True:

mkdir testrepo
git init testrepo
cp ... testrepo git.exe # Replace "..." with any executable of choice.
python -c "import git; print(git.Repo('testrepo').git.version(shell=True))"

The git.exe executable in the repository directory will be run.

Or use no Repo object, but do it from the location with the git.exe:

cd testrepo
python -c "import git; print(git.Git().version(shell=True))"

The git.exe executable in the current directory will be run.

For the scenario with hooks, install a hook in a repository, create a bash.exe file in the current directory, and perform an operation that causes GitPython to attempt to run the hook:

mkdir testrepo
cd testrepo
git init
mv .git/hooks/pre-commit.sample .git/hooks/pre-commit
cp ... bash.exe # Replace "..." with any executable of choice.
echo "Some text" >file.txt
git add file.txt
python -c "import git; git.Repo().index.commit('Some message')"

The bash.exe executable in the current directory will be run.

Impact

The greatest impact is probably in applications that set Git.USE_SHELL = True for historical reasons. (Undesired console windows had, in the past, been created in some kinds of applications, when it was not used.) Such an application may be vulnerable to arbitrary code execution from a malicious repository, even with no other exacerbating conditions. This is to say that, if a shell is used to run git, the full effect of CVE-2023-40590 is still present. Furthermore, as noted above, running the application itself from a trusted directory is not a sufficient mitigation.

An application that does not direct GitPython to use a shell to run git subprocesses thus avoids most of the risk. However, there is no such straightforward way to prevent GitPython from running bash.exe to interpret hooks. So while the conditions needed for that to be exploited are more involved, it may be harder to mitigate decisively prior to patching.

Possible solutions

A straightforward approach would be to address each bug directly:

  • When a shell is used, pass NoDefaultCurrentDirectoryInExePath into the subprocess environment, because in that scenario the subprocess is the cmd.exe shell that itself performs the path search.
  • Set NoDefaultCurrentDirectoryInExePath in the GitPython process environment during the Popen call made to run hooks with a bash.exe subprocess.

These need only be done on Windows.

References

@Byron Byron published to gitpython-developers/GitPython Jan 10, 2024
Published to the GitHub Advisory Database Jan 10, 2024
Reviewed Jan 10, 2024
Published by the National Vulnerability Database Jan 11, 2024
Last updated Sep 20, 2024

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction Active
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

EPSS score

0.050%
(20th percentile)

Weaknesses

CVE ID

CVE-2024-22190

GHSA ID

GHSA-2mqj-m65w-jghx

Credits

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