MLflow has a command injection in mlflow/sagemaker/__init__.pyGHSA-xch3-2f9x-wh9f
HIGHFix: mlflow/mlflow#19277GHSA-xch3-2f9x-wh9f is a high-severity (CVSS 7.5) Code Injection vulnerability in mlflow. A fix is available for mlflow — see the affected versions and patch details below.
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
- A successful exploit gives an attacker total control of the affected component, not partial access.
Exploitation and automatability from CISA’s SSVC triage for GHSA-xch3-2f9x-wh9f.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
Where this sits among everything scored
Real-World Exposure
mlflowReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
A command injection vulnerability exists in mlflow/mlflow versions before v3.7.0, specifically in the mlflow/sagemaker/__init__.py file at lines 161-167. The vulnerability arises from the direct interpolation of user-supplied container image names into shell commands without proper sanitization, which are then executed using os.system(). This allows attackers to execute arbitrary commands by supplying malicious input through the --container parameter of the CLI. The issue affects environments where MLflow is used, including development setups, CI/CD pipelines, and cloud deployments.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | mlflow | all versions | 3.8.0rc0pip install --upgrade 'mlflow==3.8.0rc0' |
Affected Products
mlflowlfprojectsDetection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for mlflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update mlflow to 3.8.0rc0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-xch3-2f9x-wh9f is resolved across your whole dependency graph.
Workarounds
Stop passing untrusted input into the interpreter or shell: call the affected binary with an argument array rather than a composed command string, reject anything outside a strict allowlist of expected values, and run the component under an account that cannot reach beyond the work it legitimately does.
Frequently Asked Questions
Is GHSA-xch3-2f9x-wh9f in your dependencies?
Find it across PyPI, including transitive dependencies.