Vulnerability Description
A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact's `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.2.
CVSS Score
CRITICAL
Affected Products
| Vendor | Product | Versions |
|---|---|---|
| Lfprojects | Mlflow | >= 3.8.0, <= 3.8.1 |
Related Weaknesses (CWE)
References
- https://github.com/mlflow/mlflow/commit/361b6f620adf98385c6721e384fb5ef9a30bb05ePatch
- https://huntr.com/bounties/dc9c1c20-7879-4050-87df-4d095fe5ca75ExploitThird Party Advisory
FAQ
What is CVE-2025-15379?
CVE-2025-15379 is a vulnerability with a CVSS score of 9.8 (CRITICAL). A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_...
How severe is CVE-2025-15379?
CVE-2025-15379 has been rated CRITICAL with a CVSS base score of 9.8/10. This is considered a critical vulnerability requiring immediate attention.
Is there a patch for CVE-2025-15379?
Check the references section above for vendor advisories and patch information. Affected products include: Lfprojects Mlflow.