Description (CNA)
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.
Affected (CNA)
| Vendor / product | Versions |
|---|---|
| mlflow / mlflow/mlflow | affected unspecified before 3.8.2 |
CWE
CWE-77
References
- https://huntr.com/bounties/dc9c1c20-7879-4050-87df-4d095fe5ca75
- https://github.com/mlflow/mlflow/commit/361b6f620adf98385c6721e384fb5ef9a30bb05e
ADP enrichment
No English description supplied.
No references supplied.
A flaw was found in MLflow. When deploying a model with `env_manager=LOCAL`, MLflow's model serving container initialization code, specifically the `_install_model_dependencies_to_env()` function, reads dependency specifications from the model artifact's `python_env.yaml` file. An attacker can supply a malicious model artifact, leading to command injection as these specifications are directly interpolated into a shell command without proper sanitization. This allows for arbitrary command execution on systems deploying the malicious model.