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.
Attack Parameters
Attack Vector
Network
Can be exploited remotely
Attack Complexity
High
Difficult to exploit
Privileges Required
None
No privileges needed
User Interaction
Required
User action required
Impact Assessment
Confidentiality
High
Complete data leak
Integrity
High
Complete data modification
Availability
High
Complete denial of service
CVSS Vector v3.0