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CVE-2025-15379 is a command injection vulnerability in MLflow's model serving container initialization logic. The flaw is in the _install_model_dependencies_to_env() function, which, during model deployment with env_manager=LOCAL, reads dependency specifications from the model artifact's python_env.yaml file and interpolates them into a shell command without proper sanitization. An attacker who can supply a malicious model artifact can inject shell metacharacters or crafted dependency content, resulting in arbitrary command execution on the system performing the deployment. The provided context states the issue affects MLflow 3.8.0 and is fixed in 3.8.2.
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env_manager=LOCAL. Treat python_env.yaml within model artifacts as untrusted input. Restrict who can upload or register models, validate and review model artifacts before deployment, and isolate model serving/deployment environments to limit blast radius if command execution occurs. Where operationally possible, use deployment configurations that do not invoke the vulnerable local dependency installation path.Patch, then assume compromise.
361b6f620adf98385c6721e384fb5ef9a30bb05e in the mlflow/mlflow repository. Any deployment pipelines or serving environments using MLflow 3.8.0 should be updated promptly.No public exploits tracked yet. Mallory keeps watching.
No public exploit code observed for this vulnerability.
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