AI agent vulnerability · MLflow

CVE-2025-15379: MLflow Command Injection vulnerability

criticalCVSS 3.0 10.0GHSA-r23q-823p-vmf7

A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the installmodeldependenciestoenv() function. When deploying a model with envmanager=LOCAL, MLflow reads dependency specifications from the model artifact's pythonenv.yaml file and directly interpolates them into a shell command without sanitization.

Published Mar 30, 2026 · Updated Apr 1, 2026

Affected packages

mlflow

Ecosystem: PyPI
Affected: < 3.8.1
Fixed in: 3.8.1
Check: pip show mlflow

Advisory details

From the GitHub Advisory Database (CC BY 4.0).

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 3.8.1.

Credited to drhreddy.

References

How this page is made: the data panel comes from the GitHub Advisory Database, CISA’s KEV catalog, the NVD and FIRST EPSS, and updates twice a day. No analysis has been written for this entry yet. Methodology

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