MLflow's pickle-block setting misses one loader, letting RCE through

MLflow's pickle-block setting misses one loader, letting RCE through

Summary

MLflow introduced MLFLOW_ALLOW_PICKLE_DESERIALIZATION as a security control to prevent unsafe pickle.load execution during model loading, in response to CVE-2024-37052 through CVE-2024-37060. When set to False, operators expect all pickle deserialization to be blocked. The most recent related fix (#21188) patched a bypass in the pyfunc flavor.

However, the mlflow.statsmodels flavor completely omits this guard. An attacker who places a crafted MLmodel artifact into any accessible artifact store can trigger arbitrary code execution on any process that calls `mlflow.pyfunc.lo