ZDI-26-845: MLflow Statsmodels _load_model Deserialization of Untrusted Data Remote Code Execution Vulnerability
Summary: ZDI-26-845 describes a remote code execution vulnerability in MLflow's _load_model function, caused by missing validation of user-supplied data that leads to deserialization of untrusted data. Exploitation requires user interaction, such as visiting a malicious page or opening a malicious file, and allows an attacker to execute code in the context of the current user; it is fixed in MLflow 3.15.0.
Key Takeaway: The flaw sits in a model-loading function, so the malicious file a target must open is the kind of artifact MLflow users routinely load, and successful exploitation runs code as that user.
Read the original at Zero Day Initiative ↗
- Topics
- Vulnerabilities & Patching
- Mentions
- CVE-2024-37052
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