MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.12.0rc0 until 3.17.0, third-party scorer deserialization in mlflow/genai/scorers/base.py accepts request-selected descendants of THIRD_PARTY_SCORER_ALLOWED_MODULES rather than requiring an exact allowed module. A caller can use MLflow artifact endpoints to place a Python module beneath a writable allowed package and submit its module and class through /ajax-api/3.0/mlflow/scorer/invoke. Scorer.model_validate_json() imports the module and constructs the class before trace processing. Authentication-disabled deployments permit this code execution without credentials, while basic-auth deployments require a principal capable of creating an experiment and run and uploading artifacts. In either configuration, the allowed scorer package must be writable by the server process. This issue is fixed in version 3.17.0.
Fix
Nothing published yet: no patch, vendor advisory or mitigation reference on NVD, no vendor advisory in the News for this CVE, not in CISA's KEV, no fixed package version. BaselineWatch does not guess at one.
Public exploits 1
- foxcornlab/mlflow-scorer-scanner PoC on GitHub
Each line links to the index that lists it, never to exploit code. Exploit-DB's "verified" and a Metasploit rank of good or better count as verified; a PoC-in-GitHub entry is a repository's claim.
Change history 4
- StatusPublished → Awaiting AnalysisNVD modified 2026-10-28 15:21
- StatusReceived → PublishedNVD modified 2026-10-27 20:03
- StatusPublished → ReceivedNVD modified 2026-10-27 21:18
- First seenCVSS 9.8 · mlflowNVD modified 2026-10-27 20:03
Affected (CPE criteria) 0
NVD has not attached CPE configurations yet.