MLflow vulnerable to remote code execution on unauthenticated servers via third-party scorer deserialization importing caller-placed artifact modules

[ Why it matters ]Priority signals

• Public proof-of-concept exploit exists (CISA SSVC)
• Critical severity: CVSS 9.8

[ Description ]Official description

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.

[ Fixes ]Fixes and patches

• mlflow 3.17.0Fixed version · GitHub Advisories · pip package mlflow: upgrade to 3.17.0 or later (affected >= 3.12.0rc0, < 3.17.0)

[ Advisories ]Government CERT advisories

• BSI CERT-Bund8 Oct 2026WID-SEC-2026-3825

  MLflow: Vulnerability allows code execution Translated from German

  CVE-2026-116692

[ Packages ]Affected open-source packages

• mlflow pipAffected >= 3.12.0rc0, < 3.17.0 · fixed in 3.17.0 · GHSA-26p8-2jq9-3vq9

[ References ]References

• github.com/mlflow/mlflow/commit/a732443e695c3c677680c54320efc394c81654ab
• github.com/mlflow/mlflow/pull/25906
• github.com/mlflow/mlflow/releases/tag/v3.17.0
• github.com/mlflow/mlflow/security/advisories/GHSA-26p8-2jq9-3vq9