Bug 2562393 (CVE-2026-116692)

Summary: CVE-2026-116692 mlflow: MLflow: Remote code execution on unauthenticated MLflow servers via third-party scorer deserialization importing caller-placed artifact modules
Product: [Other] Security Response Reporter: OSIDB Bzimport <bzimport>
Component: vulnerabilityAssignee: Product Security DevOps Team <prodsec-dev>
Status: NEW --- QA Contact:
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Priority: urgent    
Version: unspecifiedKeywords: Security
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OS: Linux   
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A flaw was found in MLflow. This vulnerability allows a remote attacker to achieve arbitrary code execution on the server. By uploading a crafted Python file through artifact endpoints and invoking a third-party scorer, an attacker can bypass module restrictions and force the server to dynamically import and execute the untrusted code. Successful exploitation could allow an attacker to gain control of the MLflow service and access sensitive system data.
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Description OSIDB Bzimport 2026-10-27 20:21:58 UTC 
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.