Mlflow up to 3.16.x Scorer base.py Scorer.model_validate_json deserialization

Summaryinfo

A vulnerability, which was classified as critical, has been found in Mlflow up to 3.16.x. This affects the function Scorer.model_validate_json of the file mlflow/genai/scorers/base.py of the component Scorer. This manipulation causes deserialization. This vulnerability is handled as CVE-2026-116692. The attack can be initiated remotely. There is not any exploit available. It is advisable to upgrade the affected component.

Detailsinfo

A vulnerability was found in Mlflow up to 3.16.x. It has been declared as critical. Affected by this vulnerability is the function Scorer.model_validate_json of the file mlflow/genai/scorers/base.py of the component Scorer. The manipulation with an unknown input leads to a deserialization vulnerability. The CWE definition for the vulnerability is CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. As an impact it is known to affect confidentiality, integrity, and availability. The summary by CVE is:

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.

The advisory is shared at github.com. This vulnerability is known as CVE-2026-116692 since 10/26/2026. The exploitation appears to be easy. The attack can be launched remotely. The exploitation doesn't need any form of authentication. Technical details are known, but no exploit is available.

Upgrading to version 3.17.0 eliminates this vulnerability.

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Productinfo

Name

• Mlflow

Version

• 3.0
• 3.1
• 3.2
• 3.3
• 3.4
• 3.5
• 3.6
• 3.7
• 3.8
• 3.9
• 3.10
• 3.11
• 3.12
• 3.13
• 3.14
• 3.15
• 3.16

Website

• Product: https://github.com/mlflow/mlflow/

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Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

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