MLflow up to 3.16.x Scorer invoke Scorer.model_validate_json api_key deserialization

Summaryinfo

A vulnerability was found in MLflow up to 3.16.x. It has been classified as critical. This impacts the function Scorer.model_validate_json of the file /ajax-api/3.0/mlflow/scorer/invoke of the component Scorer. Performing a manipulation of the argument api_key results in deserialization. This vulnerability is cataloged as CVE-2026-115886. It is possible to initiate the attack remotely. There is no exploit available. Upgrading the affected component is recommended.

Detailsinfo

A vulnerability was found in MLflow up to 3.16.x. It has been classified as critical. This affects the function Scorer.model_validate_json of the file /ajax-api/3.0/mlflow/scorer/invoke of the component Scorer. The manipulation of the argument api_key with an unknown input leads to a deserialization vulnerability. CWE is classifying the issue as CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. This is going to have an impact on 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, the scorer invoke, register, and GenAI evaluate endpoints, including unauthenticated POST /ajax-api/3.0/mlflow/scorer/invoke, accept serialized third-party scorer data that Scorer.model_validate_json resolves using a module-path allowlist without constraining the selected class or its constructor arguments. When optional trulens and trulens-providers-litellm packages are installed, an attacker can select mlflow.genai.scorers.trulens, choose a model URI outside MLflow's native provider registry so execution uses the LiteLLM fallback, and supply api_base and api_key values that cause the server to send an outbound request to an attacker-chosen or internal host with attacker-controlled headers and body. The vulnerable deserialization occurs before a tracking-store lookup or job submission. This issue is fixed in version 3.17.0.

It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2026-115886 since 10/23/2026. The exploitability is told to be easy. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. Technical details of the vulnerability are known, but there is no available exploit.

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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