CVE-2026-3198
Authentication Bypass in MLflow 3.9.0 Gateway API
Publication date: 2026-06-02
Last updated on: 2026-06-02
Assigner: huntr.dev
Description
Description
CVSS Scores
EPSS Scores
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Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| mlflow | mlflow | 3.9.0 |
Helpful Resources
Exploitability
| CWE ID | Description |
|---|---|
| CWE-284 | The product does not restrict or incorrectly restricts access to a resource from an unauthorized actor. |
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?
This vulnerability exists in MLflow version 3.9.0 when using basic-auth mode. The software fails to enforce proper authorization checks on several Gateway API 'list' endpoints. Specifically, certain endpoints like ListGatewaySecretInfos, ListGatewayEndpoints, and ListGatewayModelDefinitions are not included in the authorization check handlers. As a result, any authenticated user, regardless of their permissions, can access and enumerate sensitive information such as gateway secrets, API keys, endpoint configurations, and proprietary model definitions.
How can this vulnerability impact me? :
The impact of this vulnerability is that unauthorized users who have basic authentication credentials can access sensitive information that should be restricted. This includes API keys, endpoint configurations, and proprietary model definitions. Exposure of such information can lead to further security breaches, unauthorized access to systems, and potential misuse of confidential data.
How does this vulnerability affect compliance with common standards and regulations (like GDPR, HIPAA)?:
This vulnerability allows any authenticated user to enumerate sensitive information such as API keys, endpoint configurations, and proprietary model definitions without proper authorization checks.
Exposure of such sensitive information could lead to non-compliance with data protection regulations like GDPR and HIPAA, which require strict access controls and protection of sensitive data.
Therefore, organizations using affected versions of MLflow may face compliance risks due to unauthorized disclosure of sensitive information.