CRITICAL · 9.3

CVE-2026-64849

MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, the unauthenticated POST /api/2.0/mlflow/webhooks/{id}/test endpoint c...

Vulnerability Description

MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, the unauthenticated POST /api/2.0/mlflow/webhooks/{id}/test endpoint calls _validate_webhook_url() in mlflow/utils/validation.py only for the original URL while mlflow/webhooks/delivery.py follows redirects and re-resolves the hostname without pinning the validated address, allowing attackers to reach internal or cloud metadata services and receive response_status and response_body. This issue is fixed in version 3.15.0.

CVSS Score

9.3

CRITICAL

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:L/A:N
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
NONE
User Interaction
NONE
Scope
CHANGED
Confidentiality
HIGH
Integrity
LOW
Availability
NONE

Affected Products

VendorProductVersions
LfprojectsMlflow< 3.15.0

Related Weaknesses (CWE)

References

FAQ

What is CVE-2026-64849?

CVE-2026-64849 is a vulnerability with a CVSS score of 9.3 (CRITICAL). MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, the unauthenticated POST /api/2.0/mlflow/webhooks/{id}/test endpoint c...

How severe is CVE-2026-64849?

CVE-2026-64849 has been rated CRITICAL with a CVSS base score of 9.3/10. This is considered a critical vulnerability requiring immediate attention.

Is there a patch for CVE-2026-64849?

Check the references section above for vendor advisories and patch information. Affected products include: Lfprojects Mlflow.