CyberRota Analysis
AI-GeneratedThe vulnerability affects MLflow versions prior to 3.15.0, specifically through the unauthenticated POST /api/2.0/mlflow/webhooks/{id}/test endpoint, which improperly handles URL validation. This flaw allows attackers to exploit the system by reaching internal or cloud metadata services, potentially exposing sensitive response data. Organizations using MLflow for AI and machine learning should prioritize upgrading to version 3.15.0 to mitigate this critical risk.
Public Exploit Signal
A public exploit, PoC, GitHub repository or Metasploit reference was detected for this CVE.
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CISA KEV Details
Status: This CVE is listed in CISA's Known Exploited Vulnerabilities catalog.
Ransomware use: Unknown
Added to KEV: 2026-08-19
Required action: Apply mitigations in accordance with vendor instructions, ensuring compliance with CISA’s BOD 26-04 Prioritizing Security Updates Based on Risk (see URL in Notes) guidance and CISA’s “Forensics Triage Requirements” (see URL in Notes). Follow applicable BOD 26-04 guidance for cloud services or discontinue use of the product if mitigations are unavailable. Stakeholders are responsible for evaluating each asset's internet exposure and ensuring adherence to BOD 26-04 patching guidelines.
Original NVD 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.
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