Vulnerability Monitor

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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 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.


Security Impact Summary

This vulnerability carries a CRITICAL severity rating with a CVSS v3.1 score of 9.3, indicating it can be exploited remotely over the network with relatively low complexity without requiring user interaction and does not require pre-existing privileges . The vulnerability impacts confidentiality (data exposure), limited integrity, for affected systems. Impacting 1 product from lfprojects organizations running these solutions should prioritize assessment and patching.

Historical Context

Reported in 2026, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.


Published

2026-08-17T22:17:23.580

Last Modified

2026-08-20T19:16:57.867

Status

Analyzed

Source

[email protected]

Severity

CVSSv3.1: 9.3 (CRITICAL)

Weaknesses
  • Type: Secondary
    CWE-918

Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application lfprojects mlflow < 3.15.0 Yes

References

How SecUtils Interprets This CVE

SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For lfprojects's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.