MLflow Server-Side Request Forgery Vulnerability
mlflow — mlflow
MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Starting in 3.3.0 and 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.
9.3
16.4%
Vector breakdown
- Attack vector
- Network
- Attack complexity
- Low
- Privileges required
- None
- User interaction
- None
- Scope
- Changed
- Confidentiality
- High
- Integrity
- Low
- Availability
- None
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:L/A:N
- Published
- Aug 17, 2026
- Modified
- Oct 26, 2026
- Added to KEV
- Aug 19, 2026
- Federal patch due
- Sep 2, 2026
CISA 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.
Weakness classification
Affected packages
Proof-of-concept & exploitation references
Weaponization
Public repositories whose name or description references CVE-2026-64849, found via a live GitHub search at request time. These are community-sourced signals, not a verified working exploit — cross-check each one before relying on it, and treat higher star counts and recent activity as (weak) corroboration, not proof.
No public GitHub repositories referencing CVE-2026-64849 were found at last check. Absence here is not proof no exploit exists — see the references below for vendor advisories and write-ups.
References
How this class of flaw gets exploited
Frequently asked questions
What is CVE-2026-64849?
MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Starting in 3.3.0 and 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.
How severe is CVE-2026-64849?
CVE-2026-64849 has a CVSS base score of 9.3 out of 10 (CVSS 3.1).
Is CVE-2026-64849 actively exploited in the wild?
Yes. CVE-2026-64849 is listed in the CISA Known Exploited Vulnerabilities (KEV) catalog, added Aug 19, 2026, meaning CISA has confirmed evidence of active exploitation.
What is the EPSS score for CVE-2026-64849?
16.4% - meaning FIRST.org's EPSS model estimates a 16.4% probability this vulnerability will be exploited in the wild within 30 days (97% percentile among all scored CVEs).
Is there exploit tooling available for CVE-2026-64849?
Yes - a public Nuclei template referencing CVE-2026-64849 exist in public repositories we checked.
What type of vulnerability is CVE-2026-64849?
CVE-2026-64849 is classified under CWE-918 (CWE-918: Server-Side Request Forgery (SSRF)).
Cross-checked against
Impactr finds and proves whether CVE-2026-64849 — or flaws like it — are actually reachable in your own web apps and APIs, with a reproducible exploit as evidence.