MLflow · MLflow
CVE-2026-64849
MLflow: Unauthenticated full-read SSRF in webhook delivery: _validate_webhook_url bypassed via unvalidated HTTP redirects (and DNS rebinding)
What it is
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.
CISA: MLflow contains a server-side request forgery vulnerability that can allow attackers to reach internal or cloud metadata services and receive response_status and response_body.
What to do
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.
Deadline for US federal agencies: September 2, 2026
- Added to the CISA list
- August 19, 2026
- Published
- August 17, 2026
- Severity
- Critical 9.3 CVSS 3.1
- Chance of attacks in the next 30 days (EPSS)
- 10% in the top 4.4% of all known vulnerabilities
- Weakness
- CWE-918
- More details
- NVD · CVE.org · CISA
All references (5)
Sources: Known Exploited Vulnerabilities (CISA, public domain), CVE records (cve.org) and EPSS (FIRST). The chance of attacks is the EPSS estimate that someone will try to exploit the flaw in the next 30 days.