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OpenAdvisories
Critical · 9.3 Known exploited Scanner template Public exploit CVE-2026-64849 BIT-mlflow-2026-64849EUVD-2026-60473GHSA-7gwp-5pfp-969jPYSEC-2026-3687

MLflow: Unauthenticated full-read SSRF in webhook delivery: _validate_webhook_url bypassed via unvalidated HTTP redirects (and DNS rebinding)

Published Aug 17, 2026 · Updated Oct 2, 2026 · Assigned by GitHub_M

Vendor: MLflow Product: MLflow Package: mlflow Ecosystem: PyPI

Description

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.

Affected products

VendorProductAffectedFixed
mlflow mlflow >= 3.3.0, < 3.15.0 —

Public exploits

Exploit or proof-of-concept code for this vulnerability is publicly available, which lowers the bar for attackers. Treat it as a reason to patch sooner.

Third-party code, not reviewed by us. Public PoCs are sometimes fake or contain malware. Read the code first and run it only in an isolated lab, against systems you are authorised to test.

GitHub 5 repositories

Sources: PoC-in-GitHub, Metasploit Framework, Exploit-DB — updated daily. Only links are listed; no exploit code is hosted here.

Automated scanner template

A ready-made Nuclei template detects this vulnerability automatically. Vulnerabilities with public scanner templates are typically probed across the internet soon after the template appears — exposed systems should be patched first.

Source: projectdiscovery/nuclei-templates (MIT) — updated daily. Only links are listed.

Affected packages

EcosystemPackageAffectedFixedRecord
PyPI mlflow >= 3.3.0, < 3.15.0 3.15.0 GHSA-7gwp-5pfp-969j
PyPI mlflow < 3.15.0 3.15.0 PYSEC-2026-3687

Advisories 3

References