The Cybersecurity and Infrastructure Security Agency (CISA) warned federal agencies that threat actors are now exploiting a critical MLflow vulnerability.
MLflow is an open-source AI engineering platform for large language models (LLMs) and agents backed by the Linux Foundation, with over 30 million monthly downloads, used by thousands of organizations to debug, evaluate, optimize, and monitor AI applications.
Tracked as CVE-2026-64849, this critical DNS-rebinding server-side request forgery (SSRF) bypass in MLflow's outbound webhook delivery was patched in version 3.15.0 and can be used by attackers without privileges to remotely access internal services or cloud metadata configurations on unpatched instances.
"The default MLflow Tracking Server (mlflow server, no authentication, default SQLite backend) exposes the model-registry webhooks API unauthenticated, including a synchronous POST /api/2.0/mlflow/webhooks/{id}/test endpoint that returns the upstream response status and body to the caller," MLflow's security team says in a security advisory issued three weeks ago.
"An unauthenticated attacker who can reach the tracking server makes the server issue HTTP requests to arbitrary internal/loopback/cloud-metadata endpoints and reads the responses via /test: cloud instance-metadata (e.g. AWS IMDS IAM credentials), internal-only admin services behind the network boundary, and internal port/host scanning."
