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CISA warns of hackers exploiting critical MLflow vulnerability

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Why This Matters

The recent exploitation of a critical MLflow vulnerability highlights the urgent need for organizations to update their AI infrastructure to prevent unauthorized access and data breaches. As MLflow is widely used in AI development, unpatched instances pose significant security risks, including theft of cloud credentials and internal data. This underscores the importance of proactive cybersecurity measures in safeguarding AI tools and sensitive information in the tech industry and beyond.

Key Takeaways

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."

Successful exploitation can allow threat actors to steal cloud credentials, such as AWS Identity and Access Management (IAM) credentials, in low-complexity attacks.

Tagged as exploited in attacks

On Wednesday, CISA added the vulnerability to its catalog of flaws exploited in the wild and ordered U.S. Federal Civilian Executive Branch (FCEB) agencies to secure their MLflow instances within two weeks as mandated by Binding Operational Directive 26-04.

BOD 26-04 was issued in June, and it requires U.S. government agencies to prioritize patching if the vulnerable assets are publicly exposed online, if the security flaw was added to CISA's KEV catalog, if exploitation can be automated for large-scale attacks, and if successful exploitation gives attackers partial or total control of a targeted system.

While BOD 26-04 applies only to U.S. government agencies, CISA urged all network defenders to prioritize patching their systems against attacks targeting CVE-2026-64849.

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