MLflow versions prior to 3.15.0 contain a server-side request forgery flaw (CWE-918) in the unauthenticated POST /api/2.0/mlflow/webhooks/{id}/test endpoint. The webhook URL is validated only for the original request, but delivery follows redirects and re-resolves the hostname without pinning the validated address, letting an attacker redirect server-side requests to internal network services or cloud instance metadata endpoints. Because the endpoint returns response_status and response_body, attackers can read internal service responses and, per public reporting, steal cloud credentials and secrets from metadata services. Any self-hosted MLflow deployment is affected, with internet-exposed servers at the highest risk. Exploitation is confirmed in the wild: CISA added the flaw to its Known Exploited Vulnerabilities catalog on 2026-08-19, and headlines report active attacks stealing cloud credentials; EPSS puts 30-day exploitation probability at 16.4% (97th percentile).
What to do: Upgrade to MLflow 3.15.0 or later immediately, prioritizing any MLflow server reachable from the internet. Until patched, restrict network access to MLflow (especially the /api/2.0/mlflow/webhooks/{id}/test endpoint), place it behind authentication or a reverse proxy, and review webhook logs for unexpected test requests and cloud metadata endpoint access; rotate cloud credentials and secrets if compromise indicators are found. Federal agencies must apply vendor mitigations in accordance with CISA BOD 26-04 guidance or discontinue use if mitigations are unavailable.
Affected
lfprojects MLflow
All versions prior to 3.15.0 (fixed in 3.15.0)
Estimated exposure
moderatelikely thousands of internet-exposed MLflow servers, from a substantially larger installed base (estimate) — No install-base or public-scan counts were supplied in the data, so this is an estimate based on MLflow's popularity as a self-hosted open-source AI/ML platform, where public scans typically show thousands of exposed servers and many…
Order-of-magnitude estimate by the model from install counts, market share and public scan data it knows; verify before quoting.
Description
MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. 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 Known Exploited Vulnerability
Affected
MLflow MLflow
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.
CISA added actively exploited MLflow SSRF flaw CVE-2026-64849 (CVSS 9.3) to its KEV catalog; attackers are stealing cloud credentials from exposed instances.
CISA added CVE-2026-64849, a critical unauthenticated server-side request forgery in MLflow, to its Known Exploited Vulnerabilities catalog. The flaw affects MLflow versions before 3.15.0 and allows unauthenticated attackers to reach internal services including cloud metadata endpoints, exposing temporary cloud credentials. watchTowr observed in-the-wild exploitation exfiltrating credentials and secrets, plus widespread scanning of exposed MLflow instances within hours of the CVE's assignment on August 17, 2026. MLflow is an open-source platform for managing the machine learning and AI development lifecycle with over 60 million monthly downloads.
Attackers exploit MLflow SSRF CVE-2026-64849 (CVSS 9.3) to steal cloud credentials; CISA added it to KEV; FUXA flaw CVE-2026-25895 is being scanned.
watchTowr observed exploitation of MLflow CVE-2026-64849, an unauthenticated SSRF (CVSS 9.3) affecting versions below 3.15.0, within hours of CVE assignment on August 17, 2026, with attackers abusing model-registry webhooks to reach cloud metadata endpoints and exfiltrate credentials and secrets. CISA added the flaw to its Known Exploited Vulnerabilities catalog on August 19, 2026, with a September 2 patch deadline for federal civilian agencies. VulnCheck reported scanning of FUXA CVE-2026-25895 (missing authentication plus path traversal, CVSS 9.5, versions through 1.2.9) beginning August 18; about 60 FUXA instances are exposed and no RCE payloads have been dropped yet.