MLflow Vulnerability Exploited for Cloud Credential Theft

A critical Server-Side Request Forgery (SSRF) vulnerability in MLflow's unauthenticated webhooks API allowed attackers to pivot through the ML platform to extract cloud credentials and secrets without any authentication required. The root failure is twofold: a sensitive API endpoint was left exposed without authentication controls, and organizations failed to apply patches before active exploitation began. This matters because MLflow instances are commonly deployed in cloud environments with broad IAM permissions, meaning credential theft can rapidly escalate to full cloud account compromise. CISA's addition of this CVE to the Known Exploited Vulnerabilities catalog signals that this is not a theoretical risk — real-world attacks are already underway.