CVE-2026-33865

[CVE catalog]

Severity

Medium · CVSS 5.1

Published

Apr 7, 2026, 12:57:38 PM UTC

Source

[NVD] · [CVE record]

EPSS

0.22% · Oct 25, 2026

A flaw was found in MLflow, a platform for managing the machine learning lifecycle. This Stored Cross-Site Scripting (XSS) vulnerability, a type of injection where malicious scripts are injected into trusted websites, is caused by the unsafe parsing of YAML-based MLmodel artifacts in its web interface. An authenticated attacker can exploit this by uploading a malicious MLmodel file containing a payload. When another user views this artifact in the user interface, the payload executes, potentially leading to session hijacking or unauthorized operations on behalf of the victim. MLflow: MLflow: Stored Cross-Site Scripting (XSS) via unsafe parsing of MLmodel artifacts Moderate: This Stored Cross-Site Scripting (XSS) flaw in MLflow, as deployed in Red Hat OpenShift AI, stems from insecure parsing of YAML-based MLmodel artifacts in its web interface. An authenticated attacker can upload a malicious MLmodel file; subsequent viewing by another user executes the payload, potentially leading to session hijacking or unauthorized actions within the victim's session. The CVSS score(s) listed for this vulnerability do not reflect the associated product's status, and are included for informational purposes to better understand the severity of this vulnerability.