Findings

CVE-2026-33865

MLflow is vulnerable to Stored Cross-Site Scripting (XSS) caused by unsafe parsing of YAML-based MLmodel artifacts in its web interface.

Published Apr 7, 2026 · updated Jun 17, 2026 · lfprojects mlflow

MLflow is vulnerable to Stored Cross-Site Scripting (XSS) caused by unsafe parsing of YAML-based MLmodel artifacts in its web interface. An authenticated attacker can upload a malicious MLmodel file containing a payload that executes when another user views the artifact in the UI. This allows actions such as session hijacking or performing operations on behalf of the victim. This issue affects MLflow version through 3.10.1

Code

The project this record applies to. Exploit listings stay in References.

Timeline

Detection, updates, and resolution for this record.

  1. Apr 7, 2026 · NIST NVD

    Detected

    MLflow is vulnerable to Stored Cross-Site Scripting (XSS) caused by unsafe parsing of YAML-based MLmodel artifacts in its web interface. An authenticated attacker can upload a malicious MLmodel file containing a payload that executes when another user views the artifact in the UI. This allows actions such as session hijacking or performing operations on behalf of the victim. This issue affects MLf

  2. Jun 17, 2026 · NIST NVD

    Updated

    MLflow is vulnerable to Stored Cross-Site Scripting (XSS) caused by unsafe parsing of YAML-based MLmodel artifacts in its web interface. An authenticated attacker can upload a malicious MLmodel file containing a payload that executes when another user views the artifact in the UI. This allows actions such as session hijacking or performing operations on behalf of the victim. This issue affects MLf

Affected

  • cpe lfprojects/mlflowversion unspecified

Sources

  • CVE.orgVulnerability recordCVE-2026-33865

    Official CVE identifier

    cve.org
  • NIST NVDVulnerability recordCVE-2026-33865

    MLflow is vulnerable to Stored Cross-Site Scripting (XSS) caused by unsafe parsing of YAML-based MLmodel artifacts in its web interface. An authenticated attacker can upload a malicious MLmodel file containing a payload that executes when another user views the artifact in the UI

    nvd.nist.gov

References

CVE-2026-33865 · ZeroDay Findings