| Component | MLflow |
| Severity | high (CVSS 7.5) |
| CVSS vector | CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H |
| Published (NVD) | 2024-02-23 |
| Last modified | 2026-06-17 |
| Affected versions | mlflow <= 2.9.2 |
| Fixed in | see the vendor advisory |
| Weakness | CWE-79 |
| CISA KEV | not listed |
NVD description
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset. This issue leads to a client-side RCE when running the recipe in Jupyter Notebook. The vulnerability stems from lack of sanitization over dataset table fields.
What to do
- NVD lists no fixed version yet: follow the vendor advisory below and keep MLflow off the public internet until a fix ships.
- Do not expose the component's API or UI to the internet without authentication in front of it.
Sources
- NVD: CVE-2024-27133
- https://github.com/mlflow/mlflow/pull/10893
- https://research.jfrog.com/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932/
Read more
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