CVE-2024-27133
CRITICAL9.6EPSS 0.20%Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.
Published: 2/24/2024Modified: 2/11/2026
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.
Affected packages (3)
- Bitnami/mlflowfrom 0, < 2.10.0
- PyPI/mlflowfrom 0, < 2.10.0
- PyPI/mlflowfrom 0, < 2.10.0
CVSS scores
| Source | Version | Severity | Vector |
|---|---|---|---|
| osv | CVSS 3.1 | CRITICAL9.6 | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H |
References (9)
- ADVISORYhttps://nvd.nist.gov/vuln/detail/CVE-2024-27133
- PATCHhttps://github.com/mlflow/mlflow
- WEBhttps://github.com/advisories/GHSA-3v79-q7ph-j75h
- WEBhttps://github.com/mlflow/mlflow/commit/c43823750bffa5b6abcc086683b15a068513b67b
- WEBhttps://github.com/mlflow/mlflow/commit/cfa71879a884cc3520e23ccab998c9aa78fdf2b1
- WEBhttps://github.com/mlflow/mlflow/pull/10893
- WEBhttps://github.com/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2024-241.yaml
- WEBhttps://research.jfrog.com/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932
- WEBhttps://research.jfrog.com/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932/