CVE-2024-27133: Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.
First published: Fri Feb 23 2024(Updated: )
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.
Credit: reefs@jfrog.com reefs@jfrog.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| pip/mlflow | <2.10.0 | 2.10.0 |
| MLflow | <=2.9.2 |
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Reference Links
- https://github.com/mlflow/mlflow/pull/10893
- https://research.jfrog.com/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932/
- https://nvd.nist.gov/vuln/detail/CVE-2024-27133
- https://research.jfrog.com/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932
- https://github.com/mlflow/mlflow/commit/c43823750bffa5b6abcc086683b15a068513b67b
- https://github.com/advisories/GHSA-3v79-q7ph-j75h (Advisory)
- https://github.com/mlflow/mlflow/commit/cfa71879a884cc3520e23ccab998c9aa78fdf2b1
Frequently Asked Questions
What is the severity of CVE-2024-27133?
CVE-2024-27133 has a severity rating that indicates a significant risk due to its potential for client-side remote code execution.
How do I fix CVE-2024-27133?
To fix CVE-2024-27133, you should upgrade MLflow to version 2.10.0 or higher.
What causes CVE-2024-27133?
CVE-2024-27133 is caused by insufficient sanitization of dataset table fields in MLflow, which allows for cross-site scripting (XSS).
Who is affected by CVE-2024-27133?
Users of MLflow versions prior to 2.10.0, as well as those using affected CPE configurations, are at risk from CVE-2024-27133.
Can CVE-2024-27133 be exploited in Jupyter Notebook?
Yes, CVE-2024-27133 can be exploited in Jupyter Notebook when running recipes that utilize untrusted datasets.
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