CVE-2024-27132: Insufficient sanitization in MLflow leads to XSS when running an untrusted recipe.
First published: Fri Feb 23 2024(Updated: )
Insufficient sanitization in MLflow leads to XSS when running an untrusted recipe. This issue leads to a client-side RCE when running an untrusted recipe in Jupyter Notebook. The vulnerability stems from lack of sanitization over template variables.
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://research.jfrog.com/vulnerabilities/mlflow-untrusted-recipe-xss-jfsa-2024-000631930/
- https://github.com/mlflow/mlflow/pull/10873
- https://nvd.nist.gov/vuln/detail/CVE-2024-27132
- https://research.jfrog.com/vulnerabilities/mlflow-untrusted-recipe-xss-jfsa-2024-000631930
- https://github.com/advisories/GHSA-6749-m5cp-6cg7 (Advisory)
Frequently Asked Questions
What is the severity of CVE-2024-27132?
CVE-2024-27132 has been classified as a high severity vulnerability due to the potential for client-side remote code execution.
How do I fix CVE-2024-27132?
To mitigate CVE-2024-27132, upgrade to MLflow version 2.10.0 or later.
Which versions of MLflow are affected by CVE-2024-27132?
CVE-2024-27132 affects MLflow versions prior to 2.10.0 and including up to 2.9.2.
What type of vulnerability is CVE-2024-27132?
CVE-2024-27132 is an insufficient sanitization vulnerability that can lead to cross-site scripting (XSS) attacks.
In what scenario does CVE-2024-27132 pose a risk?
CVE-2024-27132 poses a risk when executing untrusted recipes in a Jupyter Notebook environment.
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