CVE-2024-27133: Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.
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 Software
Remediation
Recommended actions to resolve this vulnerability, in priority order.
- Upgrade
Upgrade
pip/mlflowto a version that resolves this vulnerability.Fixed in 2.10.0
Event History
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.