CVE-2024-27132: Insufficient sanitization in MLflow leads to XSS when running an untrusted recipe.

Published 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.

Affected Software

2 affected componentsFixes available
Lfprojects Mlflow<=2.9.2
pip/mlflow<2.10.0
2.10.0

Remediation

Recommended actions to resolve this vulnerability, in priority order.

  1. Upgrade

    Upgrade pip/mlflow to a version that resolves this vulnerability.

    Fixed in 2.10.0

Event History

Feb 23, 2024
CVE Published
via MITRE·09:58 PM
Data Sourced
via MITRE·09:58 PM
DescriptionSeverityWeakness
Data Sourced
via NVD·10:15 PM
RemedyDescriptionSeverityWeaknessAffected Software
Feb 24, 2024
Advisory Published
via GitHub·12:30 AM
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Frequently Asked Questions

1

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.

2

How do I fix CVE-2024-27132?

To mitigate CVE-2024-27132, upgrade to MLflow version 2.10.0 or later.

3

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.

4

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.

5

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.

Contact

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