2024-11-25
MLflow, an open-source platform for managing the machine learning lifecycle, has been found to have a high-severity vulnerability that could allow local privilege escalation. This vulnerability, tracked as CVE-2024-46998, arises from excessive directory permissions when using the `spark_udf()` API.
A local attacker could exploit this issue by employing a Time-of-Check-to-Time-of-Use (TOCTOU) attack to gain elevated privileges. This vulnerability is specifically tied to the use of the `spark_udf()` API and is not a general issue with MLflow.
Vulnerability
Platform: MLflow
Version: Affected versions are not explicitly specified.
Vulnerability: Excessive directory permissions
Severity: High
Date: November 25, 2024
What Undercode Says:
This vulnerability highlights a critical security issue within MLflow, a widely used platform for machine learning workflows. The potential for local privilege escalation, especially when exploited through a TOCTOU attack, poses a significant risk to systems utilizing MLflow.
It’s crucial for organizations leveraging MLflow to stay informed about this vulnerability and take immediate action to mitigate the risk. This might involve updating to the latest version of MLflow, which likely addresses this issue, or implementing specific security measures to limit the potential impact of such attacks.
Given the rising complexity of machine learning pipelines and the increasing reliance on open-source tools, it’s essential to prioritize security best practices. Regular security audits, vulnerability assessments, and staying updated with the latest security advisories are key to safeguarding machine learning environments.
References:
Reported By: Github.com
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