CVE-2023-25801 Explained : Impact and Mitigation

This CVE-2023-25801 relates to a vulnerability in TensorFlow regarding a double-free issue in Fractional(Max/Avg) Pool feature.

Understanding CVE-2023-25801

This vulnerability affects TensorFlow, an open-source machine learning platform. The issue arises in versions prior to 2.12.0 and 2.11.1, specifically in the

nn_ops.fractional_avg_pool_v2

and

nn_ops.fractional_max_pool_v2

functions due to the requirement of specific elements in the

pooling_ratio

parameter.

What is CVE-2023-25801?

The vulnerability stems from the necessity for the first and fourth elements of the

pooling_ratio

parameter to be set to 1.0 in the mentioned TensorFlow functions. Failure to meet this requirement can lead to a double-free situation, impacting system security.

The Impact of CVE-2023-25801

The impact of this vulnerability is rated as high severity based on the CVSS v3.1 metrics. It has a base score of 8 out of 10, indicating a critical issue that could result in compromised data integrity and availability.

Technical Details of CVE-2023-25801

In TensorFlow versions earlier than 2.11.1, the

nn_ops.fractional_avg_pool_v2

and

nn_ops.fractional_max_pool_v2

functions lack support for pool operations on batch and channel dimensions if the first and fourth elements of the

pooling_ratio

parameter are not set to 1.0.

Vulnerability Description

The vulnerability in TensorFlow allows for a double-free scenario due to improper handling of the

pooling_ratio

parameter in the mentioned functions, leading to potential exploitation risks.

Affected Systems and Versions

The vulnerability affects TensorFlow versions prior to 2.11.1, making systems running these versions susceptible to the double-free issue in Fractional(Max/Avg) Pool operations.

Exploitation Mechanism

Attackers can exploit this vulnerability by manipulating the

pooling_ratio

parameter in a way that triggers the double-free condition, potentially causing system instability and unauthorized access.

Mitigation and Prevention

To address CVE-2023-25801 and enhance system security, follow these mitigation strategies:

Immediate Steps to Take

Upgrade TensorFlow to version 2.12.0 or 2.11.1, where the fix for this vulnerability is included.
Implement access controls to restrict unauthorized interactions with vulnerable functions.

Long-Term Security Practices

Regularly monitor security advisories from TensorFlow and apply updates promptly to mitigate emerging threats.
Conduct routine security audits to identify and rectify potential vulnerabilities in machine learning applications.

Patching and Updates

Ensure timely patching and updating of TensorFlow to the latest secure versions to prevent exploitation of known vulnerabilities, including those related to the double-free issue in Fractional(Max/Avg) Pool functionality.