CVE-2022-23585 : What You Need to Know

Tensorflow is an Open Source Machine Learning Framework. This vulnerability arises when decoding PNG images in TensorFlow, leading to a memory leak when the image is invalid. The issue occurs due to allocated buffers not being freed under certain error scenarios.

Understanding CVE-2022-23585

This section delves into the details of the CVE-2022-23585 vulnerability in TensorFlow.

What is CVE-2022-23585?

TensorFlow can produce a memory leak while decoding PNG images, as allocated buffers may not be freed under specific error conditions.

The Impact of CVE-2022-23585

The impact of this vulnerability is rated as MEDIUM with a CVSS base score of 4.3. It has low attack complexity and is triggered over a network.

Technical Details of CVE-2022-23585

Explore the technical aspects related to CVE-2022-23585 in TensorFlow.

Vulnerability Description

After calling certain functions during PNG image decoding in TensorFlow, allocated buffers are not freed in error cases, resulting in a memory leak.

Affected Systems and Versions

Versions prior to 2.5.3, between 2.6.0 and 2.6.3, and between 2.7.0 and 2.7.1 of TensorFlow are affected by this vulnerability.

Exploitation Mechanism

The vulnerability can be exploited when invalid PNG images are decoded in TensorFlow, leading to memory leaks.

Mitigation and Prevention

Take necessary actions to mitigate and prevent the CVE-2022-23585 vulnerability in TensorFlow.

Immediate Steps to Take

Users are advised to update TensorFlow to version 2.8.0 or apply the relevant patches in TensorFlow 2.7.1, 2.6.3, and 2.5.3 to address this issue.

Long-Term Security Practices

Adopt secure coding practices and perform regular code audits to prevent similar memory-related vulnerabilities in TensorFlow.

Patching and Updates

Stay updated with security advisories and promptly apply patches released by TensorFlow to secure systems against exploits.