CVE-2022-23563 : Security Advisory and Response

Tensorflow, an Open Source Machine Learning Framework, was found to have an insecure temporary file vulnerability. The issue stemmed from the improper usage of

tempfile.mktemp

to create temporary files, leading to a TOCTOU race condition. This vulnerability has been assigned a CVSS base score of 7.1 (High Severity).

Understanding CVE-2022-23563

This section provides insights into the nature of the vulnerability and its potential impact.

What is CVE-2022-23563?

The vulnerability in Tensorflow arises from the mishandling of temporary files using

tempfile.mktemp

, which could result in a race condition exploit.

The Impact of CVE-2022-23563

The vulnerability poses a significant risk to the confidentiality and integrity of affected systems, with a CVSS base score of 7.1 (High Severity).

Technical Details of CVE-2022-23563

In this section, we delve into the specifics of the vulnerability, including affected systems and mitigation measures.

Vulnerability Description

Tensorflow's improper use of

tempfile.mktemp

allows for the creation of temporary files in an insecure manner, potentially leading to file creation race conditions.

Affected Systems and Versions

The vulnerability impacts Tensorflow versions >= 2.7.0 and < 2.7.1, >= 2.6.0 and < 2.6.3, as well as versions below 2.5.3.

Exploitation Mechanism

Attackers could exploit the vulnerability by manipulating temporary files created by Tensorflow, leading to unauthorized access and potential data compromise.

Mitigation and Prevention

This section outlines the steps to mitigate the impact of CVE-2022-23563 and prevent future vulnerabilities.

Immediate Steps to Take

Users are strongly advised to upgrade to patched versions of Tensorflow that have replaced

mktemp

with safer functions like

mkstemp

/

mkdtemp

.

Long-Term Security Practices

Implement secure coding practices, regular security audits, and stay informed about potential security advisories related to Tensorflow.

Patching and Updates

Regularly check for security updates from Tensorflow and apply patches promptly to address known vulnerabilities.