CVE-2022-35967 : Vulnerability Insights and Analysis

TensorFlow, an open-source machine learning platform, is impacted by a vulnerability in

QuantizedAdd

that could lead to a denial of service attack. Learn more about the impact, description, affected systems, and mitigation steps.

Understanding CVE-2022-35967

This CVE discloses a vulnerability in TensorFlow related to the

QuantizedAdd

function that could result in a denial of service attack due to a segmentation fault.

What is CVE-2022-35967?

The CVE highlights an issue in TensorFlow where providing

min_input

or

max_input

tensors of a nonzero rank to the

QuantizedAdd

function causes a segfault, which can be exploited for a DoS attack.

The Impact of CVE-2022-35967

The vulnerability's CVSS base score is 5.9, indicating a medium severity issue with a high impact on availability. However, it does not affect confidentiality or integrity and requires no special privileges for exploitation.

Technical Details of CVE-2022-35967

This section covers the specific technical aspects of the CVE, including the vulnerability description, affected systems and versions, and the exploitation mechanism.

Vulnerability Description

The vulnerability in TensorFlow arises when certain inputs are provided to the

QuantizedAdd

function, leading to a segfault that could be leveraged for a denial of service attack.

Affected Systems and Versions

The affected versions of TensorFlow include < 2.7.2, >= 2.8.0 and < 2.8.1, and >= 2.9.0 and < 2.9.1. Users on these versions are at risk of exploitation.

Exploitation Mechanism

The vulnerability can be exploited by providing specific input data to the

QuantizedAdd

function, triggering a segfault and potentially disrupting the service.

Mitigation and Prevention

This section outlines the necessary steps to mitigate the risks posed by CVE-2022-35967 and prevent potential exploitation.

Immediate Steps to Take

Users are advised to update their TensorFlow installations to version 2.10.0 or apply the specific patch commit - 49b3824d83af706df0ad07e4e677d88659756d89. For those on affected versions 2.7.2, 2.8.1, and 2.9.1, the commit will also be backported.

Long-Term Security Practices

To enhance security posture, it is recommended to follow secure coding practices, regularly update software components, and stay informed about security advisories.

Patching and Updates

Stay informed about security releases from the TensorFlow project and promptly apply patches and updates to ensure your system is protected against known vulnerabilities.