CVE-2022-36026 Explained : Impact and Mitigation

TensorFlow is an open source platform for machine learning. The vulnerability CVE-2022-36026 affects TensorFlow versions prior to 2.7.2, between 2.8.0 to 2.8.1, and 2.9.0 to 2.9.1. The vulnerability arises from the

QuantizeAndDequantizeV3

function when given a nonscalar

num_bits

input tensor, leading to a

CHECK

fail that can be exploited for a denial of service attack.

Understanding CVE-2022-36026

This section provides an overview of the nature and impact of the vulnerability.

What is CVE-2022-36026?

The vulnerability in TensorFlow's

QuantizeAndDequantizeV3

function allows an attacker to trigger a denial of service attack by exploiting a

CHECK

fail scenario when given a specific input tensor.

The Impact of CVE-2022-36026

With a CVSSv3.1 base score of 5.9 (medium severity), this vulnerability has a high attack complexity and can impact the availability of affected systems without requiring any special privileges or user interaction. While the confidentiality and integrity remain unaffected, the availability of the system is at high risk.

Technical Details of CVE-2022-36026

This section delves into the technical specifics of the vulnerability.

Vulnerability Description

The issue stems from the incorrect handling of input tensors in the

QuantizeAndDequantizeV3

function, leading to a

CHECK

fail condition that can be weaponized for a denial of service attack.

Affected Systems and Versions

TensorFlow versions prior to 2.7.2, between 2.8.0 to 2.8.1, and 2.9.0 to 2.9.1 are affected by this vulnerability.

Exploitation Mechanism

By providing a nonscalar

num_bits

input tensor to the

QuantizeAndDequantizeV3

function, an attacker can trigger the

CHECK

fail, resulting in a denial of service attack.

Mitigation and Prevention

This section outlines steps to mitigate the vulnerability and prevent exploitation.

Immediate Steps to Take

Users and administrators are advised to update TensorFlow to version 2.10.0, which includes the patch for this vulnerability. For those using versions 2.9.1, 2.8.1, and 2.7.2, the patched commit has been cherrypicked to address the issue.

Long-Term Security Practices

Maintaining up-to-date software versions and promptly apply security patches to prevent potential vulnerabilities.

Patching and Updates

Regularly check for security advisories and updates from the TensorFlow project to stay informed about patches and fixes.