CVE-2022-23557 : Vulnerability Insights and Analysis

Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would trigger a division by zero in

BiasAndClamp

implementation. The fix will be included in TensorFlow 2.8.0, with cherry-picked commits for TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3.

Understanding CVE-2022-23557

This CVE highlights a vulnerability in TFLite allowing attackers to trigger a division by zero, affecting multiple versions of TensorFlow.

What is CVE-2022-23557?

The CVE-2022-23557 addresses a specific vulnerability in TensorFlow where a crafted TFLite model can cause a division by zero in the

BiasAndClamp

implementation.

The Impact of CVE-2022-23557

With a CVSS base score of 6.5 (Medium severity), this vulnerability has a low attack complexity but high impact on availability. An attacker with low privileges can exploit it over the network, leading to a denial of service.

Technical Details of CVE-2022-23557

This section dives into the vulnerability description, affected systems, versions, and exploitation mechanism.

Vulnerability Description

The vulnerability arises from the lack of a check for the

bias_size

being non-zero, allowing malicious actors to trigger a division by zero.

Affected Systems and Versions

TensorFlow versions >= 2.7.0, < 2.7.1
TensorFlow versions >= 2.6.0, < 2.6.3
TensorFlow versions < 2.5.3

Exploitation Mechanism

An attacker can exploit this vulnerability by crafting a TFLite model to trigger the division by zero in the

BiasAndClamp

implementation.

Mitigation and Prevention

Here are steps to mitigate and prevent exploitation of CVE-2022-23557.

Immediate Steps to Take

It is recommended to update to TensorFlow 2.8.0 when the fix is released. For versions still in the supported range, apply the cherry-picked commits for TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3.

Long-Term Security Practices

Ensure regular security updates for TensorFlow and implement secure coding practices to prevent such vulnerabilities.

Patching and Updates

Stay vigilant for security advisories from TensorFlow and promptly apply patches and updates to secure your systems.