CVE-2022-23583 : Security Advisory and Response

A detailed analysis of the

CHECK

-failures vulnerability in binary operations in TensorFlow.

Understanding CVE-2022-23583

In this section, we will delve into what CVE-2022-23583 entails.

What is CVE-2022-23583?

Tensorflow, an Open Source Machine Learning Framework, is susceptible to a denial of service due to manipulation of a

SavedModel

triggering

CHECK

failures in binary operations.

The Impact of CVE-2022-23583

The vulnerability allows a malicious actor to disrupt services by corrupting data, potentially resulting in a denial of service scenario. In some cases, this may lead to a

CHECK

crash.

Technical Details of CVE-2022-23583

This section will cover the technical aspects of CVE-2022-23583.

Vulnerability Description

By modifying the protobuf part related to tensor arguments, causing a mismatch in data types expected by the operation, the binary operator can receive corrupted data, leading to a type confusion vulnerability.

Affected Systems and Versions

Tensorflow versions >= 2.7.0 and < 2.7.1, >= 2.6.0 and < 2.6.3, and < 2.5.3 are impacted by this vulnerability.

Exploitation Mechanism

The issue arises when

Tin

and

Tout

types do not match the data type in

out

and

input_*

tensors, confusing

flat<*>

interpretation.

Mitigation and Prevention

Here we discuss how to mitigate the risks associated with CVE-2022-23583.

Immediate Steps to Take

It is crucial to update affected versions of TensorFlow to 2.7.1, 2.6.3, or install the fix included in TensorFlow 2.8.0 to address the vulnerability.

Long-Term Security Practices

Implement secure coding practices, perform regular code reviews, and stay informed about security updates in TensorFlow.

Patching and Updates

Regularly check for patches and updates from the TensorFlow team to ensure your system is protected against known vulnerabilities.