CVE-2022-23588 : Security Advisory and Response

A detailed article outlining the CVE-2022-23588 vulnerability in TensorFlow, impacting versions 2.5.3 to 2.7.0.

Understanding CVE-2022-23588

This CVE pertains to

CHECK

-fails in TensorFlow due to attempting to build a reference tensor, leading to a denial of service vulnerability.

What is CVE-2022-23588?

TensorFlow, an Open Source Machine Learning Framework, is affected by a vulnerability that allows a malicious user to cause a denial of service by manipulating a

SavedModel

to build a tensor using a reference

dtype

. This manipulation results in a crash due to a

CHECK

-fail in the

Tensor

constructor.

The Impact of CVE-2022-23588

The impact of this vulnerability is rated as MEDIUM severity with a CVSS base score of 6.5. It has a low attack complexity and vector of NETWORK, with high availability impact.

Technical Details of CVE-2022-23588

This section covers the vulnerability description, affected systems and versions, as well as the exploitation mechanism.

Vulnerability Description

The vulnerability arises from the Grappler optimizer attempting to construct a tensor using a reference

dtype

, triggering a

CHECK

-fail in the

Tensor

constructor.

Affected Systems and Versions

Versions of TensorFlow ranging from 2.5.3 to 2.7.0 are impacted by this vulnerability, including versions 2.7.1, 2.6.3, and 2.5.3.

Exploitation Mechanism

A malicious user can exploit this vulnerability by modifying a

SavedModel

to utilize a reference

dtype

, leading to a crash in the

Tensor

constructor.

Mitigation and Prevention

Outlined below are immediate steps to take and long-term security practices to mitigate the risks associated with CVE-2022-23588.

Immediate Steps to Take

Upgrade TensorFlow to version 2.8.0 to apply the fix for this vulnerability.
Patch TensorFlow versions 2.7.1, 2.6.3, and 2.5.3 if upgrading to version 2.8.0 is not feasible.

Long-Term Security Practices

Regularly update TensorFlow and other software components to the latest versions to address security vulnerabilities promptly.
Monitor security advisories from TensorFlow and other sources for any new vulnerabilities.

Patching and Updates

Apply patches provided by TensorFlow for versions 2.7.1, 2.6.3, and 2.5.3 to address the vulnerability and enhance the security of the software.