CVE-2023-25660 : What You Need to Know

This CVE record highlights a vulnerability in TensorFlow that is tracked as CVE-2023-25660. It involves a segmentation fault in the

tf.raw_ops.Print

function, making the platform susceptible to exploitation.

Understanding CVE-2023-25660

This section provides insights into the nature and impact of CVE-2023-25660 within the TensorFlow platform.

What is CVE-2023-25660?

The vulnerability identified as CVE-2023-25660 affects TensorFlow, an open-source platform utilized for machine learning tasks. Specifically, versions prior to 2.12.0 and 2.11.1 are at risk. The issue arises when the

summarize

parameter of

tf.raw_ops.Print

is set to zero, causing the new method

SummarizeArray<bool>

to reference a nullptr. This referencing to a null pointer results in a segmentation fault within the application.

The Impact of CVE-2023-25660

The impact of this vulnerability is categorized as high, with a CVSS v3.1 base score of 7.5. The attack complexity is rated as low, and the attack vector is through the network, making the availability impact high. While there is no impact on confidentiality or integrity, the exploit can occur without the need for user interaction or elevated privileges.

Technical Details of CVE-2023-25660

Understanding the technical aspects of CVE-2023-25660 aids in comprehending its implications and potential risks for affected systems.

Vulnerability Description

The vulnerability stems from a NULL pointer dereference issue (CWE-476) within TensorFlow, triggered by specific configurations in the

tf.raw_ops.Print

function. This flaw allows attackers to cause a segmentation fault, potentially leading to denial of service or arbitrary code execution.

Affected Systems and Versions

The vulnerability impacts versions of TensorFlow that are earlier than 2.1.1, leaving them vulnerable to exploitation. Users of these affected versions are at risk of encountering the segmentation fault triggered by the

tf.raw_ops.Print

function under specific conditions.

Exploitation Mechanism

Exploiting CVE-2023-25660 involves manipulating the

summarize

parameter of

tf.raw_ops.Print

to set it to zero. By triggering this configuration, attackers can force the referencing of a nullptr within the

SummarizeArray<bool>

method, resulting in a segmentation fault and potential system compromise.

Mitigation and Prevention

Taking proactive measures to mitigate the impact of CVE-2023-25660 is crucial for maintaining the security of TensorFlow deployments.

Immediate Steps to Take

Users and administrators should update their TensorFlow installations to versions 2.12.0 or 2.11.1, which include a fix for the vulnerability. Applying patches promptly can eliminate the risk of exploitation and prevent potential security incidents.

Long-Term Security Practices

In the long term, organizations should prioritize regular software updates and security monitoring to address vulnerabilities promptly. Implementing secure coding practices and conducting thorough testing can help prevent similar issues from arising in the future.

Patching and Updates

Staying vigilant about security advisories from TensorFlow and promptly applying patches are essential steps to protect systems from known vulnerabilities. Regularly monitoring for updates and maintaining up-to-date software versions can enhance the overall security posture of TensorFlow deployments.