CVE-2023-25667 : Vulnerability Insights and Analysis

This CVE involves TensorFlow being vulnerable to a segfault when opening a multiframe gif due to an integer overflow issue.

Understanding CVE-2023-25667

This section provides insight into what CVE-2023-25667 is all about, including its impact and technical details.

What is CVE-2023-25667?

CVE-2023-25667 is a vulnerability in TensorFlow, an open-source platform for machine learning. The issue occurs in versions prior to 2.12.0 and 2.11.1, where an integer overflow occurs under specific conditions, leading to a segfault when opening multiframe gifs.

The Impact of CVE-2023-25667

The impact of this vulnerability is rated as medium severity with a CVSS base score of 6.5. It has a high impact on availability but does not affect confidentiality or integrity. The attack complexity is low, and user interaction is required for exploitation.

Technical Details of CVE-2023-25667

In this section, we delve into the specific technical details of the vulnerability, including the description, affected systems and versions, and the exploitation mechanism.

Vulnerability Description

The vulnerability arises when

2^31 <= num_frames * height * width * channels < 2^32

, such as in the case of a Full HD screencast with a minimum of 346 frames. This triggers an integer overflow, leading to a segfault when processing multiframe gifs.

Affected Systems and Versions

The vulnerability impacts TensorFlow versions prior to 2.12.0 and 2.11.1. Systems running these versions are susceptible to the integer overflow issue when handling multiframe gifs.

Exploitation Mechanism

Exploiting this vulnerability requires network access and user interaction. By providing a specially crafted multiframe gif file, an attacker could trigger the integer overflow and potentially cause a segfault in TensorFlow.

Mitigation and Prevention

To protect systems from CVE-2023-25667, it is crucial to implement immediate steps, establish long-term security practices, and ensure timely patching and updates.

Immediate Steps to Take

Update TensorFlow to version 2.12.0 or 2.11.1, which includes a fix for the integer overflow vulnerability.
Avoid opening suspicious or untrusted multiframe gif files to mitigate the risk of exploitation.

Long-Term Security Practices

Regularly update software and libraries to stay protected against known vulnerabilities.
Implement network security measures to control access and prevent unauthorized exploitation.

Patching and Updates

TensorFlow users are advised to promptly apply the available patches provided in versions 2.12.0 and 2.11.1 to address the integer overflow vulnerability and prevent potential segfaults when handling multiframe gif files.