CVE-2020-26267 : Vulnerability Insights and Analysis

In affected versions of TensorFlow, the tf.raw_ops.DataFormatVecPermute API lacks validation for src_format and dst_format attributes, potentially leading to memory access issues and crashes. This CVE has a CVSS base score of 4.4.

Understanding CVE-2020-26267

This CVE highlights a vulnerability in TensorFlow related to data format attribute validation.

What is CVE-2020-26267?

In TensorFlow versions with the vulnerability, improper validation of data format attributes can result in memory access errors and crashes.

The Impact of CVE-2020-26267

The lack of validation in data format attributes in TensorFlow can lead to uninitialized memory accesses, out-of-bounds reads, and potential system crashes.

Technical Details of CVE-2020-26267

This section provides more technical insights into the vulnerability.

Vulnerability Description

The tf.raw_ops.DataFormatVecPermute API in affected TensorFlow versions does not properly validate src_format and dst_format attributes, potentially causing memory access issues.

Affected Systems and Versions

TensorFlow versions < 1.15.5
TensorFlow versions >= 2.0.0, < 2.0.4
TensorFlow versions >= 2.1.0, < 2.1.3
TensorFlow versions >= 2.2.0, < 2.2.2
TensorFlow versions >= 2.3.0, < 2.3.2

Exploitation Mechanism

The vulnerability arises due to the assumption that src_format and dst_format attributes define a permutation of NHWC, leading to potential memory access errors.

Mitigation and Prevention

To address CVE-2020-26267, follow these mitigation steps:

Immediate Steps to Take

Update TensorFlow to versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, or 2.4.0
Monitor security advisories for patches and updates

Long-Term Security Practices

Regularly update TensorFlow to the latest secure versions
Implement secure coding practices to prevent similar vulnerabilities

Patching and Updates

Apply patches provided by TensorFlow to fix the lack of validation in data format attributes