Discover the impact and mitigation strategies for CVE-2021-41205, a high-severity heap out-of-bounds read vulnerability in TensorFlow affecting versions 2.4.4 to 2.6.0.
TensorFlow is an open-source platform for machine learning. In affected versions, the shape inference functions for the
QuantizeAndDequantizeV*
operations may trigger an out-of-bounds read, leading to a high severity vulnerability.
Understanding CVE-2021-41205
In this CVE, a heap out-of-bounds read vulnerability in all
tf.raw_ops.QuantizeAndDequantizeV*
ops in TensorFlow has been identified and addressed.
What is CVE-2021-41205?
The vulnerability in TensorFlow versions could allow an attacker to read outside the bounds of a heap-allocated array.
The Impact of CVE-2021-41205
The CVSS v3.1 base score for this vulnerability is 7.1, indicating a high severity issue with a significant impact on confidentiality and availability.
Technical Details of CVE-2021-41205
This section delves into the technical aspects of the vulnerability.
Vulnerability Description
The issue stems from the shape inference functions of certain operations, potentially leading to unauthorized reads beyond the memory bounds.
Affected Systems and Versions
Exploitation Mechanism
The vulnerability can be exploited locally with low privileges required, impacting confidentiality and availability significantly.
Mitigation and Prevention
To address and mitigate the risks associated with CVE-2021-41205, consider the following steps:
Immediate Steps to Take
Long-Term Security Practices
Patching and Updates
Stay informed about security advisories issued by TensorFlow and promptly apply patches and updates to ensure a secure environment.