Learn about the high severity CVE-2021-41212 involving a heap out-of-bounds read vulnerability in TensorFlow versions. Understand the impact, affected systems, and mitigation steps.
TensorFlow is an open source platform for machine learning. In affected versions, the shape inference code for
tf.ragged.cross
can trigger a read outside of bounds of the heap allocated array. The fix is included in TensorFlow 2.7.0, and will be cherrypicked on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4 as they are also affected.
Understanding CVE-2021-41212
In this CVE, a heap out-of-bounds (OOB) read vulnerability in
tf.ragged.cross
within TensorFlow versions can lead to potential security risks.
What is CVE-2021-41212?
This CVE involves a vulnerability in TensorFlow versions where the shape inference code for
tf.ragged.cross
can cause a read operation beyond the bounds of the heap array allocated.
The Impact of CVE-2021-41212
The impact of this CVE is rated as high severity due to its potential to compromise confidentiality with a high availability impact. The attack complexity is low, requiring low privileges and no user interaction, posing a significant risk.
Technical Details of CVE-2021-41212
This section delves into the technical aspects of the vulnerability.
Vulnerability Description
The vulnerability lies in the shape inference code for
tf.ragged.cross
in affected TensorFlow versions.
Affected Systems and Versions
Exploitation Mechanism
The issue arises when the shape inference code for
tf.ragged.cross
attempts to read outside the bounds of the allocated heap array.
Mitigation and Prevention
Taking steps to mitigate and prevent the exploitation of this vulnerability is crucial.
Immediate Steps to Take
Long-Term Security Practices
Patching and Updates
Stay informed about security advisories and apply patches promptly to stay protected.