CVE-2021-29518 : Security Advisory and Response
Learn about CVE-2021-29518 where TensorFlow session operations in eager mode can lead to null pointer dereferences. Find out the impact, affected versions, and mitigation steps.
TensorFlow is an end-to-end open source platform for machine learning. In eager mode, users could trigger a null pointer dereference by calling raw ops associated with invalid session operations. This vulnerability has a LOW base score of 2.5.
Understanding CVE-2021-29518
Session operations in TensorFlow's eager mode can result in null pointer dereferences, potentially leading to undefined behavior and affecting multiple versions.
What is CVE-2021-29518?
This CVE highlights how TensorFlow's session operations in eager mode can trigger null pointer dereferences, posing a risk to the stability and functionality of machine learning processes.
The Impact of CVE-2021-29518
The vulnerability could result in undefined behavior due to null pointer dereferences, impacting the reliability of TensorFlow's machine learning operations.
Technical Details of CVE-2021-29518
In TensorFlow versions prior to 2.1.4, 2.2.3, 2.3.3, and 2.4.2, the implementation of session operations does not validate the session state pointer, allowing for invalid calls and potential null pointer dereferences.
Vulnerability Description
The vulnerability arises from the invalid handling of session operations in eager mode, leading to null pointer dereferences and undefined behavior.
Affected Systems and Versions
TensorFlow versions prior to 2.1.4, 2.2.3, 2.3.3, and 2.4.2 are affected by this vulnerability.
Exploitation Mechanism
Users could trigger null pointer dereferences by calling raw ops associated with invalid session operations in TensorFlow's eager mode.
Mitigation and Prevention
It is crucial to take immediate steps to address and prevent the exploitation of this vulnerability within TensorFlow.
Immediate Steps to Take
Users should update their TensorFlow installations to version 2.5.0 to mitigate the null pointer dereference issue.
Long-Term Security Practices
Maintain regular updates and adhere to secure coding practices to minimize the risk of vulnerabilities affecting TensorFlow.
Patching and Updates
TensorFlow users are strongly advised to apply the necessary patches and updates provided by TensorFlow to address this vulnerability.