CVE-2022-23561 Explained : Impact and Mitigation

Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Understanding CVE-2022-23561

This CVE involves an out-of-bounds write vulnerability in TFLite within TensorFlow, allowing an attacker to manipulate memory allocation and potentially execute arbitrary code.

What is CVE-2022-23561?

CVE-2022-23561 is a security flaw in TensorFlow that enables an attacker to write outside of the bounds of an array in TFLite, leading to potential memory corruption and arbitrary write capabilities.

The Impact of CVE-2022-23561

The impact of this vulnerability is rated as HIGH, with a CVSS base score of 8.8. It can result in confidentiality, integrity, and availability impacts on affected systems, posing a significant security risk.

Technical Details of CVE-2022-23561

This section provides detailed technical information about the vulnerability.

Vulnerability Description

The vulnerability allows an attacker to overwrite the linked list used by the memory allocator, creating a scenario for arbitrary write operations, which can be exploited maliciously.

Affected Systems and Versions

TensorFlow versions >= 2.7.0 and < 2.7.1
TensorFlow versions >= 2.6.0 and < 2.6.3
TensorFlow versions < 2.5.3

Exploitation Mechanism

The attacker can craft a malicious TFLite model to trigger the out-of-bounds write, potentially leading to unauthorized access and execution of arbitrary code on the target system.

Mitigation and Prevention

To address CVE-2022-23561 and enhance system security, follow these steps:

Immediate Steps to Take

Update TensorFlow to version 2.8.0 once the fix is available.
Apply security patches provided by the vendor for versions 2.7.1, 2.6.3, and 2.5.3.

Long-Term Security Practices

Regularly monitor for security advisories and updates from TensorFlow.
Implement secure coding practices and conduct routine security assessments.

Patching and Updates

Stay informed about security patches and updates released by TensorFlow.
Apply patches promptly to mitigate the risk of exploitation.