CVE-2020-15214 : Exploit Details and Defense Strategies

In TensorFlow Lite before versions 2.2.1 and 2.3.1, a vulnerability allows models using segment sum to trigger a write out of bounds/segmentation fault if segment ids are not sorted. This issue has a CVSS base score of 8.1.

Understanding CVE-2020-15214

This CVE involves an out-of-bounds write vulnerability in TensorFlow Lite.

What is CVE-2020-15214?

In TensorFlow Lite versions 2.2.0 to 2.2.1 and 2.3.0 to 2.3.1, improper handling of segment ids in models can lead to memory corruption and potential exploitation.

The Impact of CVE-2020-15214

The vulnerability can result in a segmentation fault, potentially enabling future memory corruption-based exploits.

Technical Details of CVE-2020-15214

This section provides more in-depth technical details of the vulnerability.

Vulnerability Description

The issue arises from models using segment sum where unsorted segment ids can cause memory allocation errors and write outside the array bounds.

Affected Systems and Versions

Affected versions: TensorFlow Lite >= 2.2.0, < 2.2.1 and >= 2.3.0, < 2.3.1
Systems: TensorFlow

Exploitation Mechanism

The vulnerability triggers a write out of bounds/segmentation fault due to assumptions about the order of segment ids.

Mitigation and Prevention

To address CVE-2020-15214, follow these mitigation strategies:

Immediate Steps to Take

Upgrade to TensorFlow versions 2.2.1 or 2.3.1 where the issue is patched.
Implement a custom

Verifier

to ensure segment ids are sorted in model loading code.

Long-Term Security Practices

Regularly update TensorFlow to the latest patched versions.
Conduct thorough testing to ensure proper handling of segment ids.

Patching and Updates

Patch available in commit 204945b19e44b57906c9344c0d00120eeeae178a.