CVE-2020-15211 Explained : Impact and Mitigation

In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1, a vulnerability allows for out-of-bounds access due to a double indexing scheme in saved models.

Understanding CVE-2020-15211

This CVE involves a security issue in TensorFlow Lite versions prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1, potentially leading to out-of-bounds access.

What is CVE-2020-15211?

In TensorFlow Lite, saved models in the flatbuffer format utilize a double indexing scheme, allowing for out-of-bounds access due to the use of a negative

-1

value as an index for optional tensors.

The Impact of CVE-2020-15211

The vulnerability can result in both read and write gadgets, although limited in scope, potentially allowing unauthorized access to heap allocated arrays.

Technical Details of CVE-2020-15211

Vulnerability Description

TensorFlow Lite models use a double indexing scheme that can lead to out-of-bounds access.

Affected Systems and Versions

TensorFlow versions < 1.15.4
TensorFlow versions >= 2.0.0, < 2.0.3
TensorFlow versions >= 2.1.0, < 2.1.2
TensorFlow versions >= 2.2.0, < 2.2.1
TensorFlow versions >= 2.3.0, < 2.3.1

Exploitation Mechanism

The vulnerability allows writing and reading from outside the bounds of heap allocated arrays.

Mitigation and Prevention

Immediate Steps to Take

Upgrade to patched TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1
Implement a custom

Verifier

to validate model loading

Long-Term Security Practices

Regularly update TensorFlow to the latest versions
Follow secure coding practices to prevent similar vulnerabilities

Patching and Updates

Patched code is available in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1