CVE-2020-15196 Explained : Impact and Mitigation

In Tensorflow version 2.3.0, the

SparseCountSparseOutput

and

RaggedCountSparseOutput

implementations have a vulnerability that allows a user passing fewer weights than the values for the tensors to generate a read from outside the bounds of the heap buffer allocated for the weights. This issue is patched in TensorFlow version 2.3.1.

Understanding CVE-2020-15196

What is CVE-2020-15196?

CVE-2020-15196 is a vulnerability in Tensorflow version 2.3.0 that can lead to a heap buffer overflow due to improper validation of tensor shapes.

The Impact of CVE-2020-15196

The vulnerability has a CVSS base score of 8.5 (High) and affects confidentiality, integrity, and availability. It requires low privileges to exploit and has a high attack complexity.

Technical Details of CVE-2020-15196

Vulnerability Description

In Tensorflow 2.3.0, the

SparseCountSparseOutput

and

RaggedCountSparseOutput

implementations lack validation for tensor shapes, allowing for a heap buffer overflow.

Affected Systems and Versions

Product: Tensorflow
Vendor: Tensorflow
Versions Affected: 2.3.0

Exploitation Mechanism

The vulnerability arises from passing fewer weights than tensor values, leading to reads outside the allocated buffer.

Mitigation and Prevention

Immediate Steps to Take

Update Tensorflow to version 2.3.1 to apply the patch.
Avoid processing untrusted data with affected versions.

Long-Term Security Practices

Regularly update software and libraries to the latest versions.
Implement input validation to prevent buffer overflows.

Patching and Updates

Patch for this issue is available in Tensorflow version 2.3.1.