CVE-2020-15197: 
Python vulnerability analysis and mitigation

The vulnerability (CVE-2020-15197) was discovered in TensorFlow versions before 2.3.1, specifically affecting the SparseCountSparseOutput implementation. The vulnerability was disclosed and patched on September 24, 2020. The issue affected the core functionality of TensorFlow's sparse tensor operations (GitHub Advisory).

The vulnerability exists in the SparseCountSparseOutput implementation where the code fails to validate that the input arguments form a valid sparse tensor. Specifically, there is no validation that the indices tensor has rank 2, despite the code assuming its elements are accessed as elements of a matrix. The issue is located in the file tensorflow/tensorflow/core/kernels/count_ops.cc (TensorFlow Commit).

Malicious users can exploit this vulnerability by passing tensors of different rank, which results in a CHECK assertion failure and subsequent crash. This can be leveraged to cause denial of service in serving installations where users have control over the components of the input sparse tensor (GitHub Advisory).

The vulnerability can be exploited when users have control over the input components of the sparse tensor. The attack vector requires the ability to provide malformed input to the SparseCountSparseOutput operation (GitHub Advisory).

The vulnerability was patched in TensorFlow version 2.3.1. Users are recommended to upgrade to this version or later. The fix includes proper validation of input arguments and additional checks for tensor ranks (TensorFlow Release).