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TFSA-2020-019: Crash due to invalid splits in SparseCountSparseOutput

CVE Number

CVE-2020-15197

Impact

The SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix:

    const auto indices_values = indices.matrix<int64>();

However, malicious users can pass in tensors of different rank, resulting in a CHECK assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor.

Vulnerable Versions

TensorFlow 2.3.0.

Patches

We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.

We recommend users to upgrade to TensorFlow 2.3.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been discovered through a variant analysis of a vulnerability reported by members of the Aivul Team from Qihoo 360.