## TFSA-2021-042: Division by 0 in `DenseCountSparseOutput`

### CVE Number
CVE-2021-29554

### Impact
An attacker can cause a denial of service via a FPE runtime error in
`tf.raw_ops.DenseCountSparseOutput`:

```python
import tensorflow as tf

values = tf.constant([], shape=[0, 0], dtype=tf.int64)
weights = tf.constant([])

tf.raw_ops.DenseCountSparseOutput(
  values=values, weights=weights,
  minlength=-1, maxlength=58, binary_output=True)
```

This is because the
[implementation](https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127)
computes a divisor value from user data but does not check that the result is 0
before doing the division:

```cc
int num_batch_elements = 1;
for (int i = 0; i < num_batch_dimensions; ++i) {
  num_batch_elements *= data.shape().dim_size(i);
}
int num_value_elements = data.shape().num_elements() / num_batch_elements;
```

Since `data` is given by the `values` argument, `num_batch_elements` is 0.

### Patches
We have patched the issue in GitHub commit
[da5ff2daf618591f64b2b62d9d9803951b945e9f](https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f).

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

### 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 Yakun Zhang and Ying Wang of Baidu
X-Team.