Division by 0 in `FractionalAvgPool`
### Impact
An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`:
```python
import tensorflow as tf
value = tf.constant([60], shape=[1, 1, 1, 1], dtype=tf.int32)
pooling_ratio = [1.0, 1.0000014345305555, 1.0, 1.0]
pseudo_random = False
overlapping = False
deterministic = False
seed = 0
seed2 = 0
tf.raw_ops.FractionalAvgPool(
value=value, pooling_ratio=pooling_ratio, pseudo_random=pseudo_random,
overlapping=overlapping, deterministic=deterministic, seed=seed, seed2=seed2)
```
This is because the implementation
https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89 computes a divisor quantity by dividing two user controlled values:
```cc
for (int i = 0; i < tensor_in_and_out_dims; ++i) {
output_size[i] = static_cast<int>(std::floor(input_size[i] / pooling_ratio_[i]));
DCHECK_GT(output_size[i], 0);
}
```
The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger.
Later, these computed values are used as arguments
https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99 to `GeneratePoolingSequence`
https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108. There, the first computation is a division in a modulo operation:
```cc
std::vector<int64> GeneratePoolingSequence(int input_length, int output_length,
GuardedPhiloxRandom* generator,
bool pseudo_random) {
...
if (input_length % output_length == 0) {
diff = std::vector<int64>(output_length, input_length / output_length);
}
...
}
```
Since `output_length` can be 0, this results in runtime crashing.
### Patches
We have patched the issue in GitHub commit 548b5eaf23685d86f722233d8fbc21d0a4aecb96
https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96.
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.