Affected: tensorflow

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.RFFT`. Eigen code operating on an empty matrix can trigger on an assertion and will cause program termination. 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.

Affected: PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu

### Impact An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.RFFT`: ```python import tensorflow as tf

inputs = tf.constant([1], shape=[1], dtype=tf.float32) fft_length = tf.constant([0], shape=[1], dtype=tf.int32)

tf.raw_ops.RFFT(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 [31bd5026304677faa8a0b77602c6154171b9aec1](https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1).

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.