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