Integer division by 0 in `tf.raw_ops.AllToAll`

Overview

Impact

The shape inference code for AllToAll can be made to execute a division by 0:

import tensorflow as tf
  
@tf.function
def func():
  return tf.raw_ops.AllToAll(
    input=[0.0, 0.1652, 0.6543],
    group_assignment=[1, -1],
    concat_dimension=0,
    split_dimension=0,
    split_count=0)

func()

This occurs whenever the split_count argument is 0:

TF_RETURN_IF_ERROR(c->GetAttr("split_count", &split_count));
...                  
for (int32_t i = 0; i < rank; ++i) {      
  ...                                     
  dims[i] = c->MakeDim(c->Value(dims[i]) / split_count);
  ...                
}

Patches

We have patched the issue in GitHub commit a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc.

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 members of the Aivul Team from Qihoo 360.

Affected packages

• tensorflow >= 2.6.0, < 2.6.1
• tensorflow >= 2.5.0, < 2.5.2
• tensorflow < 2.4.4
• tensorflow-cpu >= 2.6.0, < 2.6.1
• tensorflow-cpu >= 2.5.0, < 2.5.2
• tensorflow-cpu < 2.4.4
• tensorflow-gpu >= 2.6.0, < 2.6.1
• tensorflow-gpu >= 2.5.0, < 2.5.2
• tensorflow-gpu < 2.4.4

Remediation

Upgrade to a patched release:

• tensorflow 2.6.1
• tensorflow 2.5.2
• tensorflow 2.4.4
• tensorflow-cpu 2.6.1
• tensorflow-cpu 2.5.2
• tensorflow-cpu 2.4.4
• tensorflow-gpu 2.6.1
• tensorflow-gpu 2.5.2
• tensorflow-gpu 2.4.4