Heap OOB in `SparseBinCount`

Overview

Impact

The implementation of SparseBinCount is vulnerable to a heap OOB:

import tensorflow as tf
  
  
tf.raw_ops.SparseBincount(
  indices=[[0],[1],[2]]
  values=[0,-10000000]
  dense_shape=[1,1]
  size=[1]
  weights=[3,2,1]
  binary_output=False)

This is because of missing validation between the elements of the values argument and the shape of the sparse output:

for (int64_t i = 0; i < indices_mat.dimension(0); ++i) {
  const int64_t batch = indices_mat(i, 0);
  const Tidx bin = values(i);
  ...
  out(batch, bin) = ...;
}

Patches

We have patched the issue in GitHub commit f410212e373eb2aec4c9e60bf3702eba99a38aba.

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