Undefined behavior in `SparseTensorSliceDataset`

Overview

Impact

The implementation of SparseTensorSliceDataset has an undefined behavior: under certain condition it can be made to dereference a nullptr value:

import tensorflow as tf
import numpy as np

tf.raw_ops.SparseTensorSliceDataset(
  indices=[[]],
  values=[],
  dense_shape=[1,1])

The 3 input arguments represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation.

Patches

We have patched the issue in GitHub commit 965b97e4a9650495cda5a8c210ef6684b4b9eceb.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Faysal Hossain Shezan from University of Virginia.

Affected packages

• tensorflow < 2.5.3
• tensorflow >= 2.6.0, < 2.6.3
• tensorflow >= 2.7.0, < 2.7.1
• tensorflow-cpu < 2.5.3
• tensorflow-cpu >= 2.6.0, < 2.6.3
• tensorflow-cpu >= 2.7.0, < 2.7.1
• tensorflow-gpu < 2.5.3
• tensorflow-gpu >= 2.6.0, < 2.6.3
• tensorflow-gpu >= 2.7.0, < 2.7.1

Remediation

Upgrade to a patched release:

• tensorflow 2.5.3
• tensorflow 2.6.3
• tensorflow 2.7.1
• tensorflow-cpu 2.5.3
• tensorflow-cpu 2.6.3
• tensorflow-cpu 2.7.1
• tensorflow-gpu 2.5.3
• tensorflow-gpu 2.6.3
• tensorflow-gpu 2.7.1