CVE-2022-23568: Integer overflows in Tensorflow

Published Feb 3, 2022
·
Updated

Impact The implementation of AddManySparseToTensorsMap is vulnerable to an integer overflow which results in a CHECK-fail when building new TensorShape objects (so, an assert failure based denial of service):

python import tensorflow as tf import numpy as np

tf.rawops.AddManySparseToTensorsMap( sparseindices=[(0,0),(0,1),(0,2),(4,3),(5,0),(5,1)], sparsevalues=[1,1,1,1,1,1], sparseshape=[232,232], container='', sharedname='', name=None)

We are missing some validation on the shapes of the input tensors as well as directly constructing a large TensorShape with user-provided dimensions. The latter is an instance of TFSA-2021-198 (CVE-2021-41197) and is easily fixed by replacing a call to TensorShape constructor with a call to BuildTensorShape static helper factory. Patches We have patched the issue in GitHub commits b51b82fe65ebace4475e3c54eb089c18a4403f1c and a68f68061e263a88321c104a6c911fe5598050a8.

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.

Other sources

Tensorflow is an Open Source Machine Learning Framework. The implementation of AddManySparseToTensorsMap is vulnerable to an integer overflow which results in a CHECK-fail when building new TensorShape objects (so, an assert failure based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large TensorShape with user-provided dimensions. 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.

Affected Software

12 affected componentsFixes available
pip/tensorflow-gpu=2.7.0
2.7.1
pip/tensorflow-gpu>=2.6.0<2.6.3
2.6.3
pip/tensorflow-gpu<2.5.3
2.5.3
pip/tensorflow-cpu=2.7.0
2.7.1
pip/tensorflow-cpu>=2.6.0<2.6.3
2.6.3
pip/tensorflow-cpu<2.5.3
2.5.3
pip/tensorflow=2.7.0
2.7.1
pip/tensorflow>=2.6.0<2.6.3
2.6.3
pip/tensorflow<2.5.3
2.5.3
Google TensorFlow<=2.5.2
Google TensorFlow>=2.6.0<=2.6.2
Google TensorFlow=2.7.0

Event History

Feb 3, 2022
CVE Published
via MITRE·11:42 AM
Data Sourced
via MITRE·11:42 AM
DescriptionSeverity
Feb 9, 2022
Advisory Published
via GitHub·11:39 PM

Frequently Asked Questions

1

What is the severity of CVE-2022-23568?

CVE-2022-23568 is considered a high-severity vulnerability due to the potential for an integer overflow leading to a crash.

2

How do I fix CVE-2022-23568?

You can fix CVE-2022-23568 by upgrading TensorFlow to version 2.7.1 or higher.

3

Which versions of TensorFlow are affected by CVE-2022-23568?

CVE-2022-23568 affects TensorFlow versions 2.5.2 and earlier, including 2.6.x and 2.7.0.

4

What are the risks associated with CVE-2022-23568?

Exploitation of CVE-2022-23568 could lead to application crashes or Denial of Service conditions.

5

Is CVE-2022-23568 related to any specific TensorFlow functionalities?

CVE-2022-23568 is specifically related to the `AddManySparseToTensorsMap` implementation in TensorFlow.

Contact

SecAlerts Pty Ltd.
132 Wickham Terrace
Fortitude Valley,
QLD 4006, Australia
info@secalerts.co
By using SecAlerts services, you agree to our services end-user license agreement. This website is safeguarded by reCAPTCHA and governed by the Google Privacy Policy and Terms of Service. All names, logos, and brands of products are owned by their respective owners, and any usage of these names, logos, and brands for identification purposes only does not imply endorsement. If you possess any content that requires removal, please get in touch with us.
© 2026 SecAlerts Pty Ltd.
ABN: 70 645 966 203, ACN: 645 966 203