high
7.3
CWE
125
Advisory Published
Advisory Published
Updated

CVE-2021-37635: Heap out of bounds access in sparse reduction operations in TensorFlow

First published: Thu Aug 12 2021(Updated: )

### Impact The implementation of sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data: ```python import tensorflow as tf x = tf.SparseTensor( indices=[[773, 773, 773], [773, 773, 773]], values=[1, 1], dense_shape=[337, 337, 337]) tf.sparse.reduce_sum(x, 1) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_reduce_op.cc#L217-L228) fails to validate that each reduction group does not overflow and that each corresponding index does not point to outside the bounds of the input tensor. ### Patches We have patched the issue in GitHub commit [87158f43f05f2720a374f3e6d22a7aaa3a33f750](https://github.com/tensorflow/tensorflow/commit/87158f43f05f2720a374f3e6d22a7aaa3a33f750). 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](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) 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.

Credit: security-advisories@github.com security-advisories@github.com

Affected SoftwareAffected VersionHow to fix
pip/tensorflow-gpu=2.5.0
2.5.1
pip/tensorflow-gpu>=2.4.0<2.4.3
2.4.3
pip/tensorflow-gpu<2.3.4
2.3.4
pip/tensorflow-cpu=2.5.0
2.5.1
pip/tensorflow-cpu>=2.4.0<2.4.3
2.4.3
pip/tensorflow-cpu<2.3.4
2.3.4
pip/tensorflow=2.5.0
2.5.1
pip/tensorflow>=2.4.0<2.4.3
2.4.3
pip/tensorflow<2.3.4
2.3.4
TensorFlow Keras>=2.3.0<2.3.4
TensorFlow Keras>=2.4.0<2.4.3
TensorFlow Keras=2.5.0
TensorFlow Keras=2.6.0-rc0
TensorFlow Keras=2.6.0-rc1
TensorFlow Keras=2.6.0-rc2

Remedy

https://github.com/tensorflow/tensorflow/commit/87158f43f05f2720a374f3e6d22a7aaa3a33f750

Never miss a vulnerability like this again

Sign up to SecAlerts for real-time vulnerability data matched to your software, aggregated from hundreds of sources.

Read MoreStart Free Trial

Reference Links

Frequently Asked Questions

  • What is the severity of CVE-2021-37635?

    CVE-2021-37635 has been classified with a high severity level due to potential out-of-bounds access leading to security vulnerabilities.

  • How do I fix CVE-2021-37635?

    To fix CVE-2021-37635, upgrade to TensorFlow version 2.5.1, 2.4.3, or 2.3.4.

  • Which versions of TensorFlow are affected by CVE-2021-37635?

    CVE-2021-37635 affects TensorFlow versions between 2.3.0 and 2.3.4, versions between 2.4.0 and 2.4.3, as well as versions 2.5.0 and 2.6.0-rc0, rc1, and rc2.

  • What type of vulnerability is CVE-2021-37635?

    CVE-2021-37635 is a memory safety vulnerability that can lead to out-of-bounds access in TensorFlow.

  • Who is affected by CVE-2021-37635?

    Developers and users of TensorFlow versions listed in the vulnerability details are at risk from CVE-2021-37635.

Company

Resources

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.
© 2025 SecAlerts Pty Ltd.
ABN: 70 645 966 203, ACN: 645 966 203