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

Published 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], denseshape=[337, 337, 337]) tf.sparse.reducesum(x, 1)

The implementation 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.

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 members of the Aivul Team from Qihoo 360.

Other sources

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data. The implementation 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. We have patched the issue in GitHub 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.

Affected Software

15 affected componentsFixes available
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
Google TensorFlow>=2.3.0<2.3.4
Google TensorFlow>=2.4.0<2.4.3
Google TensorFlow=2.5.0
Google TensorFlow=2.6.0-rc0
Google TensorFlow=2.6.0-rc1
Google TensorFlow=2.6.0-rc2

Remediation

Recommended actions to resolve this vulnerability, in priority order.

  1. Upgrade

    Upgrade pip/tensorflow-gpu to a version that resolves this vulnerability.

    Fixed in 2.5.1
  2. Upgrade

    Upgrade pip/tensorflow-gpu to a version that resolves this vulnerability.

    Fixed in 2.4.3
  3. Upgrade

    Upgrade pip/tensorflow-gpu to a version that resolves this vulnerability.

    Fixed in 2.3.4
  4. Upgrade

    Upgrade pip/tensorflow-cpu to a version that resolves this vulnerability.

    Fixed in 2.5.1
  5. Upgrade

    Upgrade pip/tensorflow-cpu to a version that resolves this vulnerability.

    Fixed in 2.4.3
  6. Upgrade

    Upgrade pip/tensorflow-cpu to a version that resolves this vulnerability.

    Fixed in 2.3.4
  7. Upgrade

    Upgrade pip/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.5.1
  8. Upgrade

    Upgrade pip/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.4.3
  9. Upgrade

    Upgrade pip/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.3.4
  10. Upgrade

    Upgrade TensorFlow to a version that resolves this vulnerability.

    Fixed in 2.6.0Patch 87158f43f05f2720a374f3e6d22a7aaa3a33f750
  11. Upgrade

    Upgrade TensorFlow to a version that resolves this vulnerability.

    Fixed in 2.5.1Patch 87158f43f05f2720a374f3e6d22a7aaa3a33f750
  12. Upgrade

    Upgrade TensorFlow to a version that resolves this vulnerability.

    Fixed in 2.4.3Patch 87158f43f05f2720a374f3e6d22a7aaa3a33f750
  13. Upgrade

    Upgrade TensorFlow to a version that resolves this vulnerability.

    Fixed in 2.3.4Patch 87158f43f05f2720a374f3e6d22a7aaa3a33f750

Event History

Aug 12, 2021
CVE Published
via MITRE·08:30 PM
Data Sourced
via MITRE·08:30 PM
DescriptionSeverityWeakness
Data Sourced
via NVD·09:15 PM
RemedyDescriptionSeverityWeaknessAffected Software
Aug 25, 2021
Advisory Published
via GitHub·02:44 PM

Frequently Asked Questions

1

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.

2

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.

3

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.

4

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.

5

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

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Contact

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