CVE-2021-37655: Heap OOB in `ResourceScatterUpdate` in TensorFlow

Published Aug 12, 2021
·
Updated

Impact An attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to tf.rawops.ResourceScatterUpdate:

python import tensorflow as tf

v = tf.Variable([b'vvv']) tf.rawops.ResourceScatterUpdate( resource=v.handle, indices=[0], updates=['1', '2', '3', '4', '5']) The implementation has an incomplete validation of the relationship between the shapes of indices and updates: instead of checking that the shape of indices is a prefix of the shape of updates (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship.

Patches We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f.

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 an attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to tf.rawops.ResourceScatterUpdate. The implementation has an incomplete validation of the relationship between the shapes of indices and updates: instead of checking that the shape of indices is a prefix of the shape of updates (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship. We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f. 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 01cff3f986259d661103412a20745928c727326f
  11. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.5.1Patch 01cff3f986259d661103412a20745928c727326f
  12. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.4.3Patch 01cff3f986259d661103412a20745928c727326f
  13. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.3.4Patch 01cff3f986259d661103412a20745928c727326f

Event History

Aug 12, 2021
CVE Published
via MITRE·08:25 PM
Data Sourced
via MITRE·08:25 PM
DescriptionSeverityWeakness
Data Sourced
via NVD·09:15 PM
RemedyDescriptionSeverityWeaknessAffected Software
Aug 25, 2021
Advisory Published
via GitHub·02:42 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-37655?

CVE-2021-37655 is classified as a high severity vulnerability due to its potential to allow attackers to read beyond the bounds of heap allocated data.

2

How do I fix CVE-2021-37655?

To fix CVE-2021-37655, you should upgrade to TensorFlow version 2.5.1 or later, or 2.4.3 if using an earlier version.

3

Which versions of TensorFlow are affected by CVE-2021-37655?

CVE-2021-37655 affects TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, and 2.5.0.

4

What type of vulnerability is CVE-2021-37655?

CVE-2021-37655 is a heap data exposure vulnerability that can be exploited by providing invalid arguments to the ResourceScatterUpdate function.

5

Is there a known exploit for CVE-2021-37655?

As of now, there is no publicly known exploit for CVE-2021-37655, but its high severity indicates a significant risk if left unpatched.

Company

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