CVE-2021-37675: Division by 0 in most convolution operators in TensorFlow

Published Aug 12, 2021
·
Updated

Impact Most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash:

python import tensorflow as tf

tf.compat.v1.disablev2behavior() tf.rawops.Conv2D( input = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32), filter = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32), strides = [1, 1, 1, 1], padding = "SAME")

The shape inference implementation is missing several validations before doing divisions and modulo operations.

Patches We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4.

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 Yakun Zhang of Baidu Security.

Other sources

TensorFlow is an end-to-end open source platform for machine learning. In affected versions most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash. The shape inference implementation is missing several validations before doing divisions and modulo operations. We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4. 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 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4
  11. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.5.1Patch 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4
  12. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.4.3Patch 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4
  13. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.3.4Patch 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4

Event History

Aug 12, 2021
CVE Published
via MITRE·09:45 PM
Data Sourced
via MITRE·09:45 PM
DescriptionSeverityWeakness
Data Sourced
via NVD·10:15 PM
RemedyDescriptionSeverityWeaknessAffected Software
Aug 25, 2021
Advisory Published
via GitHub·02:41 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-37675?

CVE-2021-37675 has a high severity rating due to its potential to cause denial of service through application crashes.

2

How do I fix CVE-2021-37675?

To fix CVE-2021-37675, upgrade TensorFlow to version 2.5.1 or later for affected versions.

3

What versions of TensorFlow are affected by CVE-2021-37675?

CVE-2021-37675 affects TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, and specific 2.6.0 release candidates.

4

Can CVE-2021-37675 be exploited remotely?

Yes, CVE-2021-37675 can be exploited remotely, allowing attackers to cause service disruptions.

5

Where can I find additional information about CVE-2021-37675?

Additional information about CVE-2021-37675 can be found in security advisories provided by TensorFlow on their GitHub repository.

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