CVE-2021-37674: Incomplete validation in `MaxPoolGrad` in TensorFlow

Published Aug 12, 2021
·
Updated

Impact An attacker can trigger a denial of service via a segmentation fault in tf.rawops.MaxPoolGrad caused by missing validation:

python import tensorflow as tf tf.rawops.MaxPoolGrad( originput = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32), origoutput = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32), grad = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32), ksize = [1, 16, 16, 1], strides = [1, 16, 18, 1], padding = "EXPLICIT", explicitpaddings = [0, 0, 14, 3, 15, 5, 0, 0]) The implementation misses some validation for the originput and origoutput tensors.

The fixes for CVE-2021-29579 were incomplete. Patches We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475.

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 an attacker can trigger a denial of service via a segmentation fault in tf.rawops.MaxPoolGrad caused by missing validation. The implementation misses some validation for the originput and origoutput tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. 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 136b51f10903e044308cf77117c0ed9871350475
  11. Upgrade

    Upgrade TensorFlow to a version that resolves this vulnerability.

    Fixed in 2.5.1Patch 136b51f10903e044308cf77117c0ed9871350475
  12. Upgrade

    Upgrade TensorFlow to a version that resolves this vulnerability.

    Fixed in 2.4.3Patch 136b51f10903e044308cf77117c0ed9871350475
  13. Upgrade

    Upgrade TensorFlow to a version that resolves this vulnerability.

    Fixed in 2.3.4Patch 136b51f10903e044308cf77117c0ed9871350475

Event History

Aug 12, 2021
CVE Published
via MITRE·10:40 PM
Data Sourced
via MITRE·10:40 PM
DescriptionSeverityWeakness
Data Sourced
via NVD·11:15 PM
RemedyDescriptionSeverityWeaknessAffected Software
Aug 25, 2021
Advisory Published
via GitHub·02:41 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-37674?

The severity of CVE-2021-37674 is considered to be high due to the potential for denial of service.

2

Which versions of TensorFlow are affected by CVE-2021-37674?

CVE-2021-37674 affects TensorFlow versions between 2.3.0 and 2.3.4, 2.4.0 and 2.4.3, and specifically 2.5.0, along with release candidates 2.6.0-rc0, 2.6.0-rc1, and 2.6.0-rc2.

3

How do I fix CVE-2021-37674?

To fix CVE-2021-37674, upgrade to TensorFlow version 2.5.1 or 2.4.3, or 2.3.4.

4

What type of vulnerability is CVE-2021-37674?

CVE-2021-37674 is classified as a denial of service vulnerability caused by a segmentation fault.

5

Can CVE-2021-37674 be exploited remotely?

Yes, CVE-2021-37674 can potentially be exploited remotely by an attacker to trigger a denial of service.

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