CVE-2021-37662: Reference binding to nullptr in boosted trees in TensorFlow

Published Aug 12, 2021
·
Updated

Impact An attacker can generate undefined behavior via a reference binding to nullptr in BoostedTreesCalculateBestGainsPerFeature:

python import tensorflow as tf

tf.rawops.BoostedTreesCalculateBestGainsPerFeature( nodeidrange=[], statssummarylist=[[1,2,3]], l1=[1.0], l2=[1.0], treecomplexity =[1.0], minnodeweight =[1.17], maxsplits=5)

A similar attack can occur in BoostedTreesCalculateBestFeatureSplitV2:

python import tensorflow as tf tf.rawops.BoostedTreesCalculateBestFeatureSplitV2( nodeidrange=[], statssummarieslist=[[1,2,3]], splittypes=[''], candidatefeatureids=[1,2,3,4], l1=[1], l2=[1], treecomplexity=[1.0], minnodeweight=[1.17], logitsdimension=5) The implementation does not validate the input values.

Patches We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit. 429f009d2b2c09028647dd4bb7b3f6f414bbaad7.

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 generate undefined behavior via a reference binding to nullptr in BoostedTreesCalculateBestGainsPerFeature and similar attack can occur in BoostedTreesCalculateBestFeatureSplitV2. The implementation does not validate the input values. We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit 429f009d2b2c09028647dd4bb7b3f6f414bbaad7. 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/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.6.0
  11. Upgrade

    Upgrade to a fixed release to a version that resolves this vulnerability.

    Patch 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad
  12. Upgrade

    Upgrade to a fixed release to a version that resolves this vulnerability.

    Patch 429f009d2b2c09028647dd4bb7b3f6f414bbaad7
  13. Upgrade

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

    Fixed in 2.5.1
  14. Upgrade

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

    Fixed in 2.4.3
  15. Upgrade

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

    Fixed in 2.3.4

Event History

Aug 12, 2021
CVE Published
via MITRE·08:55 PM
Data Sourced
via MITRE·08:55 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-2021-37662?

CVE-2021-37662 is classified as a high-severity vulnerability due to its potential for causing undefined behavior in TensorFlow.

2

How do I fix CVE-2021-37662?

To fix CVE-2021-37662, upgrade TensorFlow to version 2.3.5, 2.4.3, or 2.5.1.

3

What software is affected by CVE-2021-37662?

CVE-2021-37662 affects TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, and 2.5.0.

4

What impact does CVE-2021-37662 have on users?

CVE-2021-37662 may lead to crashes or unexpected behavior in applications using affected versions of TensorFlow.

5

Is there a workaround for CVE-2021-37662?

There is no specific workaround for CVE-2021-37662; the recommended action is to update to the patched versions.

Contact

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