CVE-2021-37671: Reference binding to nullptr in map operations in TensorFlow

Published Aug 12, 2021
·
Updated

Impact An attacker can cause undefined behavior via binding a reference to null pointer in tf.rawops.Map and tf.rawops.OrderedMap operations:

python import tensorflow as tf tf.rawops.MapPeek( key=tf.constant([8],dtype=tf.int64), indices=[], dtypes=[tf.int32], capacity=8, memorylimit=128)

The implementation has a check in place to ensure that indices is in ascending order, but does not check that indices is not empty. Patches We have patched the issue in GitHub commit 532f5c5a547126c634fefd43bbad1dc6417678ac. 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 cause undefined behavior via binding a reference to null pointer in tf.rawops.Map and tf.rawops.OrderedMap operations. The implementation has a check in place to ensure that indices is in ascending order, but does not check that indices is not empty. We have patched the issue in GitHub commit 532f5c5a547126c634fefd43bbad1dc6417678ac. 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 532f5c5a547126c634fefd43bbad1dc6417678ac
  11. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.5.1Patch 532f5c5a547126c634fefd43bbad1dc6417678ac
  12. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.4.3Patch 532f5c5a547126c634fefd43bbad1dc6417678ac
  13. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.3.4Patch 532f5c5a547126c634fefd43bbad1dc6417678ac

Event History

Aug 12, 2021
CVE Published
via MITRE·09:40 PM
Data Sourced
via MITRE·09:40 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-2021-37671?

CVE-2021-37671 has been classified as a high-severity vulnerability due to potential undefined behavior when handling null pointers.

2

How do I fix CVE-2021-37671?

To resolve CVE-2021-37671, upgrade TensorFlow to version 2.3.4, 2.4.3, or 2.5.1, depending on your current version.

3

Which versions of TensorFlow are affected by CVE-2021-37671?

CVE-2021-37671 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-2021-37671 lead to data loss?

While CVE-2021-37671 does not directly cause data loss, the undefined behavior could lead to unexpected application crashes.

5

Is CVE-2021-37671 a remote code execution vulnerability?

CVE-2021-37671 does not provide attackers with the ability to execute arbitrary code remotely, but it can lead to instability in applications.

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