CVE-2021-37672: Heap OOB in `SdcaOptimizerV2` in TensorFlow

Published Aug 12, 2021
·
Updated

Impact An attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to tf.rawops.SdcaOptimizerV2:

python import tensorflow as tf tf.rawops.SdcaOptimizerV2( sparseexampleindices=[[1]], sparsefeatureindices=[[1]], sparsefeaturevalues=[[1.0,2.0]], densefeatures=[[1.0]], exampleweights=[1.0], examplelabels=[], sparseindices=[1], sparseweights=[1.0], denseweights=[[1.0]], examplestatedata=[[100.0,100.0,100.0,100.0]], losstype='logisticloss', l1=100.0, l2=100.0, numlosspartitions=1, numinneriterations=1, adaptive=True)

The implementation does not check that the length of examplelabels is the same as the number of examples.

Patches We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6.

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 read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to tf.rawops.SdcaOptimizerV2. The implementation does not check that the length of examplelabels is the same as the number of examples. We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6. 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 a4e138660270e7599793fa438cd7b2fc2ce215a6
  11. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.5.1Patch a4e138660270e7599793fa438cd7b2fc2ce215a6
  12. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.4.3Patch a4e138660270e7599793fa438cd7b2fc2ce215a6
  13. Upgrade

    Upgrade tensorflow to a version that resolves this vulnerability.

    Fixed in 2.3.4Patch a4e138660270e7599793fa438cd7b2fc2ce215a6

Event History

Aug 12, 2021
CVE Published
via MITRE·10:20 PM
Data Sourced
via MITRE·10:20 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-2021-37672?

CVE-2021-37672 is considered a medium severity vulnerability as it allows attackers to read out-of-bounds memory segments.

2

How do I fix CVE-2021-37672?

To remediate CVE-2021-37672, update TensorFlow to version 2.5.1 or later, or to version 2.4.3 if you are using TensorFlow 2.4.x.

3

What versions of TensorFlow are affected by CVE-2021-37672?

CVE-2021-37672 affects TensorFlow versions from 2.3.0 to 2.4.3, including version 2.5.0 and release candidates of 2.6.0.

4

What type of exploit is associated with CVE-2021-37672?

The exploit for CVE-2021-37672 involves sending specially crafted illegal arguments to the tf.raw_ops.SdcaOptimizerV2 function.

5

What are the potential impacts of CVE-2021-37672?

The potential impact of CVE-2021-37672 includes unauthorized access to sensitive information due to heap memory read vulnerabilities.

Company

Resources

Contact

SecAlerts Pty Ltd.
132 Wickham Terrace
Fortitude Valley,
QLD 4006, Australia
info@secalerts.co
By using SecAlerts services, you agree to our services end-user license agreement. This website is safeguarded by reCAPTCHA and governed by the Google Privacy Policy and Terms of Service. All names, logos, and brands of products are owned by their respective owners, and any usage of these names, logos, and brands for identification purposes only does not imply endorsement. If you possess any content that requires removal, please get in touch with us.
© 2026 SecAlerts Pty Ltd.
ABN: 70 645 966 203, ACN: 645 966 203