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Fencer Vulns
medium 5.5

CVE-2021-37675 json

Division by 0 in most convolution operators in TensorFlow

published 2021-08-12 5 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2021-37675 , EUVD-2021-0401 , GHSA-9c8h-2mv3-49ww , PYSEC-2021-297 , PYSEC-2021-588 , PYSEC-2021-786

cvss
5.5
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
0.2%
EPSS 0.2% chance of exploitation in 30 days, percentile 5%
public exploits
0
none known

Summary

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](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) 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.

Patch / fix

  • pypi tensorflow 2.3.4, 2.4.3, 2.5.1
  • pypi tensorflow-cpu 2.3.4, 2.4.3, 2.5.1
  • pypi tensorflow-gpu 2.3.4, 2.4.3, 2.5.1
  • bitnami tensorflow 2.3.4, 2.4.3, 2.5.1
  • google tensorflow 2.3.4, 2.4.3
  • tensorflow2 Package Hub 15 SP3, openSUSE Leap 15.3 2.6.0-bp153.2.3.1
  • bazel3.7 Package Hub 15 SP3, openSUSE Leap 15.3 3.7.2-bp153.4.1
  • tensorflow2-lite Package Hub 15 SP3, openSUSE Leap 15.3 2.6.0-bp153.2.3.1
  • bazel-skylib1.0.3 Package Hub 15 SP3, openSUSE Leap 15.3 1.0.3-bp153.2.1
  • tensorflow2_2_6_0-gnu-hpc Package Hub 15 SP3, openSUSE Leap 15.3 2.6.0-bp153.2.3.1
  • tensorflow2_2_6_0-gnu-openmpi2-hpc Package Hub 15 SP3, openSUSE Leap 15.3 2.6.0-bp153.2.3.1

opensuse advisories openSUSE-SU-2022:10014-1

  • tensorflow Arch Linux 2.5.1-1

arch linux advisories AVG-2292

Exploit prediction

0.16% chance of exploitation in the next 30 days, higher than 5% of all scored CVEs (FIRST EPSS, 2026-11-08).

CVSS scores

assigned by version score vector
CNA 3.1 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
GitHub 3.1 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
NVD 3.1 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
NVD 2.0 2.1 AV:L/AC:L/Au:N/C:N/I:N/A:P
OSV 3.1 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Affected packages

ecosystem package affected fixed in
pypi tensorflow
<2.3.4
>=2.4.0, <2.4.3
>=2.5.0, <2.5.1
>=2.3.0, <2.3.4
2.3.4
2.4.3
2.5.1
pypi tensorflow-cpu
<2.3.4
>=2.4.0, <2.4.3
>=2.5.0, <2.5.1
>=2.3.0, <2.3.4
2.3.4
2.4.3
2.5.1
pypi tensorflow-gpu
<2.3.4
>=2.4.0, <2.4.3
>=2.5.0, <2.5.1
>=2.3.0, <2.3.4
2.3.4
2.4.3
2.5.1
bitnami tensorflow
>=2.3.0, <2.3.4
>=2.4.0, <2.4.3
>=2.5.0, <2.5.1
2.3.4
2.4.3
2.5.1

Affected products

  • tensorflow tensorflow

Classification

Weakness

References

Sources

Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.