Skip to content
Fencer Vulns
high 7.8

CVE-2021-37689 json

Null pointer dereference in TensorFlow Lite MLIR optimizations

published 2021-08-12 5 y ago modified 2026-09-10 59 d ago also BIT-tensorflow-2021-37689 , EUVD-2021-0415 , GHSA-wf5p-c75w-w3wh , PYSEC-2021-311 , PYSEC-2021-602 , PYSEC-2021-800

cvss
7.8
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 an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. This is caused by the MLIR optimization of `L2NormalizeReduceAxis` operator. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70) unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements. We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955. 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

0.17% 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 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
GitHub 3.1 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/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 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/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.