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Fencer Vulns
high 7.8

CVE-2021-37663 json

Incomplete validation in `QuantizeV2` in TensorFlow

published 2021-08-12 5 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2021-37663 , EUVD-2021-0389 , GHSA-g25h-jr74-qp5j , PYSEC-2021-285 , PYSEC-2021-576 , PYSEC-2021-774

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 6%
public exploits
0
none known

Summary

TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in `tf.raw_ops.QuantizeV2`, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/quantize_op.cc#L59) has some validation but does not check that `min_range` and `max_range` both have the same non-zero number of elements. If `axis` is provided (i.e., not `-1`), then validation should check that it is a value in range for the rank of `input` tensor and then the lengths of `min_range` and `max_range` inputs match the `axis` dimension of the `input` tensor. We have patched the issue in GitHub commit 6da6620efad397c85493b8f8667b821403516708. 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 6% 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 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
NVD 2.0 4.6 AV:L/AC:L/Au:N/C:P/I:P/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
  • CWE-20 Improper Input Validation

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.