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Fencer Vulns
high 8.1

CVE-2022-21728 json

Out of bounds read in Tensorflow

published 2022-02-03 4 y ago modified 2026-09-10 1 mo ago also BIT-tensorflow-2022-21728 , EUVD-2022-0291 , GHSA-6gmv-pjp9-p8w8 , PYSEC-2022-107 , PYSEC-2022-52 , PYSEC-2026-3121

cvss
8.1
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
1.1%
EPSS 1.1% chance of exploitation in 30 days, percentile 66%
public exploits
0
none known

Summary

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Patch / fix

  • pypi tensorflow 2.5.3, 2.6.3, 2.7.1
  • pypi tensorflow-cpu 2.5.3, 2.6.3, 2.7.1
  • pypi tensorflow-gpu 2.5.3, 2.6.3, 2.7.1
  • bitnami tensorflow 2.5.3, 2.6.3, 2.7.1

CISA SSVC

Exploitation
Proof of concept is public
Automatable
no
Technical impact
partial
Assessed
18 mo ago

Exploit prediction

1.13% chance of exploitation in the next 30 days, higher than 66% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428 referenced PoC, tagged "exploit" by a source, unverified
  • github.com https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671 referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 8.1 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
GitHub 3.1 8.1 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
NVD 3.1 8.1 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
NVD 2.0 5.5 AV:N/AC:L/Au:S/C:P/I:N/A:P
OSV 3.1 8.1 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H

Affected packages

ecosystem package affected fixed in
pypi tensorflow
<2.5.3
>=2.6.0, <2.6.3
>=2.7.0, <2.7.1
2.5.3
2.6.3
2.7.1
pypi tensorflow-cpu
<2.5.3
>=2.6.0, <2.6.3
>=2.7.0, <2.7.1
2.5.3
2.6.3
2.7.1
pypi tensorflow-gpu
<2.5.3
>=2.6.0, <2.6.3
>=2.7.0, <2.7.1
2.5.3
2.6.3
2.7.1
bitnami tensorflow
<2.5.3
>=2.6.0, <2.6.3
>=2.7.0, <2.7.1
2.5.3
2.6.3
2.7.1

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.