Skip to content
Fencer Vulns
medium 6.5

CVE-2022-23583 json

`CHECK`-failures in binary ops in Tensorflow

published 2022-02-04 4 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2022-23583 , EUVD-2022-0331 , GHSA-gjqc-q9g6-q2j3 , PYSEC-2022-147 , PYSEC-2022-92 , PYSEC-2026-3191

cvss
6.5
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
0.9%
EPSS 0.9% chance of exploitation in 30 days, percentile 59%
public exploits
0
none known

Summary

Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that any binary op would trigger `CHECK` failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the `dtype` no longer matches the `dtype` expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. If `Tin` and `Tout` don't match the type of data in `out` and `input_*` tensors then `flat<*>` would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a `CHECK` crash, hence a denial of service. 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

0.88% chance of exploitation in the next 30 days, higher than 59% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/cwise_ops_common.h#L88-L137 referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
GitHub 3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
NVD 3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
NVD 2.0 4.0 AV:N/AC:L/Au:S/C:N/I:N/A:P
OSV 3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/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

Affected products

  • tensorflow tensorflow

Classification

Weakness
  • CWE-617 Reachable Assertion
  • CWE-843 Access of Resource Using Incompatible Type

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.