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CVE-2022-21737

Assertion failure based denial of service in Tensorflow

6.5 MediumFix available

Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. 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.

Attack profile

How easy it is to exploit

Attack vector
Network
Complexity
Low
Privileges needed
Low
User interaction
None

What an attacker can affect

Confidentiality
None
Integrity
None
Availability
High

Exploit likelihood

0.79%Down 0.1 points since Feb 8, 2022
90%50%10%1%

What each source reports

CVE List Score used 6.5

Assertion failure based denial of service in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. 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.

Record
CVE-2022-21737
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-754
Updated
2026-11-02
EUVDEUVD-2022-0300 6.5

Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. 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.

Record
EUVD-2022-0300
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
GitHub AdvisoriesGHSA-f2vv-v9cg-qhh7 7.1

Assertion failure based denial of service in Tensorflow

Impact

The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail:

import tensorflow as tf

tf.raw_ops.DenseBincount(
  input=[[0], [1], [2]],
  size=[1],
  weights=[3,2,1],
  binary_output=False)

There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated.

Patches

We have patched the issue in GitHub commit 7019ce4f68925fd01cdafde26f8d8c938f47e6f9.

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.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.

Record
GHSA-f2vv-v9cg-qhh7
CVSS 4.0
7.1 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-617, CWE-754
Updated
2026-11-02
NVD 6.5

Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. 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.

Record
CVE-2022-21737
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVSS 2.0
4.0 MediumAV:N/AC:L/Au:S/C:N/I:N/A:P
Weakness
CWE-754
Updated
2026-11-02
OSV 6.5

Assertion failure based denial of service in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. 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.

Record
CVE-2022-21737
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVGHSA-f2vv-v9cg-qhh7 7.1

Assertion failure based denial of service in Tensorflow

Impact

The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail:

import tensorflow as tf

tf.raw_ops.DenseBincount(
  input=[[0], [1], [2]],
  size=[1],
  weights=[3,2,1],
  binary_output=False)

There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated.

Patches

We have patched the issue in GitHub commit 7019ce4f68925fd01cdafde26f8d8c938f47e6f9.

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.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.

Record
GHSA-f2vv-v9cg-qhh7
CVSS 4.0
7.1 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-617, CWE-754
Updated
2026-11-02
Show 5 moreShow less
OSVPYSEC-2026-3164 7.1

Assertion failure based denial of service in Tensorflow

Impact

The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail:

import tensorflow as tf

tf.raw_ops.DenseBincount(
  input=[[0], [1], [2]],
  size=[1],
  weights=[3,2,1],
  binary_output=False)

There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated.

Patches

We have patched the issue in GitHub commit 7019ce4f68925fd01cdafde26f8d8c938f47e6f9.

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.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.

Record
PYSEC-2026-3164
CVSS 4.0
7.1 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVBIT-tensorflow-2022-21737 No score

Assertion failure based denial of service in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. 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.

Record
BIT-tensorflow-2022-21737
Updated
2026-11-02
OSVopenSUSE-SU-2024:12116-1 No score

tensorflow-lite-2.9.1-1.1 on GA media

These are all security issues fixed in the tensorflow-lite-2.9.1-1.1 package on the GA media of openSUSE Tumbleweed.

Record
openSUSE-SU-2024:12116-1
Updated
2026-11-02
OSVPYSEC-2022-116 No score

Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. 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.

Record
PYSEC-2022-116
Updated
2026-11-02
OSVPYSEC-2022-61 No score

Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. 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.

Record
PYSEC-2022-61
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
before 2.5.3
2.5.3
tensorflow
PyPI
2.6.0 up to 2.6.3
2.6.3
tensorflow
PyPI
2.7.0 to 2.7.0
2.7.1
tensorflow-cpu
PyPI
before 2.5.3
2.5.3
tensorflow-cpu
PyPI
2.6.0 up to 2.6.3
2.6.3
tensorflow-cpu
PyPI
2.7.0 to 2.7.0
2.7.1
tensorflow-gpu
PyPI
before 2.5.3
2.5.3
tensorflow-gpu
PyPI
2.6.0 up to 2.6.3
2.6.3
tensorflow-gpu
PyPI
2.7.0 to 2.7.0
2.7.1
tensorflow
Bitnami
before 2.5.3, 2.6.0 up to 2.6.3, 2.7.0 up to 2.7.1
2.5.32.6.32.7.1
Show 12 moreShow less
Affected packages
PackageAffectedFixed
tensorflow
PyPI
before 2.5.3, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.5.3
tensorflow
PyPI
2.6.0 up to 2.6.3, plus listed versions
2.6.12.6.2
2.6.3
tensorflow
PyPI
2.7.0 up to 2.7.1
2.7.1
tensorflow-cpu
PyPI
before 2.5.3, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 18 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.2
2.5.3
tensorflow-cpu
PyPI
2.6.0 up to 2.6.3, plus listed versions
2.6.12.6.2
2.6.3
tensorflow-cpu
PyPI
2.7.0 up to 2.7.1
2.7.1
tensorflow-gpu
PyPI
before 2.5.3, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.5.3
tensorflow-gpu
PyPI
2.6.0 up to 2.6.3, plus listed versions
2.6.12.6.2
2.6.3
tensorflow-gpu
PyPI
2.7.0 up to 2.7.1
2.7.1
tensorflow-gpu
PyPI
before 2.5.3, 2.6.0 up to 2.6.3, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.5.32.6.3
tensorflow-cpu
PyPI
before 2.5.3, 2.6.0 up to 2.6.3, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 20 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.6.12.6.2
2.5.32.6.3
tensorflow
PyPI
before 2.5.3, 2.6.0 up to 2.6.3, 2.7.0 up to 2.7.1, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.5.32.6.32.7.1

History

History
RecordedChangedSources
facts
first indexedCVE List, EUVD, GitHub Advisories, NVD, OSV

Dates are when Every CVE recorded each change. Upstream dates may differ.

In short

CVE-2022-21737 is a medium vulnerability (CVSS 6.5) in Google Tensorflow, published February 3, 2022. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.79%, the 56th percentile. Fixed in tensorflow 2.5.3.

References

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