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CVE-2022-21733

Memory exhaustion in Tensorflow

4.3 MediumFix available

Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output. 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
Low

Exploit likelihood

0.83%Down 0.1 points since Feb 8, 2022
90%50%10%1%

What each source reports

CVE List Score used 4.3

Memory exhaustion in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output. 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-2022-21733
CVSS 3.1
4.3 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
Weakness
CWE-190
Updated
2026-11-02
EUVDEUVD-2022-0296 4.3

Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output. 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-2022-0296
CVSS 3.1
4.3 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
Updated
2026-11-02
GitHub AdvisoriesGHSA-98j8-c9q4-r38g 5.3

Memory exhaustion in Tensorflow

Impact

The implementation of StringNGrams can be used to trigger a denial of service attack by causing an OOM condition after an integer overflow:

import tensorflow as tf

tf.raw_ops.StringNGrams(
  data=['123456'],
  data_splits=[0,1],
  separator='a'*15,
  ngram_widths=[],
  left_pad='',
  right_pad='',
  pad_width=-5, 
  preserve_short_sequences=True)

We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output.

Patches

We have patched the issue in GitHub commit f68fdab93fb7f4ddb4eb438c8fe052753c9413e8.

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 Yu Tian of Qihoo 360 AIVul Team.

Record
GHSA-98j8-c9q4-r38g
CVSS 4.0
5.3 MediumCVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
CVSS 3.1
4.3 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
Weakness
CWE-190, CWE-400
Updated
2026-11-02
NVD 4.3

Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output. 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-2022-21733
CVSS 3.1
4.3 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
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
5.0 MediumAV:N/AC:L/Au:N/C:N/I:N/A:P
Weakness
CWE-190
Updated
2026-11-02
OSV 4.3

Memory exhaustion in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output. 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-2022-21733
CVSS 3.1
4.3 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
Updated
2026-11-02
OSVGHSA-98j8-c9q4-r38g 5.3

Memory exhaustion in Tensorflow

Impact

The implementation of StringNGrams can be used to trigger a denial of service attack by causing an OOM condition after an integer overflow:

import tensorflow as tf

tf.raw_ops.StringNGrams(
  data=['123456'],
  data_splits=[0,1],
  separator='a'*15,
  ngram_widths=[],
  left_pad='',
  right_pad='',
  pad_width=-5, 
  preserve_short_sequences=True)

We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output.

Patches

We have patched the issue in GitHub commit f68fdab93fb7f4ddb4eb438c8fe052753c9413e8.

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 Yu Tian of Qihoo 360 AIVul Team.

Record
GHSA-98j8-c9q4-r38g
CVSS 4.0
5.3 MediumCVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
CVSS 3.1
4.3 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
Weakness
CWE-190, CWE-400
Updated
2026-11-02
Show 5 moreShow less
OSVPYSEC-2026-3145 5.3

Memory exhaustion in Tensorflow

Impact

The implementation of StringNGrams can be used to trigger a denial of service attack by causing an OOM condition after an integer overflow:

import tensorflow as tf

tf.raw_ops.StringNGrams(
  data=['123456'],
  data_splits=[0,1],
  separator='a'*15,
  ngram_widths=[],
  left_pad='',
  right_pad='',
  pad_width=-5, 
  preserve_short_sequences=True)

We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output.

Patches

We have patched the issue in GitHub commit f68fdab93fb7f4ddb4eb438c8fe052753c9413e8.

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 Yu Tian of Qihoo 360 AIVul Team.

Record
PYSEC-2026-3145
CVSS 4.0
5.3 MediumCVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
CVSS 3.1
4.3 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
Updated
2026-11-02
OSVBIT-tensorflow-2022-21733 No score

Memory exhaustion in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output. 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-2022-21733
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-2022-112 No score

Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output. 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-2022-112
Updated
2026-11-02
OSVPYSEC-2022-57 No score

Tensorflow is an Open Source Machine Learning Framework. The implementation of StringNGrams can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on pad_witdh and that result in computing a negative value for ngram_width which is later used to allocate parts of the output. 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-2022-57
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-2022-21733 is a medium vulnerability (CVSS 4.3) 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 0.83%, the 57th percentile. Fixed in tensorflow 2.5.3.

References

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Left out here: 36 versions. The JSON record has them.

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