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CVE-2022-35998

`CHECK` fail in `EmptyTensorList` in TensorFlow

5.9 MediumFix available

TensorFlow is an open source platform for machine learning. If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Attack profile

How easy it is to exploit

Attack vector
Network
Complexity
High
Privileges needed
None
User interaction
None

What an attacker can affect

Confidentiality
None
Integrity
None
Availability
High

Exploit likelihood

0.49%Down 0.4 points since Sep 17, 2022
90%50%10%1%

What each source reports

CVE List Score used 5.9

`CHECK` fail in `EmptyTensorList` in TensorFlow

TensorFlow is an open source platform for machine learning. If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Record
CVE-2022-35998
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-617
Updated
2026-11-02
EUVDEUVD-2022-6918 5.9

TensorFlow is an open source platform for machine learning. If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Record
EUVD-2022-6918
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
GitHub AdvisoriesGHSA-qhw4-wwr7-gjc5 5.9

TensorFlow vulnerable to `CHECK` fail in `EmptyTensorList`

Impact

If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack.

import tensorflow as tf

tf.raw_ops.EmptyTensorList(element_shape=tf.ones(dtype=tf.int32, shape=[1, 0]), max_num_elements=tf.constant(1),element_dtype=tf.int32)

Patches

We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Kang Hong Jin.

Record
GHSA-qhw4-wwr7-gjc5
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-617
Updated
2026-11-02
NVD 5.9

TensorFlow is an open source platform for machine learning. If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Record
CVE-2022-35998
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
CVSS 3.1
7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-617
Updated
2026-11-02
OSV 5.9

`CHECK` fail in `EmptyTensorList` in TensorFlow

TensorFlow is an open source platform for machine learning. If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Record
CVE-2022-35998
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-617
Updated
2026-11-02
OSVGHSA-qhw4-wwr7-gjc5 5.9

TensorFlow vulnerable to `CHECK` fail in `EmptyTensorList`

Impact

If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack.

import tensorflow as tf

tf.raw_ops.EmptyTensorList(element_shape=tf.ones(dtype=tf.int32, shape=[1, 0]), max_num_elements=tf.constant(1),element_dtype=tf.int32)

Patches

We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Kang Hong Jin.

Record
GHSA-qhw4-wwr7-gjc5
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-617
Updated
2026-11-02
OSVPYSEC-2026-937 5.9

TensorFlow vulnerable to `CHECK` fail in `EmptyTensorList`

Impact

If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack.

import tensorflow as tf

tf.raw_ops.EmptyTensorList(element_shape=tf.ones(dtype=tf.int32, shape=[1, 0]), max_num_elements=tf.constant(1),element_dtype=tf.int32)

Patches

We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Kang Hong Jin.

Record
PYSEC-2026-937
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVBIT-tensorflow-2022-35998 No score

`CHECK` fail in `EmptyTensorList` in TensorFlow

TensorFlow is an open source platform for machine learning. If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Record
BIT-tensorflow-2022-35998
Updated
2026-11-02
OSVopenSUSE-SU-2024:12355-1 No score

tensorflow-lite-2.10.0-1.1 on GA media

These are all security issues fixed in the tensorflow-lite-2.10.0-1.1 package on the GA media of openSUSE Tumbleweed.

Record
openSUSE-SU-2024:12355-1
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 2.7.2
2.7.2
tensorflow
PyPI
 2.8.0 up to 2.8.1
2.8.1
tensorflow
PyPI
 2.9.0 up to 2.9.1
2.9.1
tensorflow
Bitnami
 before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1
2.7.22.8.12.9.1
tensorflow
PyPI
 before 2.7.2, 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
2.7.2
tensorflow
PyPI
 before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1, 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
2.7.22.8.12.9.1

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-2022-35998 is a medium vulnerability (CVSS 5.9) in Google Tensorflow, published September 16, 2022. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.49%, the 42nd percentile. Fixed in tensorflow 2.7.2.

References

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