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CVE-2022-35960

`CHECK` failure in `TensorListReserve` in TensorFlow

5.9 MediumFix available

TensorFlow is an open source platform for machine learning. In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement. We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. 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

0.70%Down 0.2 points since Sep 17, 2022
90%50%10%1%

What each source reports

CVE List Score used 5.9

`CHECK` failure in `TensorListReserve` in TensorFlow

TensorFlow is an open source platform for machine learning. In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement. We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. 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-2022-35960
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-2022-6941 5.9

TensorFlow is an open source platform for machine learning. In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement. We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. 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-2022-6941
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-v5xg-3q2c-c2r4 5.9

TensorFlow vulnerable to `CHECK` failure in `TensorListReserve` via missing validation

Impact

In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement.

import tensorflow as tf

tf.raw_ops.TensorListReserve(element_shape=(1,1), num_elements=tf.constant([1,1], dtype=tf.int32), element_dtype=tf.int8)

Patches

We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7.

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 from Singapore Management University.

Record
GHSA-v5xg-3q2c-c2r4
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. In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement. We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. 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-2022-35960
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` failure in `TensorListReserve` in TensorFlow

TensorFlow is an open source platform for machine learning. In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement. We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. 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-2022-35960
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-v5xg-3q2c-c2r4 5.9

TensorFlow vulnerable to `CHECK` failure in `TensorListReserve` via missing validation

Impact

In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement.

import tensorflow as tf

tf.raw_ops.TensorListReserve(element_shape=(1,1), num_elements=tf.constant([1,1], dtype=tf.int32), element_dtype=tf.int8)

Patches

We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7.

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 from Singapore Management University.

Record
GHSA-v5xg-3q2c-c2r4
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
Show 5 moreShow less
OSVPYSEC-2026-1036 5.9

TensorFlow vulnerable to `CHECK` failure in `TensorListReserve` via missing validation

Impact

In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement.

import tensorflow as tf

tf.raw_ops.TensorListReserve(element_shape=(1,1), num_elements=tf.constant([1,1], dtype=tf.int32), element_dtype=tf.int8)

Patches

We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7.

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 from Singapore Management University.

Record
PYSEC-2026-1036
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
OSVPYSEC-2026-3243 5.9

TensorFlow vulnerable to `CHECK` failure in `TensorListReserve` via missing validation

Impact

In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement.

import tensorflow as tf

tf.raw_ops.TensorListReserve(element_shape=(1,1), num_elements=tf.constant([1,1], dtype=tf.int32), element_dtype=tf.int8)

Patches

We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7.

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 from Singapore Management University.

Record
PYSEC-2026-3243
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
OSVPYSEC-2026-3370 5.9

TensorFlow vulnerable to `CHECK` failure in `TensorListReserve` via missing validation

Impact

In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement.

import tensorflow as tf

tf.raw_ops.TensorListReserve(element_shape=(1,1), num_elements=tf.constant([1,1], dtype=tf.int32), element_dtype=tf.int8)

Patches

We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7.

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 from Singapore Management University.

Record
PYSEC-2026-3370
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-2022-35960 No score

`CHECK` failure in `TensorListReserve` in TensorFlow

TensorFlow is an open source platform for machine learning. In core/kernels/list_kernels.cc's TensorListReserve, num_elements is assumed to be a tensor of size 1. When a num_elements of more than 1 element is provided, then tf.raw_ops.TensorListReserve fails the CHECK_EQ in CheckIsAlignedAndSingleElement. We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. 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-2022-35960
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-cpu
PyPI
before 2.7.2
2.7.2
tensorflow-cpu
PyPI
2.8.0 up to 2.8.1
2.8.1
tensorflow-cpu
PyPI
2.9.0 up to 2.9.1
2.9.1
tensorflow-gpu
PyPI
before 2.7.2
2.7.2
tensorflow-gpu
PyPI
2.8.0 up to 2.8.1
2.8.1
tensorflow-gpu
PyPI
2.9.0 up to 2.9.1
2.9.1
tensorflow
Bitnami
2.7.0 up to 2.7.2, 2.8.0 to 2.8.0, 2.9.0 to 2.9.0
2.7.2
Show 6 moreShow less
Affected packages
PackageAffectedFixed
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-cpu
PyPI
before 2.7.2, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 27 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.1
2.7.2
tensorflow-gpu
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-gpu
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
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
tensorflow-cpu
PyPI
before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 27 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.1
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-2022-35960 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 0.70%, the 53rd percentile. Fixed in tensorflow 2.7.2.

References

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