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CVE-2022-41900

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow

7.1 HighFix available

TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

Attack profile

How easy it is to exploit

Attack vector
Network
Complexity
High
Privileges needed
Low
User interaction
Required

What an attacker can affect

Confidentiality
High
Integrity
High
Availability
High

Exploit likelihood

0.66%Down 1.0 points since Nov 19, 2022
90%50%10%1%

What each source reports

CVE List Score used 7.1

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow

TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

Record
CVE-2022-41900
CVSS 3.1
7.1 HighCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
Weakness
CWE-787, CWE-125
Updated
2026-11-02
EUVDEUVD-2022-7468 7.1

TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

Record
EUVD-2022-7468
CVSS 3.1
7.1 HighCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
Updated
2026-11-02
GitHub AdvisoriesGHSA-xvwp-h6jv-7472 7.1

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess

Impact

An input pooling_ratio that is smaller than 1 will trigger a heap OOB in tf.raw_ops.FractionalMaxPool and tf.raw_ops.FractionalAvgPool.

Patches

We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48.

The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

For more information

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

Record
GHSA-xvwp-h6jv-7472
CVSS 3.1
7.1 HighCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
Weakness
CWE-125, CWE-787
Updated
2026-11-02
NVD 7.1

TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

Record
CVE-2022-41900
CVSS 3.1
7.1 HighCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
CVSS 3.1
9.8 CriticalCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Weakness
CWE-125, CWE-787
Updated
2026-11-02
OSVAZL-11539 9.8

CVE-2022-41900 affecting package tensorflow for versions less than 2.11.0-1

TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

Record
AZL-11539
CVSS 3.1
9.8 CriticalCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Updated
2026-11-02
OSV 7.1

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow

TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

Record
CVE-2022-41900
CVSS 3.1
7.1 HighCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
Weakness
CWE-125, CWE-787
Updated
2026-11-02
Show 5 moreShow less
OSVGHSA-xvwp-h6jv-7472 7.1

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess

Impact

An input pooling_ratio that is smaller than 1 will trigger a heap OOB in tf.raw_ops.FractionalMaxPool and tf.raw_ops.FractionalAvgPool.

Patches

We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48.

The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

For more information

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

Record
GHSA-xvwp-h6jv-7472
CVSS 3.1
7.1 HighCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
Weakness
CWE-125, CWE-787
Updated
2026-11-02
OSVPYSEC-2026-1049 7.1

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess

Impact

An input pooling_ratio that is smaller than 1 will trigger a heap OOB in tf.raw_ops.FractionalMaxPool and tf.raw_ops.FractionalAvgPool.

Patches

We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48.

The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

For more information

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

Record
PYSEC-2026-1049
CVSS 3.1
7.1 HighCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
Updated
2026-11-02
OSVPYSEC-2026-3261 7.1

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess

Impact

An input pooling_ratio that is smaller than 1 will trigger a heap OOB in tf.raw_ops.FractionalMaxPool and tf.raw_ops.FractionalAvgPool.

Patches

We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48.

The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

For more information

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

Record
PYSEC-2026-3261
CVSS 3.1
7.1 HighCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
Updated
2026-11-02
OSVPYSEC-2026-3383 7.1

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess

Impact

An input pooling_ratio that is smaller than 1 will trigger a heap OOB in tf.raw_ops.FractionalMaxPool and tf.raw_ops.FractionalAvgPool.

Patches

We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48.

The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

For more information

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

Record
PYSEC-2026-3383
CVSS 3.1
7.1 HighCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
Updated
2026-11-02
OSVBIT-tensorflow-2022-41900 No score

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow

TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

Record
BIT-tensorflow-2022-41900
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 2.8.4
2.8.4
tensorflow
PyPI
 2.9.0 up to 2.9.3
2.9.3
tensorflow
PyPI
 2.10.0 up to 2.10.1
2.10.1
tensorflow-cpu
PyPI
 before 2.8.4
2.8.4
tensorflow-gpu
PyPI
 before 2.8.4
2.8.4
tensorflow-cpu
PyPI
 2.9.0 up to 2.9.3
2.9.3
tensorflow-gpu
PyPI
 2.9.0 up to 2.9.3
2.9.3
tensorflow-cpu
PyPI
 2.10.0 up to 2.10.1
2.10.1
tensorflow-gpu
PyPI
 2.10.0 up to 2.10.1
2.10.1
tensorflow
Azure Linux:2
 before 2.11.0-1
2.11.0-1
Show 10 moreShow less
Affected packages
PackageAffectedFixed
tensorflow
Bitnami
 before 2.8.4, 2.9.0 up to 2.9.3, 2.10.0 up to 2.10.1
2.8.42.9.32.10.1
tensorflow
PyPI
 before 2.8.4, 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
2.8.4
tensorflow
PyPI
 2.9.0 up to 2.9.3, plus listed versions
2.9.12.9.2
2.9.3
tensorflow-cpu
PyPI
 before 2.8.4, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 34 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.12.7.22.7.32.7.42.8.02.8.12.8.22.8.3
2.8.4
tensorflow-gpu
PyPI
 before 2.8.4, 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
2.8.4
tensorflow-cpu
PyPI
 2.9.0 up to 2.9.3, plus listed versions
2.9.12.9.2
2.9.3
tensorflow-gpu
PyPI
 2.9.0 up to 2.9.3, plus listed versions
2.9.12.9.2
2.9.3
tensorflow-gpu
PyPI
 before 2.8.4, 2.9.0 up to 2.9.3, 2.10.0 up to 2.10.1, 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
2.8.42.9.32.10.1
tensorflow
PyPI
 before 2.8.4, 2.9.0 up to 2.9.3, 2.10.0 up to 2.10.1, 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
2.8.42.9.32.10.1
tensorflow-cpu
PyPI
 before 2.8.4, 2.9.0 up to 2.9.3, 2.10.0 up to 2.10.1, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 36 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.12.7.22.7.32.7.42.8.02.8.12.8.22.8.32.9.12.9.2
2.8.42.9.32.10.1

History

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

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

In short

CVE-2022-41900 is a high vulnerability (CVSS 7.1) in Google Tensorflow, published November 18, 2022. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.66%, the 51st percentile. Fixed in tensorflow 2.8.4.

References

This page doesn't list everything

Left out here: 122 versions. The JSON record has them.

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