How severe is GHSA-mgmh-g2v6-mqw5?

GHSA-mgmh-g2v6-mqw5 has a CVSS score of 5.9/10, rated MEDIUM. Review your exposure and patch according to your risk tolerance.

Which packages are affected by GHSA-mgmh-g2v6-mqw5?

GHSA-mgmh-g2v6-mqw5 affects the following packages: tensorflow (PyPI), tensorflow (PyPI), tensorflow (PyPI), tensorflow-cpu (PyPI), tensorflow-cpu (PyPI), tensorflow-cpu (PyPI), tensorflow-gpu (PyPI), tensorflow-gpu (PyPI), and 1 more. Ecosystems affected: PyPI.

How do I fix GHSA-mgmh-g2v6-mqw5?

Update tensorflow to 2.7.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-mgmh-g2v6-mqw5 is resolved across your whole dependency graph.

How do I detect GHSA-mgmh-g2v6-mqw5 in my PyPI dependencies?

Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

How do I mitigate GHSA-mgmh-g2v6-mqw5 if there is no patch (or I can't update yet)?

If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Is GHSA-mgmh-g2v6-mqw5 actively exploited in the wild?

No public exploit code has been indexed for GHSA-mgmh-g2v6-mqw5 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

What is the EPSS score for GHSA-mgmh-g2v6-mqw5?

GHSA-mgmh-g2v6-mqw5 has an EPSS (Exploit Prediction Scoring System) score of 0.7%, placing it in the 54th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is GHSA-mgmh-g2v6-mqw5?

GHSA-mgmh-g2v6-mqw5 is classified as Reachable Assertion (CWE-617). This weakness type describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation.

When was GHSA-mgmh-g2v6-mqw5 published, and has it been updated?

GHSA-mgmh-g2v6-mqw5 was published on September 16, 2022 and was last updated on July 13, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍

🐍 PyPI

Not in CISA KEV

MEDIUM severity

TensorFlow vulnerable to `CHECK` failure in `AvgPoolOp`GHSA-mgmh-g2v6-mqw5

MEDIUMFix: tensorflow/tensorflow@3a6ac52

GHSA-mgmh-g2v6-mqw5 is a medium-severity (CVSS 5.9) Reachable Assertion vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

Also known asBIT-tensorflow-2022-35941CVE-2022-35941PYSEC-2026-1019PYSEC-2026-3215PYSEC-2026-3351

Published

Sep 16, 2022

Updated

Jul 13, 2026

Affected

9 pkgs

Patched

9 / 9

Exploits

None indexed

Exploitation data as of Oct 31, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for GHSA-mgmh-g2v6-mqw5.

EPSS Exploitation Probability

via FIRST.org ↗

0.7%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs54th percentile — riskier than 54% of all scored CVEsHighest risk

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

Where this sits among everything scored

Real-World Exposure

9 pkgs affected

🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-gpu+1 more

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Impact

The AvgPoolOp function takes an argument ksize that must be positive but is not checked. A negative ksize can trigger a CHECK failure and crash the program.

import tensorflow as tf
import numpy as np

value = np.ones([1, 1, 1, 1])
ksize = [1, 1e20, 1, 1]
strides = [1, 1, 1, 1]
padding = 'SAME'
data_format = 'NHWC'

tf.raw_ops.AvgPool(value=value, ksize=ksize, strides=strides, padding=padding, data_format=data_format)

Patches

We have patched the issue in GitHub commit 3a6ac52664c6c095aa2b114e742b0aa17fdce78f.

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 Jingyi Shi.

Affected Packages

9 total 9 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`tensorflow`	all versions	2.7.2`pip install --upgrade 'tensorflow==2.7.2'`
🐍PyPI	`tensorflow`	≥ 2.8.0&&< 2.8.1	2.8.1`pip install --upgrade 'tensorflow==2.8.1'`
🐍PyPI	`tensorflow`	≥ 2.9.0&&< 2.9.2	2.9.2`pip install --upgrade 'tensorflow==2.9.2'`
🐍PyPI	`tensorflow-cpu`	all versions	2.7.2`pip install --upgrade 'tensorflow-cpu==2.7.2'`
🐍PyPI	`tensorflow-cpu`	≥ 2.8.0&&< 2.8.1	2.8.1`pip install --upgrade 'tensorflow-cpu==2.8.1'`
🐍PyPI	`tensorflow-cpu`	≥ 2.9.0&&< 2.9.2	2.9.2`pip install --upgrade 'tensorflow-cpu==2.9.2'`

Affected Products

1 product · 7 configurations

Application

tensorflowgoogle

≥ 2.9.0 && < 2.9.1

1 version

2.10

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update tensorflow to 2.7.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-mgmh-g2v6-mqw5 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Frequently Asked Questions

### Impact The [`AvgPoolOp`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/avgpooling_op.cc#L56-L98) function takes an argument `ksize` that must be positive but is not checked. A negative `ksize` can trigger a `CHECK` failure and crash the program. ```python import tensorflow as tf import numpy as np value = np.ones([1, 1, 1, 1]) ksize = [1, 1e20, 1, 1] strides = [1, 1, 1, 1] padding = 'SAME' data_format = 'NHWC' tf.raw_ops.AvgPool(value=value, ksize=ksize, strides=strides, padding=padding, data_format=data_format) ``` ### Pa

O3 Security · Impact-Aware SCA

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Find it across PyPI, including transitive dependencies.

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CVSS Score

5.9/10CVSS v3 base

Vector breakdown

Attack Vector

Network

Attack Complexity

High

Privileges Required

None

User Interaction

None

Scope

Unchanged

Confidentiality

None

Integrity

None

Availability

High

Raw vector

CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

CWE Classification

CWE-617Reachable Assertion

Weaponization

No Nuclei template, Metasploit module or public proof-of-concept found.

OpenSSF Scorecard

Package health score

tensorflow

7.7/10

Dependency-Update-Tool10/10

Maintained10/10

Code-Review7/10

Branch-ProtectionN/A

Vulnerabilities0/10

Assessed Oct 31, 2026

Timeline

Disclosed

Sep 16, 2022

Last updated

Jul 13, 2026

Identifiers

GHSA-mgmh-g2v6-mqw5

BIT-tensorflow-2022-35941

PYSEC-2026-1019

PYSEC-2026-3215

References

Advisorynvd.nist.gov · CVE 2022 35941 Webgithub.com · GHSA mgmh g2v6 mqw5 Webgithub.com · 3a6ac52664c6c095aa2b114e742b0aa17fdce78f Webgithub.com · avgpooling op.cc Webgithub.com · v2.10.0 Packagegithub.com · tensorflow

Related vulnerabilities

This CVE is medium severity; 8 of 8 other CVEs affecting tensorflow are rated as high or higher (top: high).

CVE-2023-33976CVE-2023-25661CVE-2023-25670CVE-2023-25665CVE-2023-27579CVE-2023-25673CVE-2023-25663CVE-2023-25658

Provenance

Sources

OSV.devNVDFIRST.org (EPSS)

Last verifiedJul 13, 2026

TensorFlow vulnerable to `CHECK` failure in `AvgPoolOp`GHSA-mgmh-g2v6-mqw5

Exploitation Status

No confirmed exploitation observed yet

EPSS Exploitation Probability

How urgent is this, really

Where this sits among everything scored

Real-World Exposure

Description

Impact

Patches

For more information

Attribution

Affected Packages

Affected Products

Detection & mitigation playbook

Detect

Fix

Workarounds

Frequently Asked Questions

Is GHSA-mgmh-g2v6-mqw5 in your dependencies?