How severe is GHSA-xvwp-h6jv-7472?

GHSA-xvwp-h6jv-7472 has a CVSS score of 7.1/10, rated HIGH. Immediate patching is strongly recommended.

Which packages are affected by GHSA-xvwp-h6jv-7472?

GHSA-xvwp-h6jv-7472 affects the following packages: tensorflow (PyPI), tensorflow (PyPI), tensorflow (PyPI), tensorflow-cpu (PyPI), tensorflow-gpu (PyPI), tensorflow-cpu (PyPI), tensorflow-gpu (PyPI), tensorflow-cpu (PyPI), and 1 more. Ecosystems affected: PyPI.

How do I fix GHSA-xvwp-h6jv-7472?

Update tensorflow to 2.8.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-xvwp-h6jv-7472 is resolved across your whole dependency graph.

How do I detect GHSA-xvwp-h6jv-7472 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-xvwp-h6jv-7472 if there is no patch (or I can't update yet)?

Constrain what reaches the vulnerable code: limit the size and shape of untrusted input, isolate the affected component in a sandboxed or least-privileged process, and enable the platform's memory-safety mitigations (ASLR, stack protector, hardened allocator) so an out-of-bounds access is more likely to fail closed than to be exploitable.

Is GHSA-xvwp-h6jv-7472 actively exploited in the wild?

Yes. There are 1 known exploit references for GHSA-xvwp-h6jv-7472, including 1 in-the-wild exploitation observed on GitHub and other sources. Treat this as actively exploitable and prioritize patching immediately. All exploit code should only be run in an isolated sandbox environment for research or authorized testing — never against production systems without explicit written authorization.

What is the EPSS score for GHSA-xvwp-h6jv-7472?

GHSA-xvwp-h6jv-7472 has an EPSS (Exploit Prediction Scoring System) score of 0.7%, placing it in the 52th 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-xvwp-h6jv-7472?

GHSA-xvwp-h6jv-7472 is classified as Out-of-bounds Read (CWE-125), Out-of-bounds Write (CWE-787). These weakness types describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation.

When was GHSA-xvwp-h6jv-7472 published, and has it been updated?

GHSA-xvwp-h6jv-7472 was published on November 21, 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

HIGH severity

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acessGHSA-xvwp-h6jv-7472

HIGHFix: tensorflow/tensorflow@2165251

GHSA-xvwp-h6jv-7472 is a high-severity (CVSS 7.1) Out-of-bounds Read vulnerability in tensorflow. 1 public exploit or proof-of-concept reference is indexed, so weaponization risk is real. A fix is available for tensorflow — see the affected versions and patch details below.

Also known asBIT-tensorflow-2022-41900CVE-2022-41900PYSEC-2026-1049PYSEC-2026-3261PYSEC-2026-3383

Published

Nov 21, 2022

Updated

Jul 13, 2026

Affected

9 pkgs

Patched

9 / 9

Exploits

1 known

Exploitation data as of Nov 5, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

EPSS Exploitation Probability

via FIRST.org ↗

0.7%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs52th percentile — riskier than 52% 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-gpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-cpu+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

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.

Affected Packages

9 total 9 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`tensorflow`	all versions	2.8.4`pip install --upgrade 'tensorflow==2.8.4'`
🐍PyPI	`tensorflow`	≥ 2.9.0&&< 2.9.3	2.9.3`pip install --upgrade 'tensorflow==2.9.3'`
🐍PyPI	`tensorflow`	≥ 2.10.0&&< 2.10.1	2.10.1`pip install --upgrade 'tensorflow==2.10.1'`
🐍PyPI	`tensorflow-cpu`	all versions	2.8.4`pip install --upgrade 'tensorflow-cpu==2.8.4'`
🐍PyPI	`tensorflow-gpu`	all versions	2.8.4`pip install --upgrade 'tensorflow-gpu==2.8.4'`
🐍PyPI	`tensorflow-cpu`	≥ 2.9.0&&< 2.9.3	2.9.3`pip install --upgrade 'tensorflow-cpu==2.9.3'`

Affected Products

1 product · 3 configurations

Application

tensorflowgoogle

≥ 2.9.0 && < 2.9.3

1 version

2.10.0

Exploits & PoCs

Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.

TensorFlow is an open source platform for machine learning. The security…

github.comNVDNov 2022

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 2.8.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-xvwp-h6jv-7472 is resolved across your whole dependency graph.
Workarounds
Constrain what reaches the vulnerable code: limit the size and shape of untrusted input, isolate the affected component in a sandboxed or least-privileged process, and enable the platform's memory-safety mitigations (ASLR, stack protector, hardened allocator) so an out-of-bounds access is more likely to fail closed than to be exploitable.

Frequently Asked Questions

### Impact An input `pooling_ratio` that is smaller than 1 will trigger a heap OOB in [`tf.raw_ops.FractionalMaxPool`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/fractional_max_pool_op.cc) and [`tf.raw_ops.FractionalAvgPool`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/fractional_avg_pool_op.cc). ### Patches We have patched the issue in GitHub commit [216525144ee7c910296f5b05d214ca1327c9ce48](https://github.com/tensorflow/tensorflow/commit/216525144ee7c910296f5b05d214ca1327c9ce48). The fix will be included in TensorFlow 2.11.

O3 Security · Impact-Aware SCA

Is GHSA-xvwp-h6jv-7472 in your dependencies?

Find it across PyPI, including transitive dependencies.

Scan my dependencies How O3 SCA works

CVSS Score

7.1/10CVSS v3 base

Vector breakdown

Attack Vector

Network

Attack Complexity

High

Privileges Required

Low

User Interaction

Required

Scope

Unchanged

Confidentiality

High

Integrity

High

Availability

High

Raw vector

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

CWE Classification

CWE-125Out-of-bounds Read CWE-787Out-of-bounds Write

Weaponization

No Nuclei template or Metasploit module yet. 1 public proof-of-concept reference is listed on this page.

Timeline

Disclosed

Nov 21, 2022

First exploit

Nov 23, 2022

2 days after disclosure — rapid exploitation

Last updated

Jul 13, 2026

Identifiers

GHSA-xvwp-h6jv-7472

BIT-tensorflow-2022-41900

PYSEC-2026-1049

PYSEC-2026-3261

References

Advisorynvd.nist.gov · CVE 2022 41900 Webgithub.com · GHSA xvwp h6jv 7472 Webgithub.com · 216525144ee7c910296f5b05d214ca1327c9ce48 Packagegithub.com · tensorflow

Related vulnerabilities

This CVE is high severity; 7 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

FractionalMaxPool and FractionalAVGPool heap out-of-bounds acessGHSA-xvwp-h6jv-7472

EPSS Exploitation Probability

How urgent is this, really

Where this sits among everything scored

Real-World Exposure

Description

Impact

Patches

For more information

Affected Packages

Affected Products

Detection & mitigation playbook

Detect

Fix

Workarounds

Frequently Asked Questions

Is GHSA-xvwp-h6jv-7472 in your dependencies?