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MEDIUM severity

Undefined behavior when users supply invalid resource handlesGHSA-5wpj-c6f7-24x8

MEDIUMFix: tensorflow/tensorflow@a5b89cd

GHSA-5wpj-c6f7-24x8 is a medium-severity (CVSS 5.5) Improper Input Validation 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-2022-29207CVE-2022-29207PYSEC-2026-3112PYSEC-2026-3280PYSEC-2026-955
Published
Updated
Affected
9 pkgs
Patched
9 / 9
Exploits
1 known
Exploitation data as of Nov 10, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.

Exploitation and automatability from CISA’s SSVC triage for GHSA-5wpj-c6f7-24x8.

EPSS Exploitation Probability

via FIRST.org ↗
0.3%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs26th percentile — riskier than 26% of all scored CVEsHighest risk
0.00%0.28%0.55%0.83%0.1%0.3%May 26Sep 26Nov 26

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

Multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid:

import tensorflow as tf

tf.raw_ops.QueueIsClosedV2(handle=[])

import tensorflow as tf

tf.summary.flush(writer=())

In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior.

Patches

We have patched the issue in GitHub commit a5b89cd68c02329d793356bda85d079e9e69b4e7 and GitHub commit dbdd98c37bc25249e8f288bd30d01e118a7b4498.

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Hong Jin from Singapore Management University.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.6.4pip install --upgrade 'tensorflow==2.6.4'
🐍PyPItensorflow≥ 2.7.0&&< 2.7.22.7.2pip install --upgrade 'tensorflow==2.7.2'
🐍PyPItensorflow≥ 2.8.0&&< 2.8.12.8.1pip install --upgrade 'tensorflow==2.8.1'
🐍PyPItensorflow-cpuall versions2.6.4pip install --upgrade 'tensorflow-cpu==2.6.4'
🐍PyPItensorflow-cpu≥ 2.7.0&&< 2.7.22.7.2pip install --upgrade 'tensorflow-cpu==2.7.2'
🐍PyPItensorflow-cpu≥ 2.8.0&&< 2.8.12.8.1pip install --upgrade 'tensorflow-cpu==2.8.1'

Affected Products

1 product · 9 configurations
Application
tensorflowgoogle
≥ 2.7.0 && < 2.7.2
3 versions
2.7.02.8.02.9.0
Exploits & PoCs
1

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. Prior to ver…

github.comNVDJun 2022

Detection & mitigation playbook

Open-source dependency

  1. 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.

  2. Fix

    Update tensorflow to 2.6.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-5wpj-c6f7-24x8 is resolved across your whole dependency graph.

  3. 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 Multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid: ```python import tensorflow as tf tf.raw_ops.QueueIsClosedV2(handle=[]) ``` ```python import tensorflow as tf tf.summary.flush(writer=()) ``` In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. ### Patches We have patched the issue i
O3 Security · Impact-Aware SCA

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