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HIGH severity

TensorFlow has segfault in array_ops.upper_boundGHSA-gjh7-xx4r-x345

HIGHFix: tensorflow/tensorflow@6fa05df

GHSA-gjh7-xx4r-x345 is a high-severity (CVSS 7.5) CWE-190 vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

Also known asBIT-tensorflow-2023-33976CVE-2023-33976PYSEC-2026-1962PYSEC-2026-3190PYSEC-2026-3331
Published
Updated
Affected
3 pkgs
Patched
3 / 3
Exploits
None indexed
Exploitation data as of Nov 9, 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-gjh7-xx4r-x345.

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs38th percentile — riskier than 38% of all scored CVEsHighest risk
0.00%0.31%0.62%0.93%0.0%0.4%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

3 pkgs affected
🐍tensorflow🐍tensorflow-cpu🐍tensorflow-gpu

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

array_ops.upper_bound causes a segfault when not given a rank 2 tensor.

Patches

We have patched the issue in GitHub commit 915884fdf5df34aaedd00fc6ace33a2cfdefa586.

The fix will be included in TensorFlow 2.13. We will also cherrypick this commit in TensorFlow 2.12.1.

For more information

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

Attribution

This vulnerability has been reported by dmc1778

Affected Packages

3 total 3 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.12.1pip install --upgrade 'tensorflow==2.12.1'
🐍PyPItensorflow-cpuall versions2.12.1pip install --upgrade 'tensorflow-cpu==2.12.1'
🐍PyPItensorflow-gpuall versions2.12.1pip install --upgrade 'tensorflow-gpu==2.12.1'

Affected Products

1 product · 1 configurations
Application
tensorflowgoogle
< 2.13.0
range

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 2.12.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-gjh7-xx4r-x345 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 `array_ops.upper_bound` causes a segfault when not given a rank 2 tensor. ### Patches We have patched the issue in GitHub commit [915884fdf5df34aaedd00fc6ace33a2cfdefa586](https://github.com/tensorflow/tensorflow/commit/915884fdf5df34aaedd00fc6ace33a2cfdefa586). The fix will be included in TensorFlow 2.13. We will also cherrypick this commit in TensorFlow 2.12.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and ques
O3 Security · Impact-Aware SCA

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TensorFlow has segfault in array_ops.upper_bound