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GHSA-gjh7-xx4r-x345

HIGHFix: tensorflow/tensorflow@6fa05df

GHSA-gjh7-xx4r-x345 is a high-severity (CVSS 7.5) CWE-190 vulnerability in tensorflow. O3 Security confirms whether GHSA-gjh7-xx4r-x345 is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

TensorFlow has segfault in array_ops.upper_bound

Also known asBIT-tensorflow-2023-33976CVE-2023-33976PYSEC-2026-1962PYSEC-2026-3190PYSEC-2026-3331
Published
Jul 30, 2024
Updated
Jul 13, 2026
Affected
3 pkgs
Patched
3 / 3
Exploits
None indexed

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 versions2.12.1
🐍PyPItensorflow-cpuall versions2.12.1
🐍PyPItensorflow-gpuall versions2.12.1

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. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

  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.

  4. How O3 protects you

    O3 pinpoints whether GHSA-gjh7-xx4r-x345 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to GHSA-gjh7-xx4r-x345. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

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

Is GHSA-gjh7-xx4r-x345 in your dependencies?

O3 detects GHSA-gjh7-xx4r-x345 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.