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GHSA-pxrw-j2fv-hx3h

HIGHFix: tensorflow/tensorflow@595a65a

GHSA-pxrw-j2fv-hx3h is a high-severity (CVSS 7) Out-of-bounds Read vulnerability in tensorflow. O3 Security confirms whether GHSA-pxrw-j2fv-hx3h is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

TensorFlow vulnerable to OOB read in `Gather_nd` in TF Lite

Also known asBIT-tensorflow-2022-35937CVE-2022-35937PYSEC-2026-1027PYSEC-2026-3226PYSEC-2026-3359
Published
Sep 16, 2022
Updated
Jul 13, 2026
Affected
9 pkgs
Patched
9 / 9
Exploits
None indexed

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 GatherNd function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read is triggered.

Patches

We have patched the issue in GitHub commit 595a65a3e224a0362d7e68c2213acfc2b499a196.

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 Hui Peng from Baidu Security.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.7.2
🐍PyPItensorflow2.8.0&&< 2.8.12.8.1
🐍PyPItensorflow2.9.0&&< 2.9.12.9.1
🐍PyPItensorflow-cpuall versions2.7.2
🐍PyPItensorflow-cpu2.8.0&&< 2.8.12.8.1
🐍PyPItensorflow-cpu2.9.0&&< 2.9.12.9.1

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 2.7.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-pxrw-j2fv-hx3h 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-pxrw-j2fv-hx3h 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-pxrw-j2fv-hx3h. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Impact The [`GatherNd`](https://github.com/tensorflow/tensorflow/blob/f463040eb3997e42e60a2ffc6dc72de7ef11dbb4/tensorflow/lite/kernels/gather_nd.cc#L105-L111) function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read is triggered. ### Patches We have patched the issue in GitHub commit [595a65a3e224a0362d7e68c2213acfc2b499a196](https://github.com/tensorflow/tensorflow/commit/595a65a3e224a0362d7e68c2213acfc2b499a196). The fix will be included in TensorFlow 2.10.0. We will
O3 Security · Impact-Aware SCA

Is GHSA-pxrw-j2fv-hx3h in your dependencies?

O3 detects GHSA-pxrw-j2fv-hx3h across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.