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GHSA-gf97-q72m-7579

HIGH

GHSA-gf97-q72m-7579 is a high-severity (CVSS 7.5) NULL Pointer Dereference vulnerability in tensorflow. O3 Security confirms whether GHSA-gf97-q72m-7579 is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

TensorFlow has Null Pointer Error in RandomShuffle with XLA enable

Also known asBIT-tensorflow-2023-25674CVE-2023-25674PYSEC-2026-3189PYSEC-2026-3330PYSEC-2026-999
Published
Mar 24, 2023
Updated
Jul 13, 2026
Affected
3 pkgs
Patched
3 / 3
Exploits
None indexed

Blast Radius

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

NPE in RandomShuffle with XLA enable

import tensorflow as tf

func = tf.raw_ops.RandomShuffle
para = {'value': 1e+20, 'seed': -4294967297, 'seed2': -2147483649}

@tf.function(jit_compile=True)
def test():
   y = func(**para)
   return y

test()

Patches

We have patched the issue in GitHub commit 728113a3be690facad6ce436660a0bc1858017fa.

The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1

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 r3pwnx

Affected Packages

3 total 3 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.11.1
🐍PyPItensorflow-cpuall versions2.11.1
🐍PyPItensorflow-gpuall versions2.11.1

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 2.11.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-gf97-q72m-7579 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-gf97-q72m-7579 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-gf97-q72m-7579. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Impact NPE in RandomShuffle with XLA enable ```python import tensorflow as tf func = tf.raw_ops.RandomShuffle para = {'value': 1e+20, 'seed': -4294967297, 'seed2': -2147483649} @tf.function(jit_compile=True) def test(): y = func(**para) return y test() ``` ### Patches We have patched the issue in GitHub commit [728113a3be690facad6ce436660a0bc1858017fa](https://github.com/tensorflow/tensorflow/commit/728113a3be690facad6ce436660a0bc1858017fa). The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1 ### For more information Please
O3 Security · Impact-Aware SCA

Is GHSA-gf97-q72m-7579 in your dependencies?

O3 detects GHSA-gf97-q72m-7579 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.