Your RSA-2048 keys break in 2030. Find every one of them before attackers do.
🐍
🐍 PyPI
Not in CISA KEV
HIGH severity

GHSA-gf97-q72m-7579 tensorflow

HIGHFix: tensorflow/tensorflow@728113a

GHSA-gf97-q72m-7579 is a high-severity (CVSS 7.5) NULL Pointer Dereference vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

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
Exploitation data as of Sep 19, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
  • 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-gf97-q72m-7579.

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs33th percentile — riskier than 33% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

GHSA-gf97-q72m-7579 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 377,166 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

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

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 versions2.11.1pip install --upgrade 'tensorflow==2.11.1'
🐍PyPItensorflow-cpuall versions2.11.1pip install --upgrade 'tensorflow-cpu==2.11.1'
🐍PyPItensorflow-gpuall versions2.11.1pip install --upgrade 'tensorflow-gpu==2.11.1'

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, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  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 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-gf97-q72m-7579 can be triaged on real exposure rather than presence alone.

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 Security finds GHSA-gf97-q72m-7579 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-gf97-q72m-7579: tensorflow (High 7.5) | O3 Security