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MEDIUM severity

GHSA-hq7g-wwwp-q46h tensorflow

MEDIUMFix: tensorflow/tensorflow@af4a6a3

GHSA-hq7g-wwwp-q46h is a medium-severity (CVSS 4.8) Improper Input Validation vulnerability in tensorflow. 1 public exploit reference exists, so weaponization risk is real. A fix is available for tensorflow — see the affected versions and patch details below.

`CHECK` fail via inputs in `SparseFillEmptyRowsGrad`

Also known asBIT-tensorflow-2022-41898CVE-2022-41898PYSEC-2026-1008PYSEC-2026-3201PYSEC-2026-3340
Published
Nov 21, 2022
Updated
Jul 13, 2026
Affected
9 pkgs
Patched
9 / 9
Exploits
1 known
Exploitation data as of Sep 19, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.

Exploitation and automatability from CISA’s SSVC triage for GHSA-hq7g-wwwp-q46h.

EPSS Exploitation Probability

via FIRST.org ↗
0.5%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs40th percentile — riskier than 40% 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-hq7g-wwwp-q46h 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

9 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-cpu+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

If SparseFillEmptyRowsGrad is given empty inputs, TensorFlow will crash.

import tensorflow as tf
tf.raw_ops.SparseFillEmptyRowsGrad(
    reverse_index_map=[], grad_values=[], name=None
)

Patches

We have patched the issue in GitHub commit af4a6a3c8b95022c351edae94560acc61253a1b8.

The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Jiawei Liu, PhD student at University of Illinois, Urbana-Champaign.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.8.4pip install --upgrade 'tensorflow==2.8.4'
🐍PyPItensorflow2.9.0&&< 2.9.32.9.3pip install --upgrade 'tensorflow==2.9.3'
🐍PyPItensorflow2.10.0&&< 2.10.12.10.1pip install --upgrade 'tensorflow==2.10.1'
🐍PyPItensorflow-cpuall versions2.8.4pip install --upgrade 'tensorflow-cpu==2.8.4'
🐍PyPItensorflow-gpuall versions2.8.4pip install --upgrade 'tensorflow-gpu==2.8.4'
🐍PyPItensorflow-cpu2.9.0&&< 2.9.32.9.3pip install --upgrade 'tensorflow-cpu==2.9.3'
Exploits & PoCs
1

Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.

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 2.8.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-hq7g-wwwp-q46h 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-hq7g-wwwp-q46h can be triaged on real exposure rather than presence alone.

Tailored to GHSA-hq7g-wwwp-q46h. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Impact If [`SparseFillEmptyRowsGrad`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/sparse_fill_empty_rows_op_gpu.cu.cc) is given empty inputs, TensorFlow will crash. ```python import tensorflow as tf tf.raw_ops.SparseFillEmptyRowsGrad( reverse_index_map=[], grad_values=[], name=None ) ``` ### Patches We have patched the issue in GitHub commit [af4a6a3c8b95022c351edae94560acc61253a1b8](https://github.com/tensorflow/tensorflow/commit/af4a6a3c8b95022c351edae94560acc61253a1b8). The fix will be included in TensorFlow 2.11. We will also cherrypick this comm
O3 Security · Impact-Aware SCA

Is GHSA-hq7g-wwwp-q46h in your dependencies?

O3 Security finds GHSA-hq7g-wwwp-q46h across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-hq7g-wwwp-q46h: tensorflow | O3 Security