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🐍 PyPI

CVE-2022-41883

MEDIUM

Out of bounds segmentation fault due to unequal op inputs in Tensorflow

Also known asBIT-tensorflow-2022-41883GHSA-w58w-79xv-6vcj
Published
Nov 18, 2022
Updated
Apr 2, 2026
Affected
3 pkgs
Patched
3 / 3
Exploits
1 known

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk27th percentile+0.17%
0.00%0.28%0.57%0.85%0.2%0.4%Dec 25Apr 26Jun 26

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.

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

TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. 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.

Affected Packages

3 total 3 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflow2.10.0&&< 2.10.12.10.1
🐍PyPItensorflow-cpu2.10.0&&< 2.10.12.10.1
🐍PyPItensorflow-gpu2.10.0&&< 2.10.12.10.1
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. 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 2.10.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2022-41883 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 CVE-2022-41883 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 CVE-2022-41883. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. 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.
O3 Security · Impact-Aware SCA

Is CVE-2022-41883 in your dependencies?

O3 detects CVE-2022-41883 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.