Your RSA-2048 keys break in 2030. Find every one of them before attackers do.
🐍 PyPI

CVE-2022-36014

MEDIUM

CVE-2022-36014 is a medium-severity (CVSS 5.9) NULL Pointer Dereference vulnerability in tensorflow. O3 Security confirms whether CVE-2022-36014 is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

Null-dereference in `mlir::tfg::TFOp::nameAttr` in TensorFlow

Also known asBIT-tensorflow-2022-36014GHSA-7j3m-8g3c-9qqqPYSEC-2026-3129PYSEC-2026-3292PYSEC-2026-966
Published
Sep 16, 2022
Updated
Jul 22, 2026
Affected
9 pkgs
Patched
9 / 9
Exploits
None indexed

EPSS Exploitation Probability

via FIRST.org ↗
0.6%probability of exploitation in next 30 days
Lower Risk44th percentile+0.02%
0.00%0.36%0.72%1.08%0.3%0.6%Feb 26May 26Jul 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

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

TensorFlow is an open source platform for machine learning. When mlir::tfg::TFOp::nameAttr receives null type list attributes, it crashes. We have patched the issue in GitHub commits 3a754740d5414e362512ee981eefba41561a63a6 and a0f0b9a21c9270930457095092f558fbad4c03e5. 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. There are no known workarounds for this issue.

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 CVE-2022-36014 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-2022-36014 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-2022-36014. 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 `mlir::tfg::TFOp::nameAttr` receives null type list attributes, it crashes. We have patched the issue in GitHub commits 3a754740d5414e362512ee981eefba41561a63a6 and a0f0b9a21c9270930457095092f558fbad4c03e5. 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. There are no known workarounds for this issue.
O3 Security · Impact-Aware SCA

Is CVE-2022-36014 in your dependencies?

O3 detects CVE-2022-36014 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.