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CVE-2022-35974

MEDIUM

CVE-2022-35974 is a medium-severity (CVSS 5.9) Improper Input Validation vulnerability in tensorflow. O3 Security confirms whether CVE-2022-35974 is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

Segfault in `QuantizeDownAndShrinkRange` in TensorFlow

Also known asBIT-tensorflow-2022-35974GHSA-vgvh-2pf4-jr2xPYSEC-2026-1039PYSEC-2026-3246PYSEC-2026-3373
Published
Sep 16, 2022
Updated
Jul 22, 2026
Affected
9 pkgs
Patched
9 / 9
Exploits
None indexed

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. If QuantizeDownAndShrinkRange is given nonscalar inputs for input_min or input_max, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. 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-2022-35974 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-2022-35974 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-2022-35974. 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. If `QuantizeDownAndShrinkRange` is given nonscalar inputs for `input_min` or `input_max`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. 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-2022-35974 in your dependencies?

O3 detects CVE-2022-35974 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.