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GHSA-wcv5-vrvr-3rx2

MEDIUM

Integer Overflow or Wraparound in TensorFlow

Published
Feb 9, 2022
Updated
Dec 5, 2024
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

Impact

The Grappler component of TensorFlow is vulnerable to a denial of service via CHECK-failure (assertion failure) in constant folding:

  for (const auto& output_prop : output_props) {
    const PartialTensorShape output_shape(output_prop.shape());
    // ...
  }

The output_prop tensor has a shape that is controlled by user input and this can result in triggering one of the CHECKs in the PartialTensorShape constructor. This is an instance of TFSA-2021-198 (CVE-2021-41197).

Patches

We have patched the issue in GitHub commit be7b286d40bc68cb0b56f702186cc4837d508058.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.5.3
🐍PyPItensorflow≥ 2.6.0&&< 2.6.32.6.3
🐍PyPItensorflow≥ 2.7.0&&< 2.7.12.7.1
🐍PyPItensorflow-cpuall versions2.5.3
🐍PyPItensorflow-cpu≥ 2.6.0&&< 2.6.32.6.3
🐍PyPItensorflow-cpu≥ 2.7.0&&< 2.7.12.7.1

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 2.5.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-wcv5-vrvr-3rx2 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 GHSA-wcv5-vrvr-3rx2 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 GHSA-wcv5-vrvr-3rx2. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Impact The Grappler component of TensorFlow is vulnerable to a denial of service via `CHECK`-failure (assertion failure) in [constant folding](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/constant_folding.cc#L963-L1035): ```cc for (const auto& output_prop : output_props) { const PartialTensorShape output_shape(output_prop.shape()); // ... } ``` The `output_prop` tensor has a shape that is controlled by user input and this can result in triggering one of the `CHECK`s in the `PartialTensorShape` con
O3 Security · Impact-Aware SCA

Is GHSA-wcv5-vrvr-3rx2 in your dependencies?

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