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MEDIUM severity

Integer Overflow or Wraparound in TensorFlowGHSA-wcv5-vrvr-3rx2

MEDIUMFix: tensorflow/tensorflow@be7b286

GHSA-wcv5-vrvr-3rx2 is a medium-severity (CVSS 5.5) vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

Published
Updated
Affected
9 pkgs
Patched
9 / 9
Exploits
None indexed
Exploitation data as of Dec 5, 2024 · OSV.dev, FIRST.org (EPSS)

Real-World Exposure

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 versions2.5.3pip install --upgrade 'tensorflow==2.5.3'
🐍PyPItensorflow≥ 2.6.0&&< 2.6.32.6.3pip install --upgrade 'tensorflow==2.6.3'
🐍PyPItensorflow≥ 2.7.0&&< 2.7.12.7.1pip install --upgrade 'tensorflow==2.7.1'
🐍PyPItensorflow-cpuall versions2.5.3pip install --upgrade 'tensorflow-cpu==2.5.3'
🐍PyPItensorflow-cpu≥ 2.6.0&&< 2.6.32.6.3pip install --upgrade 'tensorflow-cpu==2.6.3'
🐍PyPItensorflow-cpu≥ 2.7.0&&< 2.7.12.7.1pip install --upgrade 'tensorflow-cpu==2.7.1'

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, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  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

    Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

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

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Integer Overflow or Wraparound in TensorFlow