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MEDIUM severity

CVE-2022-21725 — tensorflow

MEDIUMFix: tensorflow/tensorflow@3218043

CVE-2022-21725 is a medium-severity (CVSS 6.5) CWE-369 vulnerability in tensorflow. 1 public exploit reference exists, so weaponization risk is real. A fix is available for tensorflow — see the affected versions and patch details below.

Division by zero in Tensorflow

Also known asBIT-tensorflow-2022-21725GHSA-v3f7-j968-4h5fPYSEC-2022-104PYSEC-2022-49PYSEC-2026-3242
Published
Updated
Affected
9 pkgs
Patched
9 / 9
Exploits
1 known
Exploitation data as of Oct 7, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.

Exploitation and automatability from CISA’s SSVC triage for CVE-2022-21725.

EPSS Exploitation Probability

via FIRST.org ↗
0.8%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs55th percentile — riskier than 55% of all scored CVEsHighest risk
0.00%0.43%0.86%1.29%0.2%0.8%Apr 26Jul 26Oct 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

CVE-2022-21725 by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.

Where this sits among everything scored

Of 385,386 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Counts from FIRST.org, log-scaled.

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 estimator for the cost of some convolution operations can be made to execute a division by 0:

import tensorflow as tf

@tf.function
def test():
  y=tf.raw_ops.AvgPoolGrad(
    orig_input_shape=[1,1,1,1],
    grad=[[[[1.0],[1.0],[1.0]]],[[[2.0],[2.0],[2.0]]],[[[3.0],[3.0],[3.0]]]],
    ksize=[1,1,1,1],
    strides=[1,1,1,0],
    padding='VALID',
    data_format='NCHW')
  return y

test()

The function fails to check that the stride argument is stricly positive:

int64_t GetOutputSize(const int64_t input, const int64_t filter,
                      const int64_t stride, const Padding& padding) {
  // Logic for calculating output shape is from GetWindowedOutputSizeVerbose() 
  // function in third_party/tensorflow/core/framework/common_shape_fns.cc.
  if (padding == Padding::VALID) {
    return (input - filter + stride) / stride;
  } else {  // SAME.
    return (input + stride - 1) / stride;
  }
} 

Hence, the fix is to add a check for the stride argument to ensure it is valid.

Patches

We have patched the issue in GitHub commit 3218043d6d3a019756607643cf65574fbfef5d7a.

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.

Attribution

This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.

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'

Affected Products

1 product · 3 configurations
Application
tensorflowgoogle
≥ 2.6.0 && ≤ 2.6.2
1 version
2.7.0
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, 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 CVE-2022-21725 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.

Frequently Asked Questions

### Impact The [estimator for the cost of some convolution operations](https://github.com/tensorflow/tensorflow/blob/ffa202a17ab7a4a10182b746d230ea66f021fe16/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L189-L198) can be made to execute a division by 0: ```python import tensorflow as tf @tf.function def test(): y=tf.raw_ops.AvgPoolGrad( orig_input_shape=[1,1,1,1], grad=[[[[1.0],[1.0],[1.0]]],[[[2.0],[2.0],[2.0]]],[[[3.0],[3.0],[3.0]]]], ksize=[1,1,1,1], strides=[1,1,1,0], padding='VALID', data_format='NCHW') return y test() ``` The function fails t
O3 Security · Impact-Aware SCA

Is CVE-2022-21725 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2022-21725: tensorflow — Fixed in 2.5.3