---
id: CVE-2022-21725
aliases:
  - GHSA-v3f7-j968-4h5f
  - BIT-tensorflow-2022-21725
  - PYSEC-2022-104
  - PYSEC-2022-49
  - PYSEC-2026-3242
title: Division by zero in Tensorflow
summary: Division by zero in Tensorflow
severity: medium
cvss: 6.5
cvssVector: 'CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - tensorflow < 2.5.3
  - 'tensorflow >= 2.6.0, < 2.6.3'
  - 'tensorflow >= 2.7.0, < 2.7.1'
  - tensorflow-cpu < 2.5.3
  - 'tensorflow-cpu >= 2.6.0, < 2.6.3'
  - 'tensorflow-cpu >= 2.7.0, < 2.7.1'
  - tensorflow-gpu < 2.5.3
  - 'tensorflow-gpu >= 2.6.0, < 2.6.3'
  - 'tensorflow-gpu >= 2.7.0, < 2.7.1'
patched:
  - tensorflow 2.5.3
  - tensorflow 2.6.3
  - tensorflow 2.7.1
  - tensorflow-cpu 2.5.3
  - tensorflow-cpu 2.6.3
  - tensorflow-cpu 2.7.1
  - tensorflow-gpu 2.5.3
  - tensorflow-gpu 2.6.3
  - tensorflow-gpu 2.7.1
published: '2022-02-10'
updated: '2026-07-13'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-v3f7-j968-4h5f'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v3f7-j968-4h5f
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2022-21725'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/3218043d6d3a019756607643cf65574fbfef5d7a
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-49.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-104.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
  - url: >-
      https://github.com/tensorflow/tensorflow/blob/ffa202a17ab7a4a10182b746d230ea66f021fe16/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L189-L198
tags:
  - osv
  - pip
epss: 0.00789
epssPercentile: 0.543
ingestedAt: '2026-07-13T18:58:03.127Z'
---

## Overview

### 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 to check that the stride argument is stricly positive:

```cc
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](https://github.com/tensorflow/tensorflow/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](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) 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

- `tensorflow < 2.5.3`
- `tensorflow >= 2.6.0, < 2.6.3`
- `tensorflow >= 2.7.0, < 2.7.1`
- `tensorflow-cpu < 2.5.3`
- `tensorflow-cpu >= 2.6.0, < 2.6.3`
- `tensorflow-cpu >= 2.7.0, < 2.7.1`
- `tensorflow-gpu < 2.5.3`
- `tensorflow-gpu >= 2.6.0, < 2.6.3`
- `tensorflow-gpu >= 2.7.0, < 2.7.1`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.5.3`
- `tensorflow 2.6.3`
- `tensorflow 2.7.1`
- `tensorflow-cpu 2.5.3`
- `tensorflow-cpu 2.6.3`
- `tensorflow-cpu 2.7.1`
- `tensorflow-gpu 2.5.3`
- `tensorflow-gpu 2.6.3`
- `tensorflow-gpu 2.7.1`