---
id: CVE-2022-23557
aliases:
  - GHSA-gf2j-f278-xh4v
  - BIT-tensorflow-2022-23557
  - PYSEC-2022-121
  - PYSEC-2022-66
  - PYSEC-2026-3188
title: Division by zero in TFLite
summary: Division by zero in TFLite
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: '2022-02-09'
updated: '2026-07-13'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-gf2j-f278-xh4v'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf2j-f278-xh4v
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2022-23557'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-66.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-121.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
  - url: >-
      https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75
tags:
  - osv
  - pip
epss: 0.00763
epssPercentile: 0.5341
ingestedAt: '2026-07-13T18:57:58.294Z'
---

## Overview

### Impact 
An attacker can craft a TFLite model that would trigger a division by zero in [`BiasAndClamp` implementation](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75):

```cc
inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size,
                         const float* bias_data, int array_size,
                         float* array_data) {
  // ...
  TFLITE_DCHECK_EQ((array_size % bias_size), 0);
  // ...
} 
```
  
There is no check that the `bias_size` is non zero.
  
### Patches
We have patched the issue in GitHub commit [8c6f391a2282684a25cbfec7687bd5d35261a209](https://github.com/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209).

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 Wang Xuan 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`