---
id: CVE-2021-37660
aliases:
  - GHSA-cm5x-837x-jf3c
  - BIT-tensorflow-2021-37660
  - PYSEC-2021-282
  - PYSEC-2021-573
  - PYSEC-2021-771
title: Division by 0 in inplace operations
summary: Division by 0 in inplace operations
severity: medium
cvss: 5.5
cvssVector: 'CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - tensorflow < 2.3.4
  - 'tensorflow >= 2.4.0, < 2.4.3'
  - 'tensorflow >= 2.5.0, < 2.5.1'
  - tensorflow-cpu < 2.3.4
  - 'tensorflow-cpu >= 2.4.0, < 2.4.3'
  - 'tensorflow-cpu >= 2.5.0, < 2.5.1'
  - tensorflow-gpu < 2.3.4
  - 'tensorflow-gpu >= 2.4.0, < 2.4.3'
  - 'tensorflow-gpu >= 2.5.0, < 2.5.1'
patched:
  - tensorflow 2.3.4
  - tensorflow 2.4.3
  - tensorflow 2.5.1
  - tensorflow-cpu 2.3.4
  - tensorflow-cpu 2.4.3
  - tensorflow-cpu 2.5.1
  - tensorflow-gpu 2.3.4
  - tensorflow-gpu 2.4.3
  - tensorflow-gpu 2.5.1
published: '2021-08-25'
updated: '2026-07-08'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-cm5x-837x-jf3c'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cm5x-837x-jf3c
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2021-37660'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-573.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-771.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-282.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
tags:
  - osv
  - pip
epss: 0.00154
epssPercentile: 0.03846
ingestedAt: '2026-07-08T18:25:48.407Z'
---

## Overview

### Impact
An attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0:

```python
import tensorflow as tf

tf.raw_ops.InplaceSub(x=[],i=[-99,-1,-1],v=[1,1,1])
```

The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/inplace_ops.cc#L283) has a logic error: it should skip processing if `x` and `v` are empty but the code uses `||` instead of `&&`.

### Patches
We have patched the issue in GitHub commit [e86605c0a336c088b638da02135ea6f9f6753618](https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618).

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 members of the Aivul Team from Qihoo 360.

## Affected packages

- `tensorflow < 2.3.4`
- `tensorflow >= 2.4.0, < 2.4.3`
- `tensorflow >= 2.5.0, < 2.5.1`
- `tensorflow-cpu < 2.3.4`
- `tensorflow-cpu >= 2.4.0, < 2.4.3`
- `tensorflow-cpu >= 2.5.0, < 2.5.1`
- `tensorflow-gpu < 2.3.4`
- `tensorflow-gpu >= 2.4.0, < 2.4.3`
- `tensorflow-gpu >= 2.5.0, < 2.5.1`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.3.4`
- `tensorflow 2.4.3`
- `tensorflow 2.5.1`
- `tensorflow-cpu 2.3.4`
- `tensorflow-cpu 2.4.3`
- `tensorflow-cpu 2.5.1`
- `tensorflow-gpu 2.3.4`
- `tensorflow-gpu 2.4.3`
- `tensorflow-gpu 2.5.1`