---
id: CVE-2021-41218
aliases:
  - GHSA-9crf-c6qr-r273
  - BIT-tensorflow-2021-41218
  - PYSEC-2021-410
  - PYSEC-2021-627
  - PYSEC-2021-825
title: Integer division by 0 in `tf.raw_ops.AllToAll`
summary: Integer division by 0 in `tf.raw_ops.AllToAll`
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 >= 2.6.0, < 2.6.1'
  - 'tensorflow >= 2.5.0, < 2.5.2'
  - tensorflow < 2.4.4
  - 'tensorflow-cpu >= 2.6.0, < 2.6.1'
  - 'tensorflow-cpu >= 2.5.0, < 2.5.2'
  - tensorflow-cpu < 2.4.4
  - 'tensorflow-gpu >= 2.6.0, < 2.6.1'
  - 'tensorflow-gpu >= 2.5.0, < 2.5.2'
  - tensorflow-gpu < 2.4.4
patched:
  - tensorflow 2.6.1
  - tensorflow 2.5.2
  - tensorflow 2.4.4
  - tensorflow-cpu 2.6.1
  - tensorflow-cpu 2.5.2
  - tensorflow-cpu 2.4.4
  - tensorflow-gpu 2.6.1
  - tensorflow-gpu 2.5.2
  - tensorflow-gpu 2.4.4
published: '2021-11-10'
updated: '2026-07-08'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-9crf-c6qr-r273'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9crf-c6qr-r273
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2021-41218'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-627.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-825.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-410.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
tags:
  - osv
  - pip
epss: 0.00133
epssPercentile: 0.02281
ingestedAt: '2026-07-08T18:25:47.834Z'
---

## Overview

### Impact
The [shape inference code for `AllToAll`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/tpu_cross_replica_ops.cc#L25-L74) can be made to execute a division by 0:

```python
import tensorflow as tf
  
@tf.function
def func():
  return tf.raw_ops.AllToAll(
    input=[0.0, 0.1652, 0.6543],
    group_assignment=[1, -1],
    concat_dimension=0,
    split_dimension=0,
    split_count=0)

func()
```

This occurs whenever the `split_count` argument is 0:
  
```cc
TF_RETURN_IF_ERROR(c->GetAttr("split_count", &split_count));
...                  
for (int32_t i = 0; i < rank; ++i) {      
  ...                                     
  dims[i] = c->MakeDim(c->Value(dims[i]) / split_count);
  ...                
}
```

### Patches
We have patched the issue in GitHub commit [a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc](https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc).

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 >= 2.6.0, < 2.6.1`
- `tensorflow >= 2.5.0, < 2.5.2`
- `tensorflow < 2.4.4`
- `tensorflow-cpu >= 2.6.0, < 2.6.1`
- `tensorflow-cpu >= 2.5.0, < 2.5.2`
- `tensorflow-cpu < 2.4.4`
- `tensorflow-gpu >= 2.6.0, < 2.6.1`
- `tensorflow-gpu >= 2.5.0, < 2.5.2`
- `tensorflow-gpu < 2.4.4`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.6.1`
- `tensorflow 2.5.2`
- `tensorflow 2.4.4`
- `tensorflow-cpu 2.6.1`
- `tensorflow-cpu 2.5.2`
- `tensorflow-cpu 2.4.4`
- `tensorflow-gpu 2.6.1`
- `tensorflow-gpu 2.5.2`
- `tensorflow-gpu 2.4.4`