---
id: CVE-2021-29554
aliases:
  - GHSA-qg48-85hg-mqc5
  - BIT-tensorflow-2021-29554
  - PYSEC-2021-191
  - PYSEC-2021-482
  - PYSEC-2021-680
title: Division by 0 in `DenseCountSparseOutput`
summary: Division by 0 in `DenseCountSparseOutput`
severity: low
cvss: 2.5
cvssVector: 'CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - 'tensorflow >= 2.3.0, < 2.3.3'
  - 'tensorflow >= 2.4.0, < 2.4.2'
  - 'tensorflow-cpu >= 2.3.0, < 2.3.3'
  - 'tensorflow-cpu >= 2.4.0, < 2.4.2'
  - 'tensorflow-gpu >= 2.3.0, < 2.3.3'
  - 'tensorflow-gpu >= 2.4.0, < 2.4.2'
patched:
  - tensorflow 2.3.3
  - tensorflow 2.4.2
  - tensorflow-cpu 2.3.3
  - tensorflow-cpu 2.4.2
  - tensorflow-gpu 2.3.3
  - tensorflow-gpu 2.4.2
published: '2021-05-21'
updated: '2026-07-08'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-qg48-85hg-mqc5'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2021-29554'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-482.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-680.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-191.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
tags:
  - osv
  - pip
epss: 0.00189
epssPercentile: 0.0879
ingestedAt: '2026-07-08T18:25:52.410Z'
---

## Overview

### Impact
An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`:

```python
import tensorflow as tf

values = tf.constant([], shape=[0, 0], dtype=tf.int64)
weights = tf.constant([])

tf.raw_ops.DenseCountSparseOutput(
  values=values, weights=weights,
  minlength=-1, maxlength=58, binary_output=True)
```
  
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division:

```cc
int num_batch_elements = 1;
for (int i = 0; i < num_batch_dimensions; ++i) {
  num_batch_elements *= data.shape().dim_size(i);
}
int num_value_elements = data.shape().num_elements() / num_batch_elements;
```

Since `data` is given by the `values` argument, `num_batch_elements` is 0.

### Patches
We have patched the issue in GitHub commit [da5ff2daf618591f64b2b62d9d9803951b945e9f](https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f).

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected.

### 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 Yakun Zhang and Ying Wang of Baidu X-Team.

## Affected packages

- `tensorflow >= 2.3.0, < 2.3.3`
- `tensorflow >= 2.4.0, < 2.4.2`
- `tensorflow-cpu >= 2.3.0, < 2.3.3`
- `tensorflow-cpu >= 2.4.0, < 2.4.2`
- `tensorflow-gpu >= 2.3.0, < 2.3.3`
- `tensorflow-gpu >= 2.4.0, < 2.4.2`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.3.3`
- `tensorflow 2.4.2`
- `tensorflow-cpu 2.3.3`
- `tensorflow-cpu 2.4.2`
- `tensorflow-gpu 2.3.3`
- `tensorflow-gpu 2.4.2`