---
id: CVE-2021-37676
aliases:
  - GHSA-v768-w7m9-2vmm
  - BIT-tensorflow-2021-37676
  - PYSEC-2021-298
  - PYSEC-2021-589
  - PYSEC-2021-787
title: Reference binding to nullptr in shape inference
summary: Reference binding to nullptr in shape inference
severity: high
cvss: 7.8
cvssVector: 'CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/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-v768-w7m9-2vmm'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v768-w7m9-2vmm
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2021-37676'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/578e634b4f1c1c684d4b4294f9e5281b2133b3ed
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-589.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-787.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-298.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
tags:
  - osv
  - pip
epss: 0.00173
epssPercentile: 0.06013
ingestedAt: '2026-07-08T18:25:53.232Z'
---

## Overview

### Impact
An attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.SparseFillEmptyRows`:

```python
import tensorflow as tf
  
tf.compat.v1.disable_v2_behavior()
tf.raw_ops.SparseFillEmptyRows(
  indices = tf.constant([], shape=[0, 0], dtype=tf.int64),
  values = tf.constant([], shape=[0], dtype=tf.int64),
  dense_shape = tf.constant([], shape=[0], dtype=tf.int64),
  default_value = 0)
```
  
The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/sparse_ops.cc#L608-L634) does not validate that the input arguments are not empty tensors.

### Patches 
We have patched the issue in GitHub commit [578e634b4f1c1c684d4b4294f9e5281b2133b3ed](https://github.com/tensorflow/tensorflow/commit/578e634b4f1c1c684d4b4294f9e5281b2133b3ed).

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 Yakun Zhang of Baidu Security

## 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`