Out of bounds read in Tensorflow
Impact
The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses:
import tensorflow as tf
@tf.function
def test():
y = tf.raw_ops.Dequantize(
input=tf.constant([1,1],dtype=tf.qint32),
min_range=[1.0],
max_range=[10.0],
mode='MIN_COMBINED',
narrow_range=False,
axis=2**31-1,
dtype=tf.bfloat16)
return y
test()The axis argument can be -1 (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor:
if (axis_ > -1) {
num_slices = input.dim_size(axis_);
}
// ...
int64_t pre_dim = 1, post_dim = 1;
for (int i = 0; i < axis_; ++i) {
pre_dim *= float_output.dim_size(i);
}
for (int i = axis_ + 1; i < float_output.dims(); ++i) {
post_dim *= float_output.dim_size(i);
}Patches
We have patched the issue in GitHub commit 23968a8bf65b009120c43b5ebcceaf52dbc9e943.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.
Affected software
Click a technology to see all vulnerabilities affecting it.
| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 | 2.5.3, 2.6.3, 2.7.1 |
| Python (PyPI) | tensorflow-cpu | < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 | 2.5.3, 2.6.3, 2.7.1 |
| Python (PyPI) | tensorflow-gpu | < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 | 2.5.3, 2.6.3, 2.7.1 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-23hm-7w47-xw72
- https://github.com/tensorflow/tensorflow/commit/23968a8bf65b009120c43b5ebcceaf52dbc9e943
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/dequantize_op.cc#L92-L153
- https://nvd.nist.gov/vuln/detail/CVE-2022-21726
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-50.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-105.yaml
- https://github.com/tensorflow/tensorflow
- https://pypi.org/project/tensorflow
- https://github.com/advisories/GHSA-23hm-7w47-xw72
- CVSS vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H- Weakness (CWE)
CWE-125- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu, tensorflow-gpu- Disclosed
- 03.02.2022
- Updated
- 11.10.2026 15:17
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2022-50 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2022-105 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-3082 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-23hm-7w47-xw72 - CC BY 4.0
Vulnerability history: tensorflow-gpu
All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.
- Total entries
- 427
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 109
- Medium 207
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 18
- 2024: 1
- 2025: 0
- 2026: 0
-
Out of bounds read in Tensorflow this entry
Know which vulnerabilities affect your application
With the DockRay integration and software inventory enabled, DockRay checks reported component versions against known vulnerabilities and notifies you about confirmed matches. Coverage depends on the supported technology and available advisory data.