Heap OOB in shape inference for `QuantizeV2`
Impact
The shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array:
import tensorflow as tf
@tf.function
def test():
data=tf.raw_ops.QuantizeV2(
input=[1.0,1.0],
min_range=[1.0,10.0],
max_range=[1.0,10.0],
T=tf.qint32,
mode='MIN_COMBINED',
round_mode='HALF_TO_EVEN',
narrow_range=False,
axis=-100,
ensure_minimum_range=10)
return data
test()
This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start of a heap buffer:
int axis = -1;
Status s = c->GetAttr("axis", &axis);
if (!s.ok() && s.code() != error::NOT_FOUND) {
return s;
}
...
if (axis != -1) {
...
TF_RETURN_IF_ERROR(
c->Merge(c->Dim(minmax, 0), c->Dim(input, axis), &depth));
}
The code allows axis to be an optional argument (s would contain an error::NOT_FOUND error code). Otherwise, it assumes that axis is a valid index into the dimensions of the input tensor. If axis is less than -1 then this results in a heap OOB read.
Patches
We have patched the issue in GitHub commit a0d64445116c43cf46a5666bd4eee28e7a82f244.
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.
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 members of the Aivul Team from Qihoo 360.
Affected software
Click a technology to see all vulnerabilities affecting it.
| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| Python (PyPI) | tensorflow | >= 2.6.0, < 2.6.1 | 2.6.1 |
| Python (PyPI) | tensorflow-cpu | >= 2.6.0, < 2.6.1 | 2.6.1 |
| Python (PyPI) | tensorflow-gpu | >= 2.6.0, < 2.6.1 | 2.6.1 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvgx-3v3q-m36c
- https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244
- https://nvd.nist.gov/vuln/detail/CVE-2021-41211
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-620.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-818.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-403.yaml
- https://github.com/tensorflow/tensorflow
- CVSS vector
CVSS:3.1/AV:L/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
- 05.11.2021
- Updated
- 11.10.2026 13:19
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2021-403 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-620 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-818 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-cvgx-3v3q-m36c - 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
-
Heap OOB in shape inference for `QuantizeV2` 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.