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.
Software afectado
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| Plataforma | Paquete | Versiones vulnerables | Corregida en |
|---|---|---|---|
| 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 |
Referencias
- 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
- Vector CVSS
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H- Debilidad (CWE)
CWE-125- Plataforma
- Python (PyPI)
- Paquete
tensorflow, tensorflow-cpu, tensorflow-gpu- Publicada
- 03.02.2022
- Actualizado
- 11.10.2026 15:17
Fuentes y licencias
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
Historial de vulnerabilidades: tensorflow-gpu
Todas las vulnerabilidades publicadas de este paquete (Python (PyPI)), de la más reciente a la más antigua. Muestra si es un fallo aislado o un paquete que hay que vigilar.
- Entradas en total
- 427
- Primera → última
- 04.2019 07.2024
- Sin corrección
- 0
- Explotada en ataques
- 0
Distribución por gravedad
- Crítica 6
- Alta 109
- Media 207
- Baja 105
Divulgaciones por año
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 18
- 2024: 1
- 2025: 0
- 2026: 0
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Out of bounds read in Tensorflow esta entrada
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