Division by zero in Tensorflow
Impact
The estimator for the cost of some convolution operations can be made to execute a division by 0:
import tensorflow as tf
@tf.function
def test():
y=tf.raw_ops.AvgPoolGrad(
orig_input_shape=[1,1,1,1],
grad=[[[[1.0],[1.0],[1.0]]],[[[2.0],[2.0],[2.0]]],[[[3.0],[3.0],[3.0]]]],
ksize=[1,1,1,1],
strides=[1,1,1,0],
padding='VALID',
data_format='NCHW')
return y
test()The function fails to check that the stride argument is stricly positive:
int64_t GetOutputSize(const int64_t input, const int64_t filter,
const int64_t stride, const Padding& padding) {
// Logic for calculating output shape is from GetWindowedOutputSizeVerbose()
// function in third_party/tensorflow/core/framework/common_shape_fns.cc.
if (padding == Padding::VALID) {
return (input - filter + stride) / stride;
} else { // SAME.
return (input + stride - 1) / stride;
}
}Hence, the fix is to add a check for the stride argument to ensure it is valid.
Patches
We have patched the issue in GitHub commit 3218043d6d3a019756607643cf65574fbfef5d7a.
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 | 2.5.3, 2.6.3 |
| Python (PyPI) | tensorflow-gpu | < 2.5.3, >= 2.6.0, < 2.6.3 | 2.5.3, 2.6.3 |
Referencias
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v3f7-j968-4h5f
- https://nvd.nist.gov/vuln/detail/CVE-2022-21725
- https://github.com/tensorflow/tensorflow/commit/3218043d6d3a019756607643cf65574fbfef5d7a
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-49.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-104.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/ffa202a17ab7a4a10182b746d230ea66f021fe16/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L189-L198
- https://pypi.org/project/tensorflow
- https://github.com/advisories/GHSA-v3f7-j968-4h5f
- Vector CVSS
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H- Debilidad (CWE)
CWE-369- Plataforma
- Python (PyPI)
- Paquete
tensorflow, tensorflow-cpu, tensorflow-gpu- Publicada
- 03.02.2022
- Actualizado
- 11.10.2026 14:18
Fuentes y licencias
OSV / GitHub Advisory Database - PYSEC-2022-49 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2022-104 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-v3f7-j968-4h5f - CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-3242 - PyPA Advisory Database; 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
-
Division by zero in Tensorflow esta entrada
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