Division by zero in TFLite's implementation of `OneHot`
Impact
The implementation of the OneHot TFLite operator is vulnerable to a division by zero error:
int prefix_dim_size = 1;
for (int i = 0; i < op_context.axis; ++i) {
prefix_dim_size *= op_context.indices->dims->data[i];
}
const int suffix_dim_size = NumElements(op_context.indices) / prefix_dim_size;An attacker can craft a model such that at least one of the dimensions of indices would be 0. In turn, the prefix_dim_size value would become 0.
Patches
We have patched the issue in GitHub commit 3ebedd7e345453d68e279cfc3e4072648e5e12e5.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 members of the Aivul Team from Qihoo 360.
Software afectado
Haz clic en una tecnología para ver todas sus vulnerabilidades.
| Plataforma | Paquete | Versiones vulnerables | Corregida en |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-cpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-gpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
Referencias
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j8qh-3xrq-c825
- https://github.com/tensorflow/tensorflow/commit/3ebedd7e345453d68e279cfc3e4072648e5e12e5
- https://nvd.nist.gov/vuln/detail/CVE-2021-29600
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-528.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-726.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-237.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/f61c57bd425878be108ec787f4d96390579fb83e/tensorflow/lite/kernels/one_hot.cc#L68-L72
- Vector CVSS
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L- Debilidad (CWE)
CWE-369- Plataforma
- Python (PyPI)
- Paquete
tensorflow, tensorflow-cpu, tensorflow-gpu- Publicada
- 14.05.2021
- Actualizado
- 11.10.2026 13:19
Fuentes y licencias
OSV / GitHub Advisory Database - PYSEC-2021-237 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-528 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-726 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-j8qh-3xrq-c825 - CC BY 4.0
Historial de vulnerabilidades: tensorflow-cpu
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
- 430
- Primera → última
- 04.2019 07.2024
- Sin corrección
- 0
- Explotada en ataques
- 0
Distribución por gravedad
- Crítica 6
- Alta 111
- Media 208
- Baja 105
Divulgaciones por año
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
-
Division by zero in TFLite's implementation of `OneHot` esta entrada
Identifica las vulnerabilidades de tu aplicación
Con la integración de DockRay y el inventario de software activado, DockRay compara las versiones notificadas de los componentes con las vulnerabilidades conocidas y avisa de las coincidencias confirmadas. La cobertura depende de la tecnología compatible y de los avisos disponibles.