Incomplete validation of shapes in multiple TF ops
Impact
Several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or CHECK-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible.
We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues.
Patches
We have patched the issue in GitHub commits 68422b215e618df5ad375bcdc6d2052e9fd3080a, 4d74d8a00b07441cba090a02e0dd9ed385145bf4, 579261dcd446385831fe4f7457d802a59685121d, da4aad5946be30e5f049920fa076e1f7ef021261, 4dddb2fd0b01cdd196101afbba6518658a2c9e07, and e7f497570abb6b4ae5af4970620cd880e4c0c904.
These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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.
Software afectado
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| Plataforma | Paquete | Versiones vulnerables | Corregida en |
|---|---|---|---|
| Python (PyPI) | tensorflow | >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 | 2.6.1, 2.5.2, 2.4.4 |
| Python (PyPI) | tensorflow-cpu | >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 | 2.6.1, 2.5.2, 2.4.4 |
| Python (PyPI) | tensorflow-gpu | >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 | 2.6.1, 2.5.2, 2.4.4 |
Referencias
- https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a
- https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4
- https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d
- https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pgcq-h79j-2f69
- https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261
- https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07
- https://nvd.nist.gov/vuln/detail/CVE-2021-41206
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-845.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-847.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-843.yaml
- https://github.com/tensorflow/tensorflow
- Vector CVSS
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H- Debilidad (CWE)
CWE-354- Plataforma
- Python (PyPI)
- Paquete
tensorflow, tensorflow-cpu, tensorflow-gpu- Publicada
- 05.11.2021
- Actualizado
- 11.10.2026 13:19
Fuentes y licencias
OSV / GitHub Advisory Database - PYSEC-2021-843 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-845 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-847 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-pgcq-h79j-2f69 - 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
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