Crash in `tf.math.segment_*` operations
Impact
The implementation of tf.math.segment_* operations results in a CHECK-fail related abort (and denial of service) if a segment id in segment_ids is large.
import tensorflow as tf
tf.math.segment_max(data=np.ones((1,10,1)), segment_ids=[1676240524292489355])
tf.math.segment_min(data=np.ones((1,10,1)), segment_ids=[1676240524292489355])
tf.math.segment_mean(data=np.ones((1,10,1)), segment_ids=[1676240524292489355])
tf.math.segment_sum(data=np.ones((1,10,1)), segment_ids=[1676240524292489355])
tf.math.segment_prod(data=np.ones((1,10,1)), segment_ids=[1676240524292489355])
This is similar to CVE-2021-29584 (and similar other reported vulnerabilities in TensorFlow, localized to specific APIs): the implementation (both on CPU and GPU) computes the output shape using AddDim. However, if the number of elements in the tensor overflows an int64_t value, AddDim results in a CHECK failure which provokes a std::abort. Instead, code should use AddDimWithStatus.
Patches
We have patched the issue in GitHub commit e9c81c1e1a9cd8dd31f4e83676cab61b60658429 (merging #51733).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit 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.
Attribution
This vulnerability has been reported externally via a GitHub issue.
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/security/advisories/GHSA-cq76-mxrc-vchh
- https://github.com/tensorflow/tensorflow/commit/e9c81c1e1a9cd8dd31f4e83676cab61b60658429
- https://github.com/tensorflow/tensorflow/pull/51733
- https://github.com/tensorflow/tensorflow/issues/46888
- https://nvd.nist.gov/vuln/detail/CVE-2021-41195
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-844.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-846.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-842.yaml
- https://github.com/tensorflow/tensorflow
- Vector CVSS
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H- Debilidad (CWE)
CWE-190- 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-2021-842 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-844 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-846 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-cq76-mxrc-vchh - 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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