Segfault in Tensorflow
Impact
The RaggedCountSparseOutput implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the splits tensor generate a valid partitioning of the values tensor. Thus, the following code sets up conditions to cause a heap buffer overflow:
auto per_batch_counts = BatchedMap<W>(num_batches);
int batch_idx = 0;
for (int idx = 0; idx < num_values; ++idx) {
while (idx >= splits_values(batch_idx)) {
batch_idx++;
}
const auto& value = values_values(idx);
if (value >= 0 && (maxlength_ <= 0 || value < maxlength_)) {
per_batch_counts[batch_idx - 1][value] = 1;
}
}A BatchedMap is equivalent to a vector where each element is a hashmap. However, if the first element of splits_values is not 0, batch_idx will never be 1, hence there will be no hashmap at index 0 in per_batch_counts. Trying to access that in the user code results in a segmentation fault.
Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.
We recommend users to upgrade to TensorFlow 2.3.1.
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 is a variant of GHSA-p5f8-gfw5-33w4
Software afectado
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| Plataforma | Paquete | Versiones vulnerables | Corregida en |
|---|---|---|---|
| Python (PyPI) | tensorflow | >= 2.3.0, < 2.3.1 | 2.3.1 |
| Python (PyPI) | tensorflow-cpu | >= 2.3.0, < 2.3.1 | 2.3.1 |
| Python (PyPI) | tensorflow-gpu | >= 2.3.0, < 2.3.1 | 2.3.1 |
Referencias
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x7rp-74x2-mjf3
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02
- https://nvd.nist.gov/vuln/detail/CVE-2020-15200
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-280.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-315.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-123.yaml
- https://github.com/tensorflow/tensorflow
- Vector CVSS
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H- Debilidad (CWE)
CWE-122, CWE-20, CWE-787- Plataforma
- Python (PyPI)
- Paquete
tensorflow, tensorflow-cpu, tensorflow-gpu- Publicada
- 25.09.2020
- Actualizado
- 11.10.2026 13:19
Fuentes y licencias
OSV / GitHub Advisory Database - PYSEC-2020-123 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2020-280 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2020-315 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-x7rp-74x2-mjf3 - 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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Segfault in Tensorflow esta entrada
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