Data leak in Tensorflow
Impact
The data_splits argument of tf.raw_ops.StringNGrams lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory
>>> tf.raw_ops.StringNGrams(data=["aa", "bb", "cc", "dd", "ee", "ff"], data_splits=[0,8], separator=" ", ngram_widths=[3], left_pad="", right_pad="", pad_width=0, preserve_short_sequences=False)
StringNGrams(ngrams=<tf.Tensor: shape=(6,), dtype=string, numpy=
array([b'aa bb cc', b'bb cc dd', b'cc dd ee', b'dd ee ff',
b'ee ff \xf4j\xa7q\x7f\x00\x00q\x00\x00\x00\x00\x00\x00\x00\xd8\x9b~\xa8q\x7f\x00',
b'ff \xf4j\xa7q\x7f\x00\x00q\x00\x00\x00\x00\x00\x00\x00\xd8\x9b~\xa8q\x7f\x00 \x9b~\xa8q\x7f\x00\x00p\xf5j\xa7q\x7f\x00\x00H\xf8j\xa7q\x7f\x00\x00\xf0\xf3\xf7\x85q\x7f\x00\x00`}\xa6\x00\x00\x00\x00\x00`~\xa6\x00\x00\x00\x00\x00\xb0~\xeb\x9bq\x7f\x00'],...
All the binary strings after ee ff are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR.
Patches
We have patched the issue in 0462de5b544ed4731aa2fb23946ac22c01856b80 and will release patch releases for all versions between 1.15 and 2.3.
We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 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 has been reported by members of the Aivul Team from Qihoo 360.
Software afectado
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| Plataforma | Paquete | Versiones vulnerables | Corregida en |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 |
| Python (PyPI) | tensorflow-cpu | < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 |
| Python (PyPI) | tensorflow-gpu | < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 |
Referencias
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g7p5-5759-qv46
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/commit/0462de5b544ed4731aa2fb23946ac22c01856b80
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
- https://nvd.nist.gov/vuln/detail/CVE-2020-15205
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-285.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-320.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-128.yaml
- https://github.com/tensorflow/tensorflow
- Vector CVSS
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H- Debilidad (CWE)
CWE-119, CWE-122, 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-2020-128 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2020-285 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2020-320 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-g7p5-5759-qv46 - 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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Data leak in Tensorflow esta entrada
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