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.
Affected software
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| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| 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 |
References
- 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
- CVSS vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H- Weakness (CWE)
CWE-119, CWE-122, CWE-787- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu, tensorflow-gpu- Disclosed
- 25.09.2020
- Updated
- 11.10.2026 13:19
Sources and licenses
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
Vulnerability history: tensorflow
All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.
- Total entries
- 433
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 112
- Medium 210
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 169
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
-
Data leak in Tensorflow this entry
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