Segfault and data corruption in tensorflow-lite
Impact
To mimic Python's indexing with negative values, TFLite uses ResolveAxis to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reduce.h#L68-L72
If the DCHECK does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption.
Patches
We have patched the issue in 2d88f470dea2671b430884260f3626b1fe99830a 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
Click a technology to see all vulnerabilities affecting it.
| 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/commit/2d88f470dea2671b430884260f3626b1fe99830a
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q4qf-3fc6-8x34
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
- https://nvd.nist.gov/vuln/detail/CVE-2020-15207
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-287.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-322.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-130.yaml
- https://github.com/tensorflow/tensorflow
- CVSS vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:H/A:H- Weakness (CWE)
CWE-119, CWE-787- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu, tensorflow-gpu- Disclosed
- 25.09.2020
- Updated
- 11.10.2026 15:17
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2020-130 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2020-287 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2020-322 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-q4qf-3fc6-8x34 - CC BY 4.0
Vulnerability history: tensorflow-cpu
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
- 430
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 111
- Medium 208
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
-
Segfault and data corruption in tensorflow-lite this entry
Know which vulnerabilities affect your application
With the DockRay integration and software inventory enabled, DockRay checks reported component versions against known vulnerabilities and notifies you about confirmed matches. Coverage depends on the supported technology and available advisory data.