Stack overflow due to looping TFLite subgraph
Impact
TFlite graphs must not have loops between nodes. However, this condition was not checked and an attacker could craft models that would result in infinite loop during evaluation. In certain cases, the infinite loop would be replaced by stack overflow due to too many recursive calls.
For example, the While implementation could be tricked into a scneario where both the body and the loop subgraphs are the same. Evaluating one of the subgraphs means calling the Eval function for the other and this quickly exhaust all stack space.
Patches
We have patched the issue in GitHub commit 9c1dc920d8ffb4893d6c9d27d1f039607b326743 (for the While operator) and in GitHub commit c6173f5fe66cdbab74f4f869311fe6aae2ba35f4 (in general).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 by members of the Aivul Team from Qihoo 360.
Betroffene Software
Klicken Sie auf eine Technologie, um alle zugehörigen Schwachstellen anzuzeigen.
| Plattform | Paket | Anfällige Versionen | Behoben in |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-cpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-gpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
Verweise
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cwv3-863g-39vx
- https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743
- https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4
- https://nvd.nist.gov/vuln/detail/CVE-2021-29591
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-519.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-717.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-228.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/106d8f4fb89335a2c52d7c895b7a7485465ca8d9/tensorflow/lite/kernels/while.cc
- CVSS-Vektor
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H- Schwäche (CWE)
CWE-674, CWE-835- Plattform
- Python (PyPI)
- Paket
tensorflow, tensorflow-cpu, tensorflow-gpu- Veröffentlicht
- 14.05.2021
- Aktualisiert
- 11.10.2026 13:19
Quellen und Lizenzen
OSV / GitHub Advisory Database - PYSEC-2021-228 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-519 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-717 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-cwv3-863g-39vx - CC BY 4.0
Schwachstellenhistorie: tensorflow
Alle veröffentlichten Schwachstellen dieses Pakets (Python (PyPI)), neueste zuerst. Zeigt, ob es ein einmaliger Ausrutscher ist oder ein Paket, das man im Auge behalten muss.
- Einträge insgesamt
- 433
- Erste → letzte
- 04.2019 07.2024
- Ohne Fix
- 0
- In Angriffen ausgenutzt
- 0
Verteilung nach Schweregrad
- Kritisch 6
- Hoch 112
- Mittel 210
- Niedrig 105
Veröffentlichungen pro Jahr
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 169
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
-
Stack overflow due to looping TFLite subgraph dieser Eintrag
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