Описание
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.
Ссылки
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cwv3-863g-39vx
- https://nvd.nist.gov/vuln/detail/CVE-2021-29591
- https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743
- https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4
- 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/blob/106d8f4fb89335a2c52d7c895b7a7485465ca8d9/tensorflow/lite/kernels/while.cc
Пакеты
tensorflow
< 2.1.4
2.1.4
tensorflow
>= 2.2.0, < 2.2.3
2.2.3
tensorflow
>= 2.3.0, < 2.3.3
2.3.3
tensorflow
>= 2.4.0, < 2.4.2
2.4.2
tensorflow-cpu
< 2.1.4
2.1.4
tensorflow-cpu
>= 2.2.0, < 2.2.3
2.2.3
tensorflow-cpu
>= 2.3.0, < 2.3.3
2.3.3
tensorflow-cpu
>= 2.4.0, < 2.4.2
2.4.2
tensorflow-gpu
< 2.1.4
2.1.4
tensorflow-gpu
>= 2.2.0, < 2.2.3
2.2.3
tensorflow-gpu
>= 2.3.0, < 2.3.3
2.3.3
tensorflow-gpu
>= 2.4.0, < 2.4.2
2.4.2
Связанные уязвимости
TensorFlow is an end-to-end open source platform for machine learning. 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(https://github.com/tensorflow/tensorflow/blob/106d8f4fb89335a2c52d7c895b7a7485465ca8d9/tensorflow/lite/kernels/while.cc) 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. 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. Please consult our security guide(https://github.com/ten
TensorFlow is an end-to-end open source platform for machine learning. ...