Описание
Arbitrary code execution due to YAML deserialization
Impact
TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format.
The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input.
Patches
Given that YAML format support requires a significant amount of work, we have removed it for now.
We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 Arjun Shibu.
Ссылки
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6jx-9g48-2r5r
- https://nvd.nist.gov/vuln/detail/CVE-2021-37678
- https://github.com/tensorflow/tensorflow/commit/1df5a69e9f1a18a937e7907223066e606bf466b9
- https://github.com/tensorflow/tensorflow/commit/23d6383eb6c14084a8fc3bdf164043b974818012
- https://github.com/tensorflow/tensorflow/commit/8e47a685785bef8f81bcb996048921dfde08a9ab
- https://github.com/tensorflow/tensorflow/commit/a09ab4e77afdcc6e1e045c9d41d5edab63aafc1a
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-591.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-789.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-300.yaml
Пакеты
tensorflow
< 2.3.4
2.3.4
tensorflow
>= 2.4.0, < 2.4.3
2.4.3
tensorflow
= 2.5.0
2.5.1
tensorflow-cpu
< 2.3.4
2.3.4
tensorflow-cpu
>= 2.4.0, < 2.4.3
2.4.3
tensorflow-cpu
= 2.5.0
2.5.1
tensorflow-gpu
< 2.3.4
2.3.4
tensorflow-gpu
>= 2.4.0, < 2.4.3
2.4.3
tensorflow-gpu
= 2.5.0
2.5.1
Связанные уязвимости
TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses `yaml.unsafe_load` which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
TensorFlow is an end-to-end open source platform for machine learning. ...
