Описание
Reference binding to nullptr in tf.ragged.cross
Impact
The shape inference code for tf.ragged.cross has an undefined behavior due to binding a reference to nullptr. In the following scenario, this results in a crash:
Patches
We have patched the issue in GitHub commit fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8.
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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-vwhq-49r4-gj9v
- https://nvd.nist.gov/vuln/detail/CVE-2021-41214
- https://github.com/tensorflow/tensorflow/commit/fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-623.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-821.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-406.yaml
Пакеты
tensorflow
>= 2.6.0, < 2.6.1
2.6.1
tensorflow
>= 2.5.0, < 2.5.2
2.5.2
tensorflow
< 2.4.4
2.4.4
tensorflow-cpu
>= 2.6.0, < 2.6.1
2.6.1
tensorflow-cpu
>= 2.5.0, < 2.5.2
2.5.2
tensorflow-cpu
< 2.4.4
2.4.4
tensorflow-gpu
>= 2.6.0, < 2.6.1
2.6.1
tensorflow-gpu
>= 2.5.0, < 2.5.2
2.5.2
tensorflow-gpu
< 2.4.4
2.4.4
Связанные уязвимости
TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `tf.ragged.cross` has an undefined behavior due to binding a reference to `nullptr`. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
TensorFlow is an open source platform for machine learning. In affecte ...