Описание
Division by 0 in inplace operations
Impact
An attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0:
The implementation has a logic error: it should skip processing if x and v are empty but the code uses || instead of &&.
Patches
We have patched the issue in GitHub commit e86605c0a336c088b638da02135ea6f9f6753618.
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 members of the Aivul Team from Qihoo 360.
Ссылки
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cm5x-837x-jf3c
- https://nvd.nist.gov/vuln/detail/CVE-2021-37660
- https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-573.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-771.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-282.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 an attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/inplace_ops.cc#L283) has a logic error: it should skip processing if `x` and `v` are empty but the code uses `||` instead of `&&`. We have patched the issue in GitHub commit e86605c0a336c088b638da02135ea6f9f6753618. 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. ...
