Описание
FPE in tf.raw_ops.UnravelIndex
Impact
An attacker can cause denial of service in applications serving models using tf.raw_ops.UnravelIndex by triggering a division by 0:
The implementation does not check that the tensor subsumed by dims is not empty. Hence, if one element of dims is 0, the implementation does a division by 0.
Patches
We have patched the issue in GitHub commit a776040a5e7ebf76eeb7eb923bf1ae417dd4d233.
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-2wmv-37vq-52g5
- https://nvd.nist.gov/vuln/detail/CVE-2021-37668
- https://github.com/tensorflow/tensorflow/commit/a776040a5e7ebf76eeb7eb923bf1ae417dd4d233
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-581.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-779.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-290.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 denial of service in applications serving models using `tf.raw_ops.UnravelIndex` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unravel_index_op.cc#L36) does not check that the tensor subsumed by `dims` is not empty. Hence, if one element of `dims` is 0, the implementation does a division by 0. We have patched the issue in GitHub commit a776040a5e7ebf76eeb7eb923bf1ae417dd4d233. 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. ...
