Описание
CHECK-fail in tf.raw_ops.RFFT
Impact
An attacker can cause a denial of service by exploiting a CHECK-failure coming from the implementation of tf.raw_ops.RFFT:
The above example causes Eigen code to operate on an empty matrix. This triggers on an assertion and causes program termination.
Patches
We have patched the issue in GitHub commit 31bd5026304677faa8a0b77602c6154171b9aec1.
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 Yakun Zhang and Ying Wang of Baidu X-Team.
Ссылки
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-ph87-fvjr-v33w
- https://nvd.nist.gov/vuln/detail/CVE-2021-29563
- https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-491.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-689.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-200.yaml
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. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.RFFT`. Eigen code operating on an empty matrix can trigger on an assertion and will cause program termination. 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.
TensorFlow is an end-to-end open source platform for machine learning. ...