Описание
Crash when type cannot be specialized in Tensorflow
Impact
Under certain scenarios, TensorFlow can fail to specialize a type during shape inference:
However, DCHECK is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the ValueOrDie line. This results in an assertion failure as ret contains an error Status, not a value. In the second case we also get a crash due to the assertion failure.
Patches
We have patched the issue in GitHub commit cb164786dc891ea11d3a900e90367c339305dc7b.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, 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.
Ссылки
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rww7-2gpw-fv6j
- https://nvd.nist.gov/vuln/detail/CVE-2022-23572
- https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-81.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-136.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174
Пакеты
tensorflow
< 2.5.3
2.5.3
tensorflow
>= 2.6.0, < 2.6.3
2.6.3
tensorflow
= 2.7.0
2.7.1
tensorflow-cpu
< 2.5.3
2.5.3
tensorflow-cpu
>= 2.6.0, < 2.6.3
2.6.3
tensorflow-cpu
= 2.7.0
2.7.1
tensorflow-gpu
< 2.5.3
2.5.3
tensorflow-gpu
>= 2.6.0, < 2.6.3
2.6.3
tensorflow-gpu
= 2.7.0
2.7.1
EPSS
7.1 High
CVSS4
6.5 Medium
CVSS3
CVE ID
Дефекты
Связанные уязвимости
Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the `DCHECK` function however, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
Tensorflow is an Open Source Machine Learning Framework. Under certain ...
EPSS
7.1 High
CVSS4
6.5 Medium
CVSS3