Описание
Memory leak in Tensorflow
Impact
If a user passes a list of strings to dlpack.to_dlpack there is a memory leak following an expected validation failure:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/c/eager/dlpack.cc#L100-L104
The allocated memory is from https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/c/eager/dlpack.cc#L256
The issue occurs because the status argument during validation failures is not properly checked:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/c/eager/dlpack.cc#L265-L267
Since each of the above methods can return an error status, the status value must be checked before continuing.
Patches
We have patched the issue in 22e07fb204386768e5bcbea563641ea11f96ceb8 and will release a patch release for all affected versions.
We recommend users to upgrade to TensorFlow 2.2.1 or 2.3.1.
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 discovered during variant analysis of GHSA-rjjg-hgv6-h69v.
Ссылки
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8fxw-76px-3rxv
- https://nvd.nist.gov/vuln/detail/CVE-2020-15192
- https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-272.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-307.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-115.yaml
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
Пакеты
tensorflow
= 2.2.0
2.2.1
tensorflow
= 2.3.0
2.3.1
tensorflow-cpu
= 2.2.0
2.2.1
tensorflow-cpu
= 2.3.0
2.3.1
tensorflow-gpu
= 2.2.0
2.2.1
tensorflow-gpu
= 2.3.0
2.3.1
Связанные уязвимости
In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to `dlpack.to_dlpack` there is a memory leak following an expected validation failure. The issue occurs because the `status` argument during validation failures is not properly checked. Since each of the above methods can return an error status, the `status` value must be checked before continuing. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.
In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list ...
