Описание
Data corruption in tensorflow-lite
Impact
When determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation modes:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/types.h#L437-L442
Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors.
Patches
We have patched the issue in 8ee24e7949a20 and will release patch releases for all versions between 1.15 and 2.3.
We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 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 reported by members of the Aivul Team from Qihoo 360.
Ссылки
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mxjj-953w-2c2v
- https://nvd.nist.gov/vuln/detail/CVE-2020-15208
- https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-288.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-323.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-131.yaml
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
Пакеты
tensorflow
< 1.15.4
1.15.4
tensorflow
>= 2.0.0, < 2.0.3
2.0.3
tensorflow
>= 2.1.0, < 2.1.2
2.1.2
tensorflow
= 2.2.0
2.2.1
tensorflow
= 2.3.0
2.3.1
tensorflow-cpu
< 1.15.4
1.15.4
tensorflow-cpu
>= 2.0.0, < 2.0.3
2.0.3
tensorflow-cpu
>= 2.1.0, < 2.1.2
2.1.2
tensorflow-cpu
= 2.2.0
2.2.1
tensorflow-cpu
= 2.3.0
2.3.1
tensorflow-gpu
< 1.15.4
1.15.4
tensorflow-gpu
>= 2.0.0, < 2.0.3
2.0.3
tensorflow-gpu
>= 2.1.0, < 2.1.2
2.1.2
tensorflow-gpu
= 2.2.0
2.2.1
tensorflow-gpu
= 2.3.0
2.3.1
Связанные уязвимости
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3 ...
