Описание
Integer overflow in Tensorflow
Impact
The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness:
The axis argument can be -1 (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes axis + 1, an attacker can trigger an integer overflow:
Patches
We have patched the issue in GitHub commit b64638ec5ccaa77b7c1eb90958e3d85ce381f91b.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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.
Attribution
This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.
Ссылки
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c6fh-56w7-fvjw
- https://nvd.nist.gov/vuln/detail/CVE-2022-21727
- https://github.com/tensorflow/tensorflow/commit/b64638ec5ccaa77b7c1eb90958e3d85ce381f91b
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-51.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-106.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L3001-L3034
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
Связанные уязвимости
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Tensorflow is an Open Source Machine Learning Framework. The implement ...