Memory corruption in Tensorflow
Vulnerability Description
In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a `reinterpret_cast` Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.
Impact Analysis
Refer to official advisory for detailed impact metrics.
Remediation
Ensure systems are updated to the latest vendor-supplied patch levels.
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Credits & Attribution
No credits recorded in the NVD database.
References
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v
- https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
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