Memory corruption in Tensorflow
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.
describes (1)
Related CVEs.
| ID | severity | exploitable | ||
|---|---|---|---|---|
| CVE-2020-15193US | high7.1 | — | ||
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 beca… | ||||
references
External citations — patches, advisories, analysis.
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.htmlADVISORY
- https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8ADVISORY
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1ADVISORY
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69vADVISORY
- https://nvd.nist.gov/vuln/detail/CVE-2020-15193WEB
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