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GHSA-8fxw-76px-3rxv

Memory leak in Tensorflow

Source: GitHub Advisory Database (reviewed) Moderate CVE-2020-15192

Packages

EcosystemPackageAffectedFixed in
PyPI tensorflow >= 2.2.0, < 2.2.1 2.2.1
PyPI tensorflow >= 2.3.0, < 2.3.1 2.3.1
PyPI tensorflow-cpu >= 2.2.0, < 2.2.1 2.2.1
PyPI tensorflow-cpu >= 2.3.0, < 2.3.1 2.3.1
PyPI tensorflow-gpu >= 2.2.0, < 2.2.1 2.2.1
PyPI tensorflow-gpu >= 2.3.0, < 2.3.1 2.3.1

Details

As written in the advisory (Markdown source, shown as plain text).

### 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](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) 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](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v).

References

External links from the advisory. They lead to third-party sites.