GHSA-8fxw-76px-3rxv Memory leak in Tensorflow

• PyPI tensorflow: >= 2.2.0, < 2.2.1 → fixed in 2.2.1 • PyPI tensorflow: >= 2.3.0, < 2.3.1 → fixed in 2.3.1 • PyPI tensorflow-cpu: >= 2.2.0, < 2.2.1 → fixed in 2.2.1 • PyPI tensorflow-cpu: >= 2.3.0, < 2.3.1 → fixed in 2.3.1 • PyPI tensorflow-gpu: >= 2.2.0, < 2.2.1 → fixed in 2.2.1 • PyPI tensorflow-gpu: >= 2.3.0, < 2.3.1 → fixed in 2.3.1

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 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.