TensorFlow vulnerable to `CHECK` fail in `FractionalMaxPoolGrad`
Impact`FractionalMaxPoolGrad` validates its inputs with `CHECK` failures instead of with returning errors. If it gets incorrectly sized inputs, the `CHECK` failure can be used to trigger a denial of service attack:PatchesWe have patched the issue in GitHub commit [8741e57d163a079db05a7107a7609af70931def4](https://github.com/tensorflow/tensorflow/commit/8741e57d163a079db05a7107a7609af70931def4).The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.For more informationPlease 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.AttributionThis vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.