Heap OOB read in TFLite's implementation of `Minimum` or `Maximum`
### Impact
The implementations of the `Minimum` and `Maximum` TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty.
This is because the broadcasting implementation
https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56 indexes in both tensors with the same index but does not validate that the index is within bounds:
```cc
auto maxmin_func = [&](int indexes[N]) {
output_data[SubscriptToIndex(output_desc, indexes)] =
op(input1_data[SubscriptToIndex(desc1, indexes)],
input2_data[SubscriptToIndex(desc2, indexes)]);
};
```
### Patches
We have patched the issue in GitHub commit 953f28dca13c92839ba389c055587cfe6c723578
https://github.com/tensorflow/tensorflow/commit/953f28dca13c92839ba389c055587cfe6c723578.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### 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 reported by members of the Aivul Team from Qihoo 360.