Out of bounds read and write in Tensorflow
### Impact
There is a typo in TensorFlow's `SpecializeType`
https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/full_type_util.cc#L81-L102 which results in heap OOB read/write:
```cc
for (int i = 0; i < op_def.output_arg_size(); i++) {
// ...
for (int j = 0; j < t->args_size(); j++) {
auto* arg = t->mutable_args(i);
// ...
}
}
```
Due to a typo, `arg` is initialized to the `i`th mutable argument in a loop where the loop index is `j`. Hence it is possible to assign to `arg` from outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data.
### Patches
We have patched the issue in GitHub commit 0657c83d08845cc434175934c642299de2c0f042
https://github.com/tensorflow/tensorflow/commit/0657c83d08845cc434175934c642299de2c0f042.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, 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.