Segfault and heap buffer overflow in `{Experimental,}DatasetToTFRecord`
### Impact
The implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault:
```python
import tensorflow as tf
dataset = tf.data.Dataset.range(3)
dataset = tf.data.experimental.to_variant(dataset)
tf.raw_ops.ExperimentalDatasetToTFRecord(
input_dataset=dataset,
filename='/tmp/output',
compression_type='')
```
The implementation
https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102 assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types.
### Patches
We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876
https://github.com/tensorflow/tensorflow/commit/e0b6e58c328059829c3eb968136f17aa72b6c876.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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.