Vulnerability: 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.
Vulnerability ID: GHSA-f8h4-7rgh-q2gm
CWE: CWE-120
Severity score: 7.8
Project: https://github.com/tensorflow/tensorflow
Published: 2021-08-25
File: tensorflow/core/kernels/data/experimental/to_tf_record_op.cc
Commit message: Fix segfault/heap buffer overflow in `{Experimental,}DatasetToTFRecord` where dataset is numeric.

Code assumes only strings inputs and then interprets numbers as valid `tstring`s. Then, when trying to compute the CRC of the record this results in heap buffer overflow.

PiperOrigin-RevId: 387675909
Change-Id: I7396b9b8afc1ac744112af7c0b1cd7bb41e0f556
Commit author: Mihai Maruseac

Vulnerable version (before fix):
 limitations under the License. #include "tensorflow/core/framework/function_handle_cache.h" #include "tensorflow/core/framework/op_kernel.h" #include "tensorflow/core/framework/resource_mgr.h" #include "tensorflow/core/kernels/ops_util.h" #include "tensorflow/core/lib/core/threadpool.h" #include "tensorflow/core/lib/io/record_writer.h" class ToTFRecordOp : public AsyncOpKernel {     TF_RETURN_IF_ERROR(finalized_dataset->MakeIterator(         &iter_ctx, /*parent=*/nullptr, "ToTFRecordOpIterator", &iterator));      std::vector<Tensor> components;     components.reserve(finalized_dataset->output_dtypes().size());     bool end_of_sequence;     do {       TF_RETURN_IF_ERROR(

Fixed version (after fix):
 limitations under the License. #include "tensorflow/core/framework/function_handle_cache.h" #include "tensorflow/core/framework/op_kernel.h" #include "tensorflow/core/framework/resource_mgr.h" #include "tensorflow/core/framework/types.h" #include "tensorflow/core/kernels/ops_util.h" #include "tensorflow/core/lib/core/threadpool.h" #include "tensorflow/core/lib/io/record_writer.h" class ToTFRecordOp : public AsyncOpKernel {     TF_RETURN_IF_ERROR(finalized_dataset->MakeIterator(         &iter_ctx, /*parent=*/nullptr, "ToTFRecordOpIterator", &iterator));      const int num_output_dtypes = finalized_dataset->output_dtypes().size();     if (num_output_dtypes != 1) {       return errors::InvalidArgument(           "ToTFRecordOp currently only support datasets of 1 single column, ",           "but got ", num_output_dtypes);     }     const DataType dt = finalized_dataset->output_dtypes()[0];     if (dt != DT_STRING) {       return errors::InvalidArgument(           "ToTFRecordOp currently only supports DT_STRING dataypes, but got ",           DataTypeString(dt));     }     std::vector<Tensor> components;     components.reserve(num_output_dtypes);     bool end_of_sequence;     do {       TF_RETURN_IF_ERROR(

Patch:
patch: @@ -18,6 +18,7 @@ limitations under the License.
 #include "tensorflow/core/framework/function_handle_cache.h"
 #include "tensorflow/core/framework/op_kernel.h"
 #include "tensorflow/core/framework/resource_mgr.h"
+#include "tensorflow/core/framework/types.h"
 #include "tensorflow/core/kernels/ops_util.h"
 #include "tensorflow/core/lib/core/threadpool.h"
 #include "tensorflow/core/lib/io/record_writer.h"
@@ -91,8 +92,20 @@ class ToTFRecordOp : public AsyncOpKernel {
     TF_RETURN_IF_ERROR(finalized_dataset->MakeIterator(
         &iter_ctx, /*parent=*/nullptr, "ToTFRecordOpIterator", &iterator));
 
+    const int num_output_dtypes = finalized_dataset->output_dtypes().size();
+    if (num_output_dtypes != 1) {
+      return errors::InvalidArgument(
+          "ToTFRecordOp currently only support datasets of 1 single column, ",
+          "but got ", num_output_dtypes);
+    }
+    const DataType dt = finalized_dataset->output_dtypes()[0];
+    if (dt != DT_STRING) {
+      return errors::InvalidArgument(
+          "ToTFRecordOp currently only supports DT_STRING dataypes, but got ",
+          DataTypeString(dt));
+    }
     std::vector<Tensor> components;
-    components.reserve(finalized_dataset->output_dtypes().size());
+    components.reserve(num_output_dtypes);
     bool end_of_sequence;
     do {
       TF_RETURN_IF_ERROR(
path: tensorflow/core/kernels/data/experimental/to_tf_record_op.cc