Vulnerability: Division by zero in TFLite's implementation of `SpaceToBatchNd` ### Impact
The implementation of the `SpaceToBatchNd` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/412c7d9bb8f8a762c5b266c9e73bfa165f29aac8/tensorflow/lite/kernels/space_to_batch_nd.cc#L82-L83):

```cc
TF_LITE_ENSURE_EQ(context, final_dim_size % block_shape[dim], 0);
output_size->data[dim + 1] = final_dim_size / block_shape[dim];
```

An attacker can craft a model such that one dimension of the `block` input is 0. Hence, the corresponding value in `block_shape` is 0.

### Patches
We have patched the issue in GitHub commit [6d36ba65577006affb272335b7c1abd829010708](https://github.com/tensorflow/tensorflow/commit/6d36ba65577006affb272335b7c1abd829010708).

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.
Vulnerability ID: GHSA-v52p-hfjf-wg88
CWE: CWE-369
Severity score: 2.5
Project: https://github.com/tensorflow/tensorflow
Published: 2021-05-21
File: tensorflow/lite/kernels/space_to_batch_nd.cc
Commit message: Prevent division by 0

PiperOrigin-RevId: 370984990
Change-Id: Ib324955bbeb1cbd97c82fd5d61a00a2697c9a2de
Commit author: Mihai Maruseac

Vulnerable version (before fix):
 TfLiteStatus ResizeOutputTensor(TfLiteContext* context,   for (int dim = 0; dim < spatial_dims_num; ++dim) {     int final_dim_size = (input_size->data[dim + 1] + paddings_data[dim * 2] +                           paddings_data[dim * 2 + 1]);     TF_LITE_ENSURE_EQ(context, final_dim_size % block_shape[dim], 0);     output_size->data[dim + 1] = final_dim_size / block_shape[dim];     output_batch_size *= block_shape[dim];

Fixed version (after fix):
 TfLiteStatus ResizeOutputTensor(TfLiteContext* context,   for (int dim = 0; dim < spatial_dims_num; ++dim) {     int final_dim_size = (input_size->data[dim + 1] + paddings_data[dim * 2] +                           paddings_data[dim * 2 + 1]);     TF_LITE_ENSURE(context, block_shape[dim] != 0);     TF_LITE_ENSURE_EQ(context, final_dim_size % block_shape[dim], 0);     output_size->data[dim + 1] = final_dim_size / block_shape[dim];     output_batch_size *= block_shape[dim];

Patch:
patch: @@ -79,6 +79,7 @@ TfLiteStatus ResizeOutputTensor(TfLiteContext* context,
   for (int dim = 0; dim < spatial_dims_num; ++dim) {
     int final_dim_size = (input_size->data[dim + 1] + paddings_data[dim * 2] +
                           paddings_data[dim * 2 + 1]);
+    TF_LITE_ENSURE(context, block_shape[dim] != 0);
     TF_LITE_ENSURE_EQ(context, final_dim_size % block_shape[dim], 0);
     output_size->data[dim + 1] = final_dim_size / block_shape[dim];
     output_batch_size *= block_shape[dim];
path: tensorflow/lite/kernels/space_to_batch_nd.cc