Vulnerability: Memory corruption in `DrawBoundingBoxesV2` ### Impact
The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs:

```python
import tensorflow as tf

images = tf.fill([10, 96, 0, 1], 0.)
boxes = tf.fill([10, 53, 0], 0.)
colors = tf.fill([0, 1], 0.)

tf.raw_ops.DrawBoundingBoxesV2(images=images, boxes=boxes, colors=colors)
```

The [implementation](https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption:

```cc 
const auto tboxes = boxes.tensor<T, 3>();
for (int64 bb = 0; bb < num_boxes; ++bb) {
  ...
  const int64 min_box_row = static_cast<float>(tboxes(b, bb, 0)) * (height - 1);
  const int64 max_box_row = static_cast<float>(tboxes(b, bb, 2)) * (height - 1);
  const int64 min_box_col = static_cast<float>(tboxes(b, bb, 1)) * (width - 1);
  const int64 max_box_col = static_cast<float>(tboxes(b, bb, 3)) * (width - 1);
  ...
}
``` 

If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices.

### Patches
We have patched the issue in GitHub commit [79865b542f9ffdc9caeb255631f7c56f1d4b6517](https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517).

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 Yakun Zhang and Ying Wang of Baidu X-Team.
Vulnerability ID: GHSA-whr9-vfh2-7hm6
CWE: CWE-787
Severity score: 4.5
Project: https://github.com/tensorflow/tensorflow
Published: 2021-05-21
File: tensorflow/core/kernels/image/draw_bounding_box_op.cc
Commit message: Fix memory corruption issue with `tf.raw_ops.DrawBoundingBoxesV2`.

PiperOrigin-RevId: 372033910
Change-Id: I8a9f4efc1c8ddaacbc26ec1fbe4bfdd6791c226d
Commit author: Amit Patankar

Vulnerable version (before fix):
 class DrawBoundingBoxesOp : public OpKernel {         errors::InvalidArgument("Channel depth should be either 1 (GRY), "                                 "3 (RGB), or 4 (RGBA)"));      const int64 batch_size = images.dim_size(0);     const int64 height = images.dim_size(1);     const int64 width = images.dim_size(2);

Fixed version (after fix):
 class DrawBoundingBoxesOp : public OpKernel {         errors::InvalidArgument("Channel depth should be either 1 (GRY), "                                 "3 (RGB), or 4 (RGBA)"));      OP_REQUIRES(         context, boxes.dim_size(2) == 4,         errors::InvalidArgument(             "The size of the third dimension of the box must be 4. Received: ",             boxes.dim_size(2)));      const int64 batch_size = images.dim_size(0);     const int64 height = images.dim_size(1);     const int64 width = images.dim_size(2);

Patch:
patch: @@ -73,6 +73,12 @@ class DrawBoundingBoxesOp : public OpKernel {
         errors::InvalidArgument("Channel depth should be either 1 (GRY), "
                                 "3 (RGB), or 4 (RGBA)"));
 
+    OP_REQUIRES(
+        context, boxes.dim_size(2) == 4,
+        errors::InvalidArgument(
+            "The size of the third dimension of the box must be 4. Received: ",
+            boxes.dim_size(2)));
+
     const int64 batch_size = images.dim_size(0);
     const int64 height = images.dim_size(1);
     const int64 width = images.dim_size(2);
path: tensorflow/core/kernels/image/draw_bounding_box_op.cc