QID 982478

Security update has been released for tensorflow,tensorflow-cpu,tensorflow-gpu to fix the vulnerability.

Note: The preceding description block is extracted directly from the security advisory. Using automation, we have attempted to clean and format it as much as possible without introducing additional issues.

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.