QID 982515

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.

An attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`:

```python
import tensorflow as tf

images = tf.fill([53, 0, 48, 1], 0.)
boxes = tf.fill([53, 31, 4], 0.)
boxes = tf.Variable(boxes)
boxes[0, 0, 0].assign(3.90621)
tf.raw_ops.DrawBoundingBoxes(images=images, boxes=boxes)
```

This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses `CHECK_*` assertions instead of `OP_REQUIRES` to validate user controlled inputs. Whereas `OP_REQUIRES` allows returning an error condition back to the user, the `CHECK_*` macros result in a crash if the condition is false, similar to `assert`.

```cc
const int64 max_box_row_clamp = std::min<int64>(max_box_row, height - 1);
...
CHECK_GE(max_box_row_clamp, 0);
```

In this case, `height` is 0 from the `images` input. This results in `max_box_row_clamp` being negative and the assertion being falsified, followed by aborting program execution.