Also, how do CNNs draw a box around the target in the image?
You can, of course, tell the network to output whatever you want: all of the guesses, best guess, top five guesses, all guesses over a threshold, etc.
Note, this is a gross oversimplification, but it gets the general concept across.
In the past, some people did this inefficiently by just sliding a window across the image and using the same classifier you'd use for the first problem. But this is inefficient, and different sizes make it more inefficient. So the best solution is to use an "Object Detection" network, look into SSD or YOLO to see an example of this.
Effectively. That's what a DNN is, ANNs with multiple inference layers each one gives their "highest probability" and then the client/system sets the weight threshold for what is returned.