Detecting Halo in Images
If I understand you correctly then you have complete black images with white borders?
In this case I think the easiest approach is to compute a histogram of the intensity values of the pixels, i.e. how „dark/bright” is the overall image. I guess that the junk images are significantly darker than the non-junk images. You can then filter the images based on their histogram. For that you have to choose a threshold: Every image darker than this threshold is considered as junk.
If this approach is to fuzzy you can easily improve it. For example: just compute the histogram of the inner image without the edges, because this makes the histogram much more darker in comparison to non-junk images.
I've never done any image processing and I was wondering if someone can nudge me in the right direction. 
Here's my issue: I have a bunch of images of black and white images of places around a city. Due to some problems with the camera system, some images contain nothing but a black image with a white vignette around the edge. This vignette is noisy and non-uniform (sometimes it can be on both sides, other times only one).
What are some good ways I can go about detecting these frames? I would just need to be able to  write a bit.
My image set is huge, so I would need this to be an automated process and in the end it should use Python since it needs to integrate into my existing code.
I was thinking some sort of machine learning algorithm but I'm not sure what to do beyond that.