The original license that accounts for most of the code you are concerned with was released with an MIT license.
https://github.com/CompVis/stable-diffusion/commit/2ff270f4e... The August 10th update made unenforceable rules about how the pre-trained model can be used or distributed. A new license was added to an entire codebase that was already partially released under the MIT license. So only the new code would have copyright reserved. That alone makes most of your argument a moot point.
The actual scripts being used were committed to the repo on August 21st. https://github.com/hlky/stable-diffusion/commit/1d0036cb6644... And these actual scripts being used don't seem to be modified from the ones that were relicensed with the rights reserved.
The crux of the situation for me is that at no point during the release of the pre-trained model do the authors claim any sort of copyright on the images produced, if the end user is generating on their own hardware. There's no meaningful way to legally enforce the current CreativeML Open RAIL-M or the previous MIT derived license that creates rules about how the output of the software can be used.
That is something that has been confusing me, but I imagine it will get cleared up sooner rather than later.
The additional rules are effectively an acceptable use policy. There is no meaningful legal consequence of breaking acceptable use policy. The most that can be done is that an end user will no longer be allowed to used the pre-trained models. Additionally acceptable use policy has to specify a jurisdiction. In the US, breaking acceptable use policy does not amount to violating the CFAA.
The actual license seems mostly about a way for there to be no way to hold the authors of the models accountable for any illegal activity done by the end users. Which is completely fair and understandable.
This kind of misunderstanding and fear-based approach to reusing code is what holds back progress and seems to be what the authors actively tried to fight by releasing the current repo with a CreativeML Open RAIL-M license.
I believe the intent of the authors is as important as the exact text of the repository. Especially since the cited sources for the foundation this was built of off, x-transformers by lucidrains, OpenAI's ADM codebase, and Denoising Diffusion Probabilistic Model, in Pytorch by lucidrains are all licensed with MIT. Most importantly, the restrictive license is based almost completely on the condition that the end user is using their pre-trained model. If the end-user manages to create and uses their own model from scratch, there is no reason for any part of the original repo license to apply.