So, it only works against open source AI; basically only Stable Diffusion at this point.

I very much doubt it even works against the multitude of VAEs out there. There's not just the ones derived from StabilitiyAI's models but ones right now simply intended to be faster (at a loss of quality): TAESD can also encode and has a completely different architecture thus is completely unlikely to be fooled by the same attack vector. That failing, you can use a simple affine transformation to convert between latent and rgb space (that's what "latent2rgb" is) and compare outputs to know whether the big VAE model got fooled into generating something unrelated. That thing just doesn't have any attack surface, there's several magnitudes too few weights in there.

Which means that there's an undefeatable way to detect that the VAE was defeated. Which means it's only a matter of processing power until Nightshade is defeated, no human input needed. They'll of course again train and try to fool the now hardened VAE, starting another round, ultimately achieving nothing but making the VAE harder and harder to defeat.

It's like with Russia: They've already lost the war but they haven't noticed, yet -- though I wouldn't be too sure that Nightshade devs themselves aren't aware of that: What they're doing is a powerful way to grift a lot of money from artists without a technical bone in their body.