Regulation is easier said than done, in part because the regulation surface, so to speak, is broad and complicated.
Even a badly misaligned LLM is only as dangerous as its tools, but that's a poor regulation target because it turns out to be very very difficult (probably impossible with current LLM technology) to build a toolkit that is both useful for autonomous work and safe in the sense that it can't escape its own sandbox or otherwise perform malicious actions, whether it's because of misalignment or because of malicious prompt injection.
Another option is to regulate the training process. Perhaps an LLM may not be legally distributed unless it contains certain RL steps that penalize malicious behavior and reward self regulation. That that's going to seriously limit innovation while also heavily favoring incumbent labs who can check the boxes and maintain a paper trail of such things.
The other option is to regulate observed behavior, like how airplanes and cars have to meet certain minimum requirements but have some latitude in how they can achieve those requirements. In a framework like this, you can't distribute an LLM until it's past some formal audit or testing procedure, with some kind of formal certification regulators will ask you for and fine you if you don't have it.
Regulating observed behavior is maybe the most tractable approach, and it also works the best with our existing frameworks for regulation, where you always have some kind of a division between DIY/hobby projects, which tend to be lightly regulated, and commercial projects, which tend to be more heavily regulated. Of course, even drawing such a line itself will be challenging.
And that's before you get into any problems of regulatory capture, fun stuff.