I think the potential to generate "objectionable content" is the least of the risks that LLMs pose. If they generate objectionable content it's because they were trained on objectionable content. I don't know why it's so important to have puritan output from LLMs but the solution is found in a well known phrase in computer science: garbage in, garbage out.
An in the "attack" they just find a prompt they can put in that generates objectionable content. It's like saying `echo $insult` is an "attack" on echo. It's one thing if you can embed something sinister in an otherwise properly performing LLM that's waiting to be activated. I don't see the concern that with deliberate prompting you can get them to do something like this.
The problem would be if you have an AI system and you give it third party input, say you have an AI assistant that has permissions to your emails, calendars and documents. The AI would read email, summarize them, remind you of stuff, you can ask the AI to reply to people. But someone could send you a special crafted email and convince the AI to email them back some secret/private documents , or transfer some money to them.
Or someone creates an AI to score papers/articles, this attacks could trick the AI to give thee articles a big score.
Or you try to use AI to filter scam emails , but with this attacks the filter will not work.
Conclusion is that it will not be a simple plug and play the AI into everything.