Removing harmful information from the dataset could be a way to do this, but it also makes the tool less useful, and it's hard, so companies aren't really doing that. There's the additional issue that with the rise of Reinforcement Learning being used to train these tools, they're not just learning from their training data - they basically try a million things and then get rewarded for doing things that work - so they can even discover hacking techniques from scratch.
Additionally, and not completely relevant to this discussion, there is a possibility that some users ask the tool to pursue goals that purposely harm a lot of people, such as developing weapons, hacks and viruses.
The things that's "new" here is that the tool is both very good (meaning, for example, that it's much easier for me to hack into an online service with an agent powered by a frontier llm than it was using google 6 years ago), and hard to control (google never hacked into an Australian government database when I asked it to find me some information).
So yeah, an LLM powered agent is a tool, and Google is a tool, and a hammer is a tool, and both can be used for good things and bad things, but the agent is (much) more powerful and more unpredictable. It also seems like the agents are getting more powerful and more unpredictable by the day - we didn't have this issue with GPT-3 or even the first LLM-powered agents - so people are very worried about what the agents 6 months from now will do, both when asked to do harmful things on purpose, and when asked to do harmless things.
Are you not worried? And is that because you think these incidents are basically the AI companies making them happen on purpose for marketing?