Large language models are now capable of automating attacks that were previously only possible by human adversaries. In this talk, I discuss several ways that adversaries could mis-use current models in order to cause harm both at a larger scale and at a lower cost than they do currently. For example, we find that recent state-of-the-art models can now find 0-day vulnerabilities in large software projects that have been extensively tested by humans for decades. These new capabilities will alter the threat landscape and require we rethink security in the coming years.
A black hat is a malicious(evil) hacker. The goal is unauthorized access of remote computer systems, typically. The closer to root the better.
A grey hat is a neutral hacker. Probably mostly a curiosity, no good or bad intent. Perhaps like someone who’s trying to reverse engineer a game console because they own a lot of games and they’re just curious how it all works. Or someone that just wants to make a backup of a movie (circumvent DRM.)
A white hat is a benevolent hacker that seeks to fix exploits that black hats use to perform their crimes. And they often target the greys(but usually the lawyers are more effective there.)