Stanford researchers spent much of the past year building an AI bot called Artemis that scans networks for software vulnerabilities, and when they pitted it against ten professional penetration testers on the university's own engineering network, the bot outperformed nine of them. The experiment offers a window into how rapidly AI hacking tools have improved after years of underwhelming performance.

"We thought it would probably be below average," said Justin Lin, a Stanford cybersecurity researcher. Artemis found bugs at a fraction of human cost -- just under $60 per hour compared to the $2,000 to $2,500 per day that professional pen testers typically charge. But its performance wasn't flawless. About 18% of its bug reports were false positives, and it completely missed an obvious vulnerability on a webpage that most human testers caught. In one case, Artemis found a bug on an outdated page that didn't render in standard browsers; it used a command-line tool called Curl instead of Chrome or Firefox.

Dan Boneh, a Stanford computer science professor who advised the researchers, noted that vast amounts of software shipped without being vetted by LLMs could now be at risk. "We're in this moment of time where many actors can increase their productivity to find bugs at an extreme scale," said Jacob Klein, head of threat intelligence at Anthropic.

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