Agents are also significantly smarter than the kinds of bots that are typically used to hack into systems. Bots are simple automated programs that run through scripts, so they struggle to adapt to unexpected scenarios. Agents, on the other hand, are able not only to adapt the way they engage with a hacking target but also to avoid detection—both of which are beyond the capabilities of limited, scripted programs, says Volkov. “They can look at a target and guess the best ways to penetrate it,” he says. “That kind of thing is out of reach of, like, dumb scripted bots.”
Since LLM Agent Honeypot went live in October of last year, it has logged more than 11 million attempts to access it—the vast majority of which were from curious humans and bots. But among these, the researchers have detected eight potential AI agents, two of which they have confirmed are agents that appear to originate from Hong Kong and Singapore, respectively.
“We would guess that these confirmed agents were experiments directly launched by humans with the agenda of something like ‘Go out into the internet and try and hack something interesting for me,’” says Volkov. The team plans to expand its honeypot into social media platforms, websites, and databases to attract and capture a broader range of attackers, including spam bots and phishing agents, to analyze future threats.
To determine which visitors to the vulnerable servers were LLM-powered agents, the researchers embedded prompt-injection techniques into the honeypot. These attacks are designed to change the behavior of AI agents by issuing them new instructions and asking questions that require humanlike intelligence. This approach wouldn’t work on standard bots.
