GitHub Copilot and similar AI tools are accelerating insider threats and external attacks. At DEF CON, researchers showed how prompt-injection attacks can trick AI bots into leaking customer data. Unmanaged devices running AI tools and users downloading data locally create new exfiltration paths that traditional DLP can't catch.
Yeah, I mean, right now, you know, with Copilot, a lot of concerns obviously around both insider threat, you know, considerations that you would have, but also, you know, just the consideration that attackers now have all this tooling, you know, that they never had access to before. If you think about how quickly they could penetrate your network if they had a chatbot like Copilot to begin to, you know, do a lot of reconnaissance within your environment, it could shorten the span, you know, to breach to, you know, escalation of privilege to lateral movement faster than we've ever seen, right? And, you know, DEF CON was a month ago. My co-founder went to there or went there, you know, to take part and just kind of visualize what was going on. And there was a lot of, you know, different use cases of attackers and hackers using AI to breach these networks. And I thought the most fascinating one was around these companies, right? They pitch that our product is AI-powered. I always think of that SpongeBob meme with the rainbow with the AI-powered above it there just to kind of express the hype cycle, right, of what that is. But these attackers are using that and they're using what's now known as prompt injection to be able to ping that bot, which is accessing data on the backend and they were able to pull out some sensitive customer information, you know, based off of just prompting it with different types of cues that exposed that to the front end. And Copilot's no different, right, when it comes to that. But when you talk about, you know, these AI tools being leveraged on these unmanaged devices and things of that nature, you know, it's even more of a broader attack surface for somebody to come in, expose, you know, a personal device in that nature, and then be able to use that to harvest, you know, all this data, you know, on the client environment or get access to Copilot because the user has it and surface all this sensitive data to move into ransom or whatever that might look like. So it's just kind of the speed of breach, you know, is significantly reduced with that exposure as well. And you want to understand from a data loss prevention perspective, you know, what clients or what users are doing, you know, from even a data exfiltration standpoint, right? Downloading things locally, um, and moving things into unmanaged locations.
