AI systems have long been treated like sealed black boxes, especially in areas like facial recognition and autonomous driving. New research suggests that protection isn’t as solid as assumed.
A KAIST-led team shows that AI systems can be reverse engineered remotely using emissions that leak during normal operation, without direct intrusion. Instead, the approach listens.
Using a small antenna, the researchers captured faint electromagnetic traces from GPUs and rebuilt how the system was designed. It sounds like a heist trick, but the results hold up, and the security implications are immediate.
The system, called ModelSpy, collects electromagnetic output produced while GPUs handle AI workloads These traces are subtle, yet they follow patterns tied to how the architecture is arranged.
By analyzing those patterns, the team inferred key details, including layer setups and parameter choices. Tests showed core structures could be identified with up to 97.6 percent accuracy.
The setup is what makes this unsettling. The antenna fits inside a bag and doesn’t need physical access. It worked from as far as six meters away, even through walls, across multiple GPU types. Computation itself becomes a side channel, exposing the system’s design without a traditional breach.
This pushes AI security into less familiar territory. Most defenses focus on software exploits or network access. ModelSpy targets the physical byproducts of computation instead.
Even isolated systems could leak sensitive information if hardware emissions aren’t controlled. For companies, that architecture is often core intellectual property, which turns this into a direct business risk.
The work frames this as a cyber physical challenge, where defending AI now involves both digital safeguards and the surrounding environment, which raises the bar for what protection actually means.
The team also outlined ways to reduce the risk, including adding electromagnetic noise and adjusting how computations run so patterns become harder to interpret
Those fixes suggest a broader change. Securing AI may require hardware level adjustments, not just software updates, which complicates deployment for industries already locked into existing systems.
The research earned recognition at a major security conference, signaling how seriously this threat is being taken. The next exposure may not involve breaking in at all, but simply observing what systems unintentionally reveal.
Did you think hitting delete on your AI chatbot conversation actually makes it disappear? Georgia Tech researchers just proved that's not entirely true. They have built a forensic tool called ORISA that can dig deleted conversations from your phone and even rebuild them into a working chatbot session you can keep talking to.
How can ORISA bring deleted AI conversations back?
Touchscreen laptops have been around for years. You can get them in all sizes and shapes. Just not from Apple. For years, the Cupertino giant has treated the idea of a touchscreen MacBook the way I treat a meeting that could have been an email: with open contempt. However, Wednesday looks like the day the company could finally change its mind.
The latest Apple invite puts the “Pro and Tell” showcase in Los Angeles at 10 a.m. PT (1 p.m. ET) on October 28, 2026. Instead of a regular live-streamed keynote, it is an invitation-only, hands-on event for a handful of press and creators (similar to what the company did for the MacBook Neo earlier this year).
Two residents of Chicago have filed a lawsuit in the US over claims that robots run by Coco Robotics and Serve Robotics captured their facial and hand measurements without consent, bringing renewed attention to the food delivery robots. The cases raise a troubling question: If a robot delivers food to your door, can it also be gathering sensitive information about you?
According to a report by The Associated Press, the proposed class-action lawsuits were filed in Cook County on Oct. 9 and allege violations of Illinois’ Biometric Information Privacy Act. The complaints claim that the robots’ cameras and LiDAR sensors captured information on customers’ faces and hands as they approached the machines to pick up their orders. Both have denied the allegations.