Researchers at the Karlsruhe Institute of Technology (KIT) in Germany have issued a warning about the potential for ordinary WiFi networks to identify individuals with remarkable accuracy. Their study, presented at the ACM’s Conference on Computer and Communications Security, demonstrates that using beamforming feedback information (BFI), routers can infer a person's identity with 99.5% accuracy. This technique relies on unencrypted feedback data from connected devices, which can be accessed without specialized equipment. The researchers conducted experiments with nearly 200 participants, analyzing how WiFi signals interact with people and objects to gather identifying information. They also compared this BFI method to an older technique called channel state information (CSI), which achieved an 82.4% accuracy rate. The implications of this technology are significant; it could allow for covert identification in public spaces, raising concerns about privacy. Co-author Julian Todt emphasized that individuals could be recognized by public authorities or companies without their knowledge. The researchers are urging the IEEE to implement stronger privacy safeguards in the forthcoming 802.11bf standard for WiFi sensing applications.