A recent study from the Karlsruhe Institute of Technology in Germany has unveiled alarming privacy vulnerabilities in standard Wi-Fi routers, which can identify individuals with a remarkable accuracy of 99.5%. This identification is made possible through a technique known as beamforming feedback information (BFI), which enhances Wi-Fi connectivity but inadvertently exposes personal data. The researchers analyzed feedback signals from 161 participants, demonstrating that even minor changes in movement, such as carrying objects, only reduced identification accuracy to between 50% and 60%. The study highlights that the feedback data is unencrypted and accessible without needing to connect to the router, posing severe privacy risks as Wi-Fi technology becomes more ubiquitous in homes and public spaces. The researchers argue that this method of identity inference constitutes a privacy attack and call for stronger privacy protections or the abandonment of beamforming. Their findings contrast with other Wi-Fi tracking systems, emphasizing the need for regulatory action to safeguard individual privacy.