The security analysts (Danilo Avola, Daniele Pannone, Dario Montagnini, and Emad Emam) noted that the repositories already include scripts for automatic target enrollment: a would-be spy merely walks a hall with a smartphone, captures 100 Wi-Fi packets per person, and the transformer encoder—reportedly achieving 95.5% Rank-1 precision—learns a radio “fingerprint” that remains stable even if the subject changes clothes or carries a backpack. # whofi_persist.py — model self-refresh loop batch_q, batch_g = sampler.next() # passive CSI queue S_q, S_g = model(batch_q), model(batch_g) # embed signatures sim = torch.mm(S_q, S_g.T) # cosine (l2-normed) loss = F.cross_entropy(sim, torch.arange(sim.size(0))) loss.backward(); optimizer. Until firmware vendors expose CSI access only to signed drivers—and until SOCs learn to flag sustained raw-802.11 captures—WhoFi represents a disquieting leap in non-invasive surveillance, placing radio-frequency biometrics squarely in the attacker’s toolkit. With years of experience under his belt in Cyber Security, he is covering Cyber Security News, technology and other news. Cyber Security News is a Dedicated News Platform For Cyber News, Cyber Attack News, Hacking News & Vulnerability Analysis.
This Cyber News was published on cybersecuritynews.com. Publication date: Thu, 24 Jul 2025 12:40:14 +0000