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PRIVACY NIGHTMARE IN PLAIN SIGHT: WIFI CAN BE HIJACKED TO SEE PEOPLE THROUGH WALLS

  • Writer: Mark Playne
    Mark Playne
  • May 29
  • 3 min read


VIDEO



But could it work? This November 2025 proves the tech to be true:

"BFId: Identity Inference Attacks Utilising Beamforming Feedback Information"


  • Published 19 November 2025

  • Computer Science, Engineering


You can download the paper below. Meanwhile, here is a summary:


Paper Summary: WiFi Identity Inference via Beamforming Feedback

This is a 2025 ACM CCS paper that investigates a privacy nightmare hiding in plain sight—your WiFi router's beamforming feedback data can be used to identify you with frightening precision, no specialised hardware required.


The Core Finding

The researchers developed BFId, the first identity inference attack using Beamforming Feedback Information (BFI)—data that WiFi access points and clients exchange unencrypted over the air to optimize signal direction. Their results are staggering:

99.5% identification accuracy across 197 participants, using off-the-shelf hardware. Why This Is Worse Than Previous Attacks

Attack Type

Barrier to Entry

Encryption

CSI-based (older)

Requires modified firmware, specific hardware

Not broadcast

BFI-based (this paper)

Any device within range can capture it

Unencrypted, broadcast openly

The critical distinction: BFI is broadcast in the clear. A single malicious device sitting anywhere within WiFi range can record the beamforming feedback between the router and every legitimate client. No firmware hacks. No physical access. Just listen.


How It Works

  1. Beamforming (introduced in WiFi 5/802.11ac) uses physical environment data to steer signals toward clients for better bandwidth

  2. Clients send back BFI—a compressed representation of how the signal propagated through the environment

  3. This compression actually filters out noise, potentially making BFI better than raw CSI for sensing

  4. The authors fed this data into recurrent neural networks to classify individuals by their unique gait and body interference patterns


The Privacy Implications

This isn't theoretical lab work. The paper explicitly warns:

  • IEEE is standardising WiFi sensing (802.11bf) with zero privacy protections built in

  • BFI works across multiple perspectives, walking styles, and reduced sample rates

  • It scales to large populations (197 subjects is far larger than prior studies which typically used a handful)

  • The adversary model is terrifyingly weak: anyone with a laptop in a coffee shop, apartment building, or office can passively identify individuals moving through the space


The Real-World Threat

Think about what this means in practice. Every modern WiFi network is silently broadcasting enough data to:

  • Track individuals through smart buildings without their knowledge

  • Identify people in their own homes by a neighbour or a device on the street

  • Build persistent identity profiles tied to unique body-interference signatures—a biometric you cannot change


The authors frame this as "privacy risk investigation," but the subtext is clear: the infrastructure is already deployed, the data is already flowing unencrypted through the air, and the industry is actively working to standardise and expand these capabilities without any meaningful privacy safeguards.


WHAT THIS MEANS FOR US

Your WiFi router is a surveillance device that can tell who is in a room, what they're doing, and how they're moving... all from data that is deliberately left unencrypted and broadcast for anyone to harvest. The 99.5% accuracy figure should be deeply unsettling. This is not a future threat; the hardware is in your home right now.




DOWNLOAD PAPER



We published this article on this issue earlier in the month, showing how easy it is to do this: https://www.notonthebeeb.co.uk/post/wi-fi-has-major-privacy-concerns-that-will-shock-you



VIDEO- The dangers of WIFI's 2.44 GHZ

Interview by NOTB with the highly respected Dr Klinghardt



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