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QIF-T0090

critical

WiFi CSI passive body sensing (through-wall vital signs, 3D pose reconstruction, respiratory and gait biometric inference via dedicated or commodity WiFi hardware)

Tier 3 — Demonstrated (Lab-proven)

Legacy status: DEMONSTRATED

WiFi Channel State Information (CSI) captures the multipath propagation characteristics between WiFi transmitter and receiver. Human body movements — including breathing (chest wall motion ~5mm), heartbeat (body surface vibration ~0.1mm), and walking — modulate the WiFi signal propagation paths. Two attack profiles: (1) DEDICATED HARDWARE — modified firmware on CSI-capable APs enables through-wall sensing (2-3 standard walls), 3D pose reconstruction, and multi-person vital sign extraction at up to 8m range. (2) CONSUMER-GRADE — standard WiFi chipsets (Intel 5300, Atheros, ESP32) with CSI-enabled drivers extract respiratory rate (±1 bpm at 3m) and gait identity (93% single-person, 78% multi-person) without dedicated hardware. Respiratory modulation: phase shift Δφ = 4π×Δd/λ ≈ 0.4-1.2 radians at 5 GHz (chest displacement 4-12mm). Gait produces Doppler shifts f_d = 2v×cos(θ)/λ ≈ 40 Hz at walking speed. CSI matrix: H(f,t) ∈ C^(N_tx × N_rx × N_sub). CRITICAL REGULATORY GAP: Respiratory rate = PHI under HIPAA (45 CFR 160.103) when linked to individual. Gait biometric = special category data under GDPR Art. 9. No consent mechanism exists for incidental WiFi CSI health data collection — a router collecting CSI for 'network optimization' simultaneously collects respiratory data from everyone in range. This is passive radar using existing infrastructure.

Technique Details

Tactic
QIF-S.HV
Status
DEMONSTRATED
Bands
S1, S2, S3

Therapeutic Application

WiFi OFDM subcarrier amplitude and phase modulation by human body movement, respiration, and gait; works through walls without any device on the target; both dedicated CSI hardware and commodity WiFi chipsets enable contactless physiological surveillance

Clinical Analog

Contactless vital sign monitoring for sleep studies, elder care, and post-surgical recovery

Treats

  • contactless sleep apnea detection (Liu et al. 2015, demonstrated ±1 bpm)
  • elderly fall detection and activity monitoring (no wearable required)
  • post-surgical respiration monitoring without chest bands (burn patients)
  • PTSD and anxiety monitoring via nocturnal breathing pattern analysis
  • COPD exacerbation early warning via respiratory pattern changes
  • Parkinson's gait analysis for medication timing optimization
  • smart home health sensing

Neural Impact

3 of 7 neural bands affected

S1 S2 S3

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Scoring

NISS v1.1 NISS:1.1/BI:N/CR:N/CD:N/CV:I/RV:F/NP:N
CVSS v4.0 CVSS:4.0/AV:A/AC:L/AT:P/PR:H/UI:N/VC:H/VI:N/VA:N/SC:H/SI:N/SA:N
2.0Low
BICRCDCVRVNP
 

Governance

Neurorights at Risk

This technique threatens 2 of the 4 proposed neurorights (Ienca & Andorno, 2017).

Consent Complexity
0.60 / 4.0

FDORA §3305 Compliance

Cyber Device
Regulatory Coverage
0.5 / 1.0
524B Requirements
TM VA SBOM SA PM
Regulatory Gaps
  • ! CVSS partially captures risk; neural dimensions missing
  • ! No FDA pathway for consumer sensor exploitation

Population Vulnerability

CRB vulnerability adjustment (γ=0.30) accounts for age, diagnosis severity, consent capacity, and device dependency.

Population NISS Base Adjusted Severity Delta
Adult (Default) 2.0 2.0 Low -
Child (10yr) + ADHD 2.0 2.4 Low +0.35
Adult with ALS 2.0 2.3 Low +0.32

Validation Status

Theoretical / Not yet validated. This technique has not been independently tested. See the validation dashboard for what has been tested.

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