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QIF-T0099

critical

Consumer-sensor-to-BCI kill chain escalation (pre-implant reconnaissance and cognitive priming via consumer devices)

Tier 5 — Theoretical (Modeled / Simulated)

Legacy status: THEORETICAL

This capstone technique documents the full S-domain-to-BCI escalation kill chain: how consumer sensor exploitation serves as reconnaissance and preparation for subsequent BCI attacks. The chain proceeds in phases: (1) RECON — Consumer sensors (phone, watch, earbuds) establish behavioral baseline: gait patterns (T0088), cardiac signature (T0093), neurological profile (T0089), cognitive patterns (T0085 if VR/AR). (2) FINGERPRINT — Multi-modal biometric fusion (T0096) creates persistent identity profile. (3) PROFILE — Cross-device correlation (T0097) builds comprehensive health/cognitive baseline. (4) ESCALATE — When the target receives a BCI (medical implant, consumer neural interface), the attacker's pre-existing profile informs: optimal attack parameters for neural injection (calibrated to individual's neural baseline), personalized evasion of anomaly detection (trained on their 'normal'), and targeted cognitive exploitation (leveraging known cognitive vulnerabilities). The S-domain reconnaissance makes BCI attacks more effective, more targeted, and harder to detect. This technique represents the strategic justification for the entire S-domain: consumer sensors are the advance scout for future BCI exploitation.

Technique Details

Tactic
QIF-S.CH
Status
THEORETICAL
Bands
S1, S2, S3, I0, N1, N7

Therapeutic Application

Full S-domain-to-BCI escalation: consumer sensor reconnaissance builds behavioral/physiological/cognitive baseline that informs and optimizes subsequent BCI attack parameters

Clinical Analog

Pre-surgical neurological baseline assessment for BCI implant calibration

Treats

  • BCI implant pre-surgical planning (behavioral baseline)
  • neural interface calibration (cognitive baseline)
  • personalized neuroprosthetic fitting
  • rehabilitation baseline assessment

Neural Impact

6 of 7 neural bands affected

S1 S2 S3 I0 N1 N7

Drag to rotate. Click a region to learn more.

Click or hover over a glowing region to see the attack techniques targeting it and their severity.

DSM-5-TR Diagnostic Mappings

Diagnostic category references for threat modeling, not diagnostic claims.

F43.2 Adjustment Disorder F45 Somatoform disorders F44.4 Conversion Disorder F20 Schizophrenia Spectrum F32 Major Depressive Disorder F90 ADHD F42 OCD F82 Developmental Coordination Disorder F30 Manic episode F43 PTSD / Trauma F80 Communication Disorders F60 Personality Disorders F63 Impulse-Control Disorders F01 Vascular dementia F98.4 Stereotyped movement disorders

Pathway: N7 (PFC/M1) → executive function; I0 (electrode-tissue boundary) → measurement

Following Poldrack (2006), brain region disruption does not uniquely predict psychiatric outcomes.

Scoring

NISS v1.1 NISS:1.1/BI:N/CR:H/CD:H/CV:I/RV:T/NP:T
CVSS v4.0 CVSS:4.0/AV:N/AC:H/AT:P/PR:L/UI:N/VC:H/VI:H/VA:L/SC:H/SI:H/SA:L
4.7Medium
BICRCDCVRVNP
 

Governance

Neurorights at Risk

This technique threatens 6 of the 4 proposed neurorights (Ienca & Andorno, 2017).

Consent Complexity
2.25 / 4.0

FDORA §3305 Compliance

Non-Cyber Device (missing: software)
Regulatory Coverage
0.2 / 1.0
524B Requirements
TM VA SA PM
Regulatory Gaps
  • ! CVSS cannot express neural-specific impacts
  • ! No FDA pathway for consumer sensor exploitation
  • ! Threat not yet in regulatory threat catalogs

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) 4.7 4.7 Medium -
Child (10yr) + ADHD 4.7 5.5 Medium +0.83
Adult with ALS 4.7 5.5 Medium +0.76

Validation Status

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

Qinnovate Neural Security Atlas Edit this on GitHub