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QIF-T0071

high

Baseline adaptation poisoning (re-enrollment window exploitation)

Tier 4 — Demonstrated (Case Study / Observational)

Legacy status: EMERGING

Exploit the re-enrollment or adaptive baseline update window in BCI authentication systems. When a BCI recalibrates (daily calibration, post-seizure reset, firmware update, drift correction), inject adversarial signals during the enrollment period to corrupt the stored baseline. Three windows: (1) initial enrollment, (2) periodic recalibration, (3) drift-triggered adaptation. Once the baseline is poisoned, all subsequent authentication is compromised. This is the fundamental vulnerability that motivated QIF's baseline-free 'Biological TLS' architecture: by validating signals against universal biological physics (spatial dipole patterns, H-H compliance, 1/f scaling, microstates) rather than individual baselines, the entire attack surface is eliminated. Defense: Biological TLS validation (no baselines needed), multi-session enrollment consistency checks, anomaly detection during calibration windows. Derivation Log Entry 46.

Technique Details

Tactic
QIF-C.IM
Status
EMERGING
Bands
S1, S2, I0

Therapeutic Application

Exploitation of BCI re-enrollment windows to inject poisoned baseline neural data

Clinical Analog

Adaptive baseline recalibration for changing patient conditions

Treats

  • progressive neurological disease
  • medication changes affecting neural signals
  • post-surgical BCI recalibration

Neural Impact

3 of 7 neural bands affected

S1 S2 I0

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DSM-5-TR Diagnostic Mappings

Diagnostic category references for threat modeling, not diagnostic claims.

F43.2 Adjustment Disorder

Pathway: 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:L/CR:H/CD:H/CV:I/RV:P/NP:S
CVSS v4.0 CVSS:4.0/AV:A/AC:H/AT:P/PR:L/UI:N/VC:L/VI:H/VA:L/SC:N/SI:H/SA:L
7.4High
BICRCDCVRVNP
 

Governance

Neurorights at Risk

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

Consent Complexity
0.96 / 4.0

FDORA §3305 Compliance

Cyber Device
Regulatory Coverage
0.6 / 1.0
524B Requirements
TM VA SA PM
Regulatory Gaps
  • ! CVSS cannot express neural-specific impacts
  • ! High neural impact (NISS >= 7.0) without IEC 62443 coverage
  • ! Consent complexity under-matches neural impact (CCI/NISS mismatch)

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) 7.4 7.4 High -
Child (10yr) + ADHD 7.4 8.7 High +1.30
Adult with ALS 7.4 8.6 High +1.19

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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