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QIF-T0031

medium

Battery drain attack (resource depletion)

Tier 5 — Theoretical (Modeled / Simulated)

Legacy status: THEORETICAL

Force BCI processor to perform computationally expensive tasks (e.g., continuous high-rate sampling, unnecessary ML inference) to drain battery faster than normal. Critical for implanted BCIs where battery replacement requires surgery. Wearable BCIs also affected during critical use periods.

Technique Details

Tactic
QIF-P.DS
Status
THEORETICAL
Bands
S1, S2

Therapeutic Application

Accelerated battery depletion of implanted BCI through sustained high-power operation

Neural Impact

2 of 7 neural bands affected

S1 S2

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Scoring

NISS v1.1 NISS:1.1/BI:L/CR:N/CD:N/CV:N/RV:F/NP:N
CVSS v4.0 CVSS:4.0/AV:A/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:L
0.7Low
BICRCDCVRVNP
 

Governance

Neurorights at Risk

This technique threatens 1 of the 4 proposed neurorights (Ienca & Andorno, 2017).

Consent Complexity
0.10 / 4.0

FDORA §3305 Compliance

Cyber Device
Regulatory Coverage
0.6 / 1.0
524B Requirements
TM VA SBOM PM
Regulatory Gaps
  • ! 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) 0.7 0.7 Low -
Child (10yr) + ADHD 0.7 0.8 Low +0.12
Adult with ALS 0.7 0.8 Low +0.11

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