Skip to content

QIF-T0106

high

Neural sinkhole

Tier 5 — Theoretical (Modeled / Simulated)

Legacy status: THEORETICAL

Attract and drop neural signals by advertising a compromised node as optimal routing point. Neural signals are diverted and silently discarded. Analogous to sinkhole attacks in sensor networks. From Murcia neural cyberattack taxonomy.

Technique Details

Tactic
QIF-P.DS
Status
THEORETICAL
Bands
I0, N2

Therapeutic Application

Attracting and absorbing BCI network traffic by advertising false optimal routing, creating a data collection point analogous to network sinkhole attacks

Neural Impact

2 of 7 neural bands affected

I0 N2

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.

Scoring

NISS v1.1 NISS:1.1/BI:H/CR:H/CD:H/CV:E/RV:P/NP:N
5.4Medium
PINSPINS triggers when Biological Impact is High/Critical or Reversibility is Irreversible. Indicates potential lasting harm to neural safety.
BICRCDCVRVNP
 

Governance

Neurorights at Risk

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

Consent Complexity
0.12 / 4.0

FDORA §3305 Compliance

Non-Cyber Device (missing: software)
Regulatory Coverage
0.1 / 1.0
524B Requirements
TM VA SA PM
Regulatory Gaps
  • ! CVSS cannot express neural-specific impacts
  • ! 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) 5.4 5.4 Medium -
Child (10yr) + ADHD 5.4 6.4 Medium +0.95
Adult with ALS 5.4 6.3 Medium +0.87

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