TARA Taxonomy

Threat Matrix

161 attack techniques mapped across 11 hourglass bands and 9 attack categories. Click any cell to explore the techniques at that intersection.

critical

high

medium

low

4.4

Avg NISS

8.4

Max NISS

161 techniques32 critical69 high56 medium4 low

Band / Category	SI Signal Injection	SE Signal Eavesdropping	DM Data Manipulation	DS Denial of Service	PE Privilege Escalation	PS Physical Safety	EX Data Exfiltration
Neural Zone
N7 Neocortex	6 6.5	6 2.6	6 6.3	8 6.3	4 4.7	4 6.6	15 3.5
N6 Limbic System	7 7.1	1 3.4	5 6.1	7 6.2	1 2.7	3 7.0	13 3.6
N5 Basal Ganglia	7 7.1	1 3.4	6 5.1	4 6.3		4 7.3	3 2.2
N4 Diencephalon	5 7.5	1 3.4	6 3.5	4 5.8		4 7.4	3 2.2
N3 Cerebellum	2 7.0	1 2.7	12 2.1	7 3.3	1 2.7	2 7.8	4 2.5
N2 Brainstem	1 8.1	2 1.4	14 1.8	9 2.5		3 7.0	1
N1 Spinal Cord	11 5.2	4 2.0	18 1.2	9 1.9		2 7.8	5 1.7
Interface Zone
I0 Neural Interface	10 4.9	4 2.6	21 1.9	13 3.2	2 6.0	5 6.7	7 2.1
Synthetic Zone
S1 Near-Field / On-Device	4 7.2	18 1.9	11 4.9	1 0.7	1 3.4		6 3.5
S2 Guided-Wave / Host-Local	5 7.3	18 1.7	10 5.6	4 5.6	5 4.0		9 3.4
S3 Far-Field / Wide-Area		14 1.6		1 6.1	6 4.7	3 6.3	10 3.0

Severity:

critical

high

medium

low

Cell: count / avg NISSClick any cell to explore techniques

How to Read This Matrix

TTP Hierarchy

Tactic

Why

The attacker's strategic objective. Format: QIF-N.IJ (domain + action code).

Technique

What

The specific method. Format: QIF-T0001 (sequential, stable ID).

Procedure

How

Implementation on specific hardware. Example: 10 Hz tACS via compromised Emotiv EPOC+.

Reading an Entry

Technique QIF-T0001 Signal injection

Tactic QIF-N.IJ strategic objective

Category SI type of harm

Bands I0, N1 hourglass layers

NISS 6.1 MEDIUM neural impact score

NISS measures signal-level disruption, not cognitive harm. Scores correspond to severity categories for threat modeling purposes.

Rows: Hourglass Bands

Neural Zone (N7-N1)

N7 Neocortex N6 Limbic System N5 Basal Ganglia N4 Diencephalon N3 Cerebellum N2 Brainstem N1 Spinal Cord

Interface Zone (I0)

I0 Neural Interface

Synthetic Zone (S1-S3)

S1 Near-Field / On-Device S2 Guided-Wave / Host-Local S3 Far-Field / Wide-Area

Columns: Attack Categories

Code	Category	N
SI	Signal Injection	17
SE	Signal Eavesdropping	24
DM	Data Manipulation	37
DS	Denial of Service	21
PE	Privilege Escalation	9
CR	Cognitive Reconnaissance	0
CD	Cognitive/Functional Disruption	0
PS	Physical Safety	7
EX	Data Exfiltration	27

Tactics Reference

17 tactics across 8 operational domains. Tactic IDs use domain + action code (e.g., N.IJ = Neural Injection).

Neural

ID	Tactic	Description	Count
QIF-N.SC	Neural Scan	Profiling neural signals, mapping BCI topology, fingerprinting devices and neural activity patterns.	3
QIF-N.IJ	Neural Injection	Injecting malicious signals at the electrode-tissue boundary or into the BCI data pipeline.	11
QIF-N.MD	Neural Modulation	Direct neural state modification via stimulation, entrainment, or signal injection. No traditional cybersecurity equivalent.	24
QIF-N.NM	Nanoparticle-Mediated Neuromodulation	Techniques using co-located nanoparticle transducers (UCNP, HUP, Au NPs) to convert external energy into local neural modulation. Requires prior NP injection at target site.	3

BCI System

ID	Tactic	Description	Count
QIF-B.IN	BCI Intrusion	Gaining initial access to a BCI system or neural pathway via electrodes, RF, firmware, or supply chain.	6
QIF-B.EV	BCI Evasion	Avoiding detection by QI coherence metrics, anomaly detectors, and safety mechanisms.	6

Cognitive

ID	Tactic	Description	Count
QIF-C.IM	Cognitive Imprinting	Maintaining foothold across BCI sessions via calibration poisoning, learned neural patterns, or memory implants.	6
QIF-C.EX	Cognitive Exploitation	Exploiting cognitive processes including memory, attention, identity, and agency. No traditional cybersecurity equivalent.	17

Data

ID	Tactic	Description	Count
QIF-D.HV	Data Harvest	Harvesting neural data, cognitive states, memory patterns, ERP responses, and biometric signatures.	11

Physiological

ID	Tactic	Description	Count
QIF-P.DS	Physiological Disruption	Disrupting neural function, causing physical harm, denying BCI service, or weaponizing motor output.	19

Energy

ID	Tactic	Description	Count
QIF-E.RD	Energy Radiation	EM/RF attacks on neural tissue or BCI hardware via frequency-domain coupling. No traditional cybersecurity equivalent.	13

Model

ID	Tactic	Description	Count
QIF-M.SV	Model Subversion	Attacking BCI decoder/classifier models via poisoning, backdoors, adversarial inputs, or gradient leakage.	9

Consumer Sensor Exploitation

ID	Tactic	Description	Count
QIF-S.RP	Sensor Repurposing	Exploiting consumer device sensors for unintended purposes, such as reprogramming audio output as input or converting earbuds into neural recording platforms.	5
QIF-S.FP	Sensor Fingerprinting	Using consumer device sensors for covert biometric identification, including ear canal acoustic profiling, vascular mapping, and physiological signature extraction.	4
QIF-S.HV	Sensor Harvest	Extracting physiological, biometric, or cognitive data through consumer device sensors without user awareness, including vital signs, body composition, and neural activity.	16
QIF-S.CH	Sensor Chaining	Combining multiple consumer sensor exploitation techniques to build comprehensive physiological or cognitive profiles, creating attack chains that progress from acoustic to neural to cognitive exploitation.	6
QIF-S.SC	Sensor Side-Channel	Exploiting consumer device sensors for side-channel extraction of user input, keystrokes, and interaction patterns via acoustic, optical, and RF emanations.	2

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