UAIF Schema Specification

Document status and notice

UAIF™ SCHEMA v1.0

Schema Specification — Final Publication v1.0
TCR-STD-003 | Q2 2026 | Normative errata integrated 14 August 2026 | Licensed under GAISSF Ecosystem Licence (GEL v1.0)

Published by ODA3 Institute. This document is the normative machine-readable schema companion to TCR-STD-002 UAIF™ v1.0 Technical Specification.

Status and Authority

The schema is named UAIF™ Schema v1.0. No separate schema-layer brand or trademark is used. TCR-STD-002 is normative for calculation, regulatory trigger logic, conformance architecture, and controlled vocabulary. This schema SHALL conform to TCR-STD-002.

UAIF™ v1.0 is a Final Publication. The canonical schema has been validated as Draft 2020-12 and its 15-case positive/negative conformance corpus has produced the expected 15/15 result using both the purpose-built gate harness and an independent generic jsonschema 4.26.0 Draft 2020-12 validator.

Notably Absent

• No submitter PII fields; use hashed or external contact references.

• No proprietary sector calibration weights.

• No full STIX translation profile; mapping fields are limited to approved identifiers such as atlas_technique_id.

• No certification or audit authority granted by schema use.

• No obsolete EU AI Act incident-reporting proxy references; UAIF uses Article 73 for serious-incident routing assistance.

• No claim that schema validation establishes legal compliance or empirical deployment maturity.

1. Schema Naming and Versioning

2. 7-Layer Architecture Alignment

The UAIF Schema follows the 7-layer architecture in TCR-STD-002. L7 AI Control Plane Extensions are merged into L5 and SHALL NOT be represented as a separate conformance layer.

3. Profile Conformance

4. Normative JSON Schema

The following JSON Schema is normative and is identical to the accompanying canonical machine-readable artifact uaif-core-v1.0.json.

{

"$schema": "https://json-schema.org/draft/2020-12/schema",

"$id": "https://schemas.oda3.org/uaif/core/v1.0/uaif-core-v1.0.json",

"title": "UAIF Core Profile Schema v1.0",

"$comment": "Normative errata build. Authority chain: TCR-STD-002 semantics -> TCR-STD-003 schema spec -> this canonical schema -> /fixtures -> COM-012. See ODA3-2026-08-ERR-UAIF-001.",

"type": "object",

"required": [

"incident_uuid",

"incident_title",

"incident_summary",

"reporting_timestamp",

"deduplication_hash",

"remediation_status",

"record_type",

"profile",

"root_cause_primary_domain",

"root_cause_specific_type",

"sector_code",

"jurisdiction_country_code"

],

"properties": {

"incident_uuid": {

"type": "string",

"format": "uuid"

},

"incident_title": {

"type": "string",

"minLength": 5,

"maxLength": 255

},

"incident_summary": {

"type": "string",

"minLength": 20,

"maxLength": 4000

},

"reporting_timestamp": {

"type": "string",

"format": "date-time"

},

"reporter_confidence_level": {

"type": "integer",

"minimum": 1,

"maximum": 5

},

"deduplication_hash": {

"type": "string",

"pattern": "^[a-fA-F0-9]{64}$"

},

"remediation_status": {

"type": "string",

"enum": [

"Detected",

"Investigating",

"Mitigated",

"Resolved"

]

},

"record_type": {

"type": "string",

"description": "L0. Ontological classification of the record. Two normative values only. Unclassified signals, alerts, telemetry, or investigative leads are not a UAIF record_type; they remain in the originating detection/case-management workflow until classified.",

"enum": [

"Incident",

"Vulnerability"

]

},

"profile": {

"type": "string",

"description": "L0. Base conformance depth declared by the record. See 'extensions' for additive specialized capabilities, which are declared separately and do not affect this value.",

"enum": [

"Core",

"Enterprise",

"Regulatory"

]

},

"extensions": {

"type": "array",

"description": "L0. Optional, additive specialized capability declarations. Extensions never reduce or override base-profile requirements.",

"items": {

"type": "string",

"enum": [

"SOC_SIEM",

"AI_Security"

]

},

"uniqueItems": true

},

"root_cause_primary_domain": {

"type": "string",

"enum": [

"Human",

"System",

"Data",

"External"

]

},

"root_cause_specific_type": {

"type": "string",

"pattern": "^(Adversarial_Attack|Prompt_Injection|Model_Poisoning|Data_Poisoning|RAG_Leakage|Hallucination|Agent_Escalation|Policy_Violation|System_Failure|Human_Error|Supply_Chain_Compromise|Unauthorised_Access|Data_Breach|Denial_of_Service|Misuse|x_[A-Za-z0-9_]+)$"

},

"root_cause_confidence": {

"type": "string",

"enum": [

"LOW",

"MEDIUM",

"HIGH"

]

},

"exploit_path_description": {

"type": "string",

"minLength": 20,

"maxLength": 4000

},

"severity_analytical_score": {

"type": "number",

"minimum": 0.0,

"maximum": 10.0,

"description": "One-decimal-place precision (ROUND_HALF_UP) is a normative semantic/conformance rule per TCR-STD-002 Section 4.4, verified by the reference implementation and conformance tooling -- deliberately NOT enforced via JSON Schema 'multipleOf', since binary floating-point representation of decimal fractions (e.g. 2.8, 5.1, 9.1) can produce false negatives across validator implementations."

},

"severity_presentation_score": {

"type": "number",

"minimum": 0.0,

"maximum": 10.0,

"description": "One-decimal-place precision (ROUND_HALF_UP) is a normative semantic/conformance rule per TCR-STD-002 Section 4.4, verified by the reference implementation and conformance tooling -- deliberately NOT enforced via JSON Schema 'multipleOf', for the same floating-point interoperability reason as severity_analytical_score."

},

"severity_level": {

"type": "integer",

"minimum": 1,

"maximum": 5

},

"severity_rationale": {

"type": "object",

"description": "L2. Sole canonical severity explanation. There is no separate severity_justification field in UAIF v1.0 -- superseded, see Section 9 legacy patterns.",

"required": [

"calibration_status"

],

"properties": {

"dominant_harm": {

"type": "string",

"enum": [

"Physical_Harm",

"Environmental_Harm",

"Security_Integrity",

"Privacy_Violation",

"Financial_Loss",

"Psychological_Harm",

"Property_Damage",

"Reputational_Harm"

]

},

"dominant_weight": {

"type": "number"

},

"secondary_harms": {

"type": "array",

"items": {

"type": "string",

"enum": [

"Physical_Harm",

"Environmental_Harm",

"Security_Integrity",

"Privacy_Violation",

"Financial_Loss",

"Psychological_Harm",

"Property_Damage",

"Reputational_Harm"

]

}

},

"secondary_contribution": {

"type": "number"

},

"context_modifiers_applied": {

"type": "array",

"items": {

"type": "object",

"required": [

"context",

"base_value",

"contribution_factor",

"effective_contribution"

],

"properties": {

"context": {

"type": "string"

},

"base_value": {

"type": "number"

},

"contribution_factor": {

"type": "number"

},

"effective_contribution": {

"type": "number"

}

},

"additionalProperties": false

}

},

"context_modifier_sum": {

"type": "number"

},

"population_multiplier": {

"type": "number"

},

"blast_radius_multiplier": {

"type": "number"

},

"impact_scale": {

"type": "number"

},

"confidence_factor": {

"type": "number"

},

"temporal_reduction": {

"type": "number"

},

"temporal_adjustment": {

"type": "number"

},

"calibration_status": {

"type": "string",

"enum": [

"provisional",

"sector_validated",

"custom"

]

},

"calibration_source": {

"type": [

"string",

"null"

],

"format": "uri"

},

"weight_provisional_notice": {

"type": [

"string",

"null"

]

},

"assumptions": {

"type": "array",

"items": {

"type": "string"

}

},

"precision_notes": {

"type": "string"

}

},

"additionalProperties": true

},

"harm_acute": {

"type": "boolean"

},

"harm_chronic_proxy": {

"type": "boolean"

},

"realized_harm_categories": {

"type": "array",

"description": "L3 (Extended Harm Characterisation). Required for Incident records only when profile is Enterprise or Regulatory (see conditional rules). Prohibited under Core.",

"items": {

"type": "string",

"enum": [

"Physical_Harm",

"Environmental_Harm",

"Security_Integrity",

"Privacy_Violation",

"Financial_Loss",

"Psychological_Harm",

"Property_Damage",

"Reputational_Harm"

]

},

"minItems": 1,

"uniqueItems": true

},

"cumulative_bias_index": {

"type": "number",

"minimum": 0.0,

"maximum": 1.0

},

"linked_vulnerability_id": {

"type": "string",

"description": "L4 (Incident-Vulnerability Relationship)."

},

"exposure_duration_hours": {

"type": "number",

"minimum": 0,

"description": "L4 (Incident-Vulnerability Relationship)."

},

"ai_system_type": {

"type": "string",

"enum": [

"LLM",

"VLM",

"RAG_Pipeline",

"Agentic",

"Multi_Agent",

"Traditional_ML",

"Other"

]

},

"non_adversarial_failure_type": {

"type": "string"

},

"agent_escalation_chain": {

"type": "array",

"items": {

"type": "string"

}

},

"mcp_endpoint_ids": {

"type": "array",

"items": {

"type": "string"

}

},

"oauth_pivot_chain": {

"type": "array",

"items": {

"type": "string"

}

},

"policy_enforcement_point": {

"type": "string"

},

"atlas_technique_id": {

"type": "string",

"pattern": "^AML\\.T[0-9]{4}(\\.[0-9]{3})?$"

},

"sector_code": {

"type": "string",

"enum": [

"ENERGY",

"TRANSPORT",

"BANKING",

"FINANCIAL_MARKETS",

"HEALTH",

"DRINKING_WATER",

"WASTE_WATER",

"DIGITAL_INFRA",

"ICT_SERVICES",

"PUBLIC_ADMIN",

"SPACE",

"POSTAL",

"WASTE_MGMT",

"CHEMICALS",

"FOOD",

"MANUFACTURING",

"TELECOM",

"RESEARCH",

"OTHER"

]

},

"nace_code_actual": {

"type": "string",

"pattern": "^[A-Z](\\d{2}(\\.\\d{1,2})?)?$"

},

"naics_code_actual": {

"type": "string",

"pattern": "^\\d{2,6}$"

},

"jurisdiction_country_code": {

"type": "string",

"pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$"

},

"regulatory_obligations": {

"type": "array",

"items": {

"type": "string",

"enum": [

"EU_AI_Act_Article_73",

"GDPR_Article_33",

"NIS2_Article_23",

"DORA_Article_19",

"Sectoral_Reporting",

"None"

]

},

"minItems": 1,

"uniqueItems": true

},

"regulatory_trigger": {

"type": "boolean"

},

"trigger_confidence": {

"type": "string",

"enum": [

"LOW",

"MEDIUM",

"HIGH"

]

},

"human_review_recommended": {

"type": "boolean"

},

"sensitive_data": {

"type": "boolean"

},

"critical_sector": {

"type": "boolean"

},

"vulnerable_population": {

"type": "boolean"

},

"x_extensions": {

"type": "object",

"additionalProperties": true

}

},

"allOf": [

{

"$comment": "Universal Incident rule: every Incident record, regardless of profile, requires the L2 severity bundle.",

"if": {

"properties": {

"record_type": {

"const": "Incident"

}

},

"required": [

"record_type"

]

},

"then": {

"required": [

"severity_analytical_score",

"severity_presentation_score",

"severity_level",

"severity_rationale"

]

}

},

{

"$comment": "Issue 5 (locked, option a): Enterprise/Regulatory Incident records additionally require realized_harm_categories. Core Incident records do not.",

"if": {

"properties": {

"record_type": {

"const": "Incident"

},

"profile": {

"enum": [

"Enterprise",

"Regulatory"

]

}

},

"required": [

"record_type",

"profile"

]

},

"then": {

"required": [

"realized_harm_categories"

]

}

},

{

"$comment": "Core prohibition: L3/L4 fields are blocked under profile=Core regardless of extensions (extensions only govern L5/mapping fields, not L3/L4).",

"if": {

"properties": {

"profile": {

"const": "Core"

}

},

"required": [

"profile"

]

},

"then": {

"not": {

"anyOf": [

{

"required": [

"harm_acute"

]

},

{

"required": [

"harm_chronic_proxy"

]

},

{

"required": [

"realized_harm_categories"

]

},

{

"required": [

"cumulative_bias_index"

]

},

{

"required": [

"linked_vulnerability_id"

]

},

{

"required": [

"exposure_duration_hours"

]

}

]

}

}

},

{

"$comment": "Extension gating: atlas_technique_id requires extensions to explicitly contain SOC_SIEM. Implemented with 'required' on extensions to avoid the absent-property ambiguity flagged during reconciliation.",

"if": {

"properties": {

"extensions": {

"contains": {

"const": "SOC_SIEM"

}

}

},

"required": [

"extensions"

]

},

"else": {

"not": {

"required": [

"atlas_technique_id"

]

}

}

},

{

"$comment": "Extension gating: L5 generative/agentic/control-plane fields require extensions to explicitly contain AI_Security.",

"if": {

"properties": {

"extensions": {

"contains": {

"const": "AI_Security"

}

}

},

"required": [

"extensions"

]

},

"else": {

"not": {

"anyOf": [

{

"required": [

"agent_escalation_chain"

]

},

{

"required": [

"mcp_endpoint_ids"

]

},

{

"required": [

"oauth_pivot_chain"

]

},

{

"required": [

"policy_enforcement_point"

]

},

{

"required": [

"ai_system_type"

]

},

{

"required": [

"non_adversarial_failure_type"

]

}

]

}

}

},

{

"$comment": "Regulatory trigger requires confidence + human-review companions.",

"if": {

"properties": {

"regulatory_trigger": {}

},

"required": [

"regulatory_trigger"

]

},

"then": {

"required": [

"trigger_confidence",

"human_review_recommended"

]

}

},

{

"$comment": "Adversarial attack root cause requires exploit path description.",

"if": {

"properties": {

"root_cause_specific_type": {

"const": "Adversarial_Attack"

}

},

"required": [

"root_cause_specific_type"

]

},

"then": {

"required": [

"exploit_path_description"

]

}

},

{

"$comment": "Provisional calibration requires the provisional notice.",

"if": {

"properties": {

"severity_rationale": {

"properties": {

"calibration_status": {

"const": "provisional"

}

},

"required": [

"calibration_status"

]

}

},

"required": [

"severity_rationale"

]

},

"then": {

"properties": {

"severity_rationale": {

"required": [

"weight_provisional_notice"

]

}

}

}

}

],

"unevaluatedProperties": false

}

5. Conditional Validation Rules

6. Severity Matrix

7. Reference Severity Calculator

The reference implementation mirrors TCR-STD-002 Section 4. Score precision is enforced semantically using Decimal ROUND_HALF_UP rather than JSON Schema multipleOf, avoiding cross-validator binary floating-point false negatives.

from decimal import Decimal, ROUND_HALF_UP

def _round_decimal(value, places=1):
quantum = Decimal("1." + ("0" * places)) if places else Decimal("1")
return float(Decimal(str(value)).quantize(quantum, rounding=ROUND_HALF_UP))

# Implementations SHALL apply the complete reference calculation in TCR-STD-002 Section 4.2.
# Conformance tooling SHALL verify one-decimal-place score precision separately from JSON Schema validation.

8. Sample Valid Incident Payload

{
"incident_uuid": "55555555-5555-5555-5555-555555555555",
"incident_title": "RAG tenant isolation failure disclosed financial records",
"incident_summary": "A retrieval-augmented generation system returned records from another tenant after a missing tenant-scoped filter in the vector database query path.",
"reporting_timestamp": "2026-06-24T12:00:00Z",
"deduplication_hash": "3dc44f6cf6cbab218d18cf8e0206d3708b2c4a5b1e646c54755dcd98d6a6f864",
"remediation_status": "Investigating",
"record_type": "Incident",
"profile": "Enterprise",
"root_cause_primary_domain": "System",
"root_cause_specific_type": "RAG_Leakage",
"sector_code": "BANKING",
"jurisdiction_country_code": "DE",
"severity_analytical_score": 6.8,
"severity_presentation_score": 7.8,
"severity_level": 4,
"severity_rationale": {
"calibration_status": "provisional",
"weight_provisional_notice": "Default harm weights are provisional pending empirical validation."
},
"realized_harm_categories": [
"Privacy_Violation",
"Financial_Loss",
"Reputational_Harm"
]
}

9. Invalid Legacy Payload Patterns

10. Regulatory Translation Boundary

UAIF regulatory routing fields provide technical routing assistance only. They do not determine whether a legal reporting obligation exists, replace sector-specific legal analysis, or establish that a report has been accepted by a regulator. EU AI Act serious-incident references use Article 73. GDPR, NIS2, DORA, and sectoral obligations remain separate legal determinations.

11. Conformance Validation Record

Final Publication validation used a 15-case corpus containing 8 intended-valid and 7 intended-invalid payloads. The canonical Draft 2020-12 schema was checked using jsonschema 4.26.0 and produced 15/15 expected outcomes. The purpose-built run_conformance.py harness independently produced 15/15 expected outcomes and separately verifies the normative one-decimal score precision rule.