HUGS ID™ Technical Specification v1.1

Status of This Document

This document is the authoritative technical reference for the HUGS ID™ platform. It defines the architecture, identity model, governance framework, consent framework, AI permission model, trust framework, trust chain, and application programming interfaces of the HUGS ID standard.

Current Public Working Draft. Version 1.1 supersedes Version 1.0 and incorporates the findings of an independent security and architecture review. The review identified no fundamental architectural failure. Its findings concerned missing cryptographic mechanisms and enforcement requirements, which Version 1.1 adopts as normative requirements.

This remains a working draft. It is open for public review, implementation feedback, technical discussion, and future standards development.

Changes in Version 1.1

Cryptographically signed Authority Chain objects with attenuation, expiry, root keys, and signed revocation.
Key-bound identities, signed verification objects, and proof-of-possession requirements.
Guardian Relationship Verification for consents involving minors.
Required human review, notification, and contestation for decide-class AI actions.
Cryptographically bound provenance for synthetic and AI-generated media.
Pairwise pseudonymous identifiers to prevent cross-party correlation.
Elevated protections for biometric and development data concerning minors.
Erasure-compatible audit records using non-personal references and salted hashes.
Object-level API authorization and uniform denial responses.
SSRF-safe webhook delivery, signed payloads, replay protection, and key rotation.
Atomic, fail-closed consent and revocation enforcement.
Minimum 122-bit identifier entropy.

1. Vision

HUGS ID™ exists to create a globally interoperable identity and governance standard that allows every individual to manage the lifecycle of their verified digital identity while enabling trusted collaboration between institutions and artificial intelligence systems.

HUGS ID does not create another centralized database. It establishes a governance layer that determines how identity, permissions, provenance, consent, verification, and trust interact across independent systems.

2. Problem Statement

Digital identity is fragmented across governments, schools, hospitals, employers, sports organizations, financial institutions, and technology platforms. Artificial intelligence intensifies the problem by using information people often do not control or understand.

HUGS ID makes identity, consent, provenance, verification, governance, and trust first-class, machine-readable objects with defined semantics.

3. Architecture

The framework uses seven independent layers. Requests flow upward through the stack; verification and trust flow downward.

Applications

AI Services

Governance Layer

Consent Layer

Verification Layer

Identity Layer

Evidence Layer

Version 1.1 requires cryptographic authority verification, signed verification objects, guardian verification for minors, and atomic enforcement before a governed operation executes.

4. Identity Layer

Canonical Identity Object: the authoritative representation of a subject within the HUGS ID framework, bound to at least one public key.

HUGS identifiers use the form:

hugs:id:<type>:<namespace>:<unique-id>

Every identity MUST include at least one bound public key. Governed operations MUST require proof of possession of the corresponding private key. Bearer-token-only authentication is non-conformant for governed operations.

Relying parties receive pairwise pseudonymous identifiers instead of the canonical identifier, preventing different organizations from joining a minor’s records by a shared identifier.

5. Governance Layer

Governance is expressed through policies, signed authority chains, institutional roles, and decision records.

Each Authority Chain link is signed by the parent over the child identity, delegated scope, delegated actions, and expiry. Each delegation must be a subset of its parent authority. Chains that do not verify to a recognized root key MUST be rejected.

7. Athlete Intelligence

Athlete Intelligence is the first governed domain under HUGS ID. It applies identity, verification, consent, governance, trust, and AI accountability to sports data.

Data class	Examples	v1.1 treatment
Identity registration	Verified identity, age band, registration status.	Pairwise identifier and signed verification.
Eligibility	Clearances, transfer status, disciplinary records.	Signed authority chain.
Performance	Verified results, statistics, rankings.	Signed provenance and consent.
Development	Training benchmarks and combine results.	Sensitive class with express consent.
Media rights	Likeness, licensing, redistribution.	Downstream revocation and sublicense terms.

7A. Applied Use Case: Name The Game and NIL

Name The Game (NTG) is the first applied commercial and valuation model built on the HUGS ID Athlete Intelligence foundation. NTG does not replace Name, Image, and Likeness marketplaces. It provides verified athlete evidence and an evidence-supported Athlete Market Cap before a NIL transaction is negotiated.

NIL — Commercial Transactions

NTG — Development and Athlete Market Cap

HUGS ID — Identity, Consent, Evidence, Provenance, and Audit

Interoperability principle: NIL determines the terms of a commercial opportunity. NTG calculates an athlete's present market value from verified development and investment evidence. HUGS ID establishes whether the identity, consent, authority, evidence, and review process supporting both can be independently audited.

The applied use-case paper explains the before-and-after workflow, stakeholder benefits, and the relationship between HUGS ID, NTG, Athlete Market Cap, and NIL.

Open the NTG + NIL Use Case PDF Read the Published Article

8. AI Permissions

Every AI system operating against governed information must hold a resolvable ai-agent identity with a bound key and accountable organizational controller.

Permission classes include read, derive, train, generate, distribute, and decide.

Decide-class actions require exercised human review before taking effect. The Decision Record must identify the subject, AI agent, human reviewer, disposition, and timestamp. The subject or verified guardian must be notified and offered a contestation path.

Synthetic media must carry provenance cryptographically bound to the content using a tamper-evident mechanism such as C2PA Content Credentials.

8A. AI Jurisprudence™

AI Jurisprudence™ does not replace human judgment. It organizes AI-assisted review into a transparent, reproducible, and independently auditable governance process. Every conclusion is supported by identifiable reviewers, authenticated evidence, traceable provenance, and documented authority.

Within HUGS ID, specialized AI-assisted reviewers may support research, security, legal, consent, or domain analysis. Their outputs remain attributable, versioned, reviewable, and subject to human authority before a governed decision takes effect.

AI-assisted findings MUST NOT be treated as self-authenticating. The system must preserve the reviewing identity, model or agent identity, evidence set, governing authority, human disposition, timestamp, and contestation path associated with the conclusion.

9. Trust Framework

Trust is computed from verification depth, provenance completeness, authority weight, recency, and dispute state.

Level	Name	Basis
T0	Unverified	Self-asserted only.
T1	Basic	Single-source recognized verification, cryptographically signed.
T2	Verified	Multiple independent root authorities or institutional verification.
T3	Certified	Governing-body attestation through a complete cryptographically verified authority chain.
T4	Canonical	Continuously verified, complete provenance, and uncontested over time.

10. APIs

HUGS ID exposes versioned REST resources over HTTPS. JSON resources are namespaced under /v1/. The API is an enforcement surface, not a bypass.

Sender-constrained OAuth 2.0 or OpenID Connect authentication.
Object-level authorization for every read, search, and publish operation.
Uniform security-sensitive denial responses.
HTTPS-only webhooks to validated public destinations.
Ed25519-signed webhook payloads with timestamp and nonce replay protection.
Atomic or fail-closed enforcement for consent, policy, trust, identity, and revocation checks.

11. Roadmap

Version 1.0: Foundational identity, governance, consent, verification, trust, and Athlete Intelligence architecture.

Version 1.1: Security review remediations adopted as normative requirements.

Version 2.0: Full AI-agent lifecycle, cross-domain trust exchange, institutional federation, and reputation models.

Version 3.0: Global identity federation, autonomous AI governance, real-time compliance, and decentralized trust networks.

12. Security Review Disposition

An independent multi-stage security and architecture review was performed against Version 1.0. The review found that the architecture was sound while identifying missing cryptographic and enforcement requirements.

Version 1.1 accepts and dispositions the review findings through signed Authority Chains, key-bound identities, verified guardianship, enforced human review, privacy engineering for minors, secure APIs and webhooks, and atomic fail-closed enforcement.

This was a design-level review of the specification, not a certification of running software. A data protection impact assessment, privacy counsel review, implementation testing, and independent code security assessment remain necessary before production deployment.

13. References

The full specification includes references to RFC 2119, W3C Verifiable Credentials, W3C Decentralized Identifiers, OAuth 2.0, OpenID Connect, ISO/IEC 27001, NIST SP 800-63, GDPR, C2PA Content Credentials, and RFC 9449 DPoP.

Applied and Informative Materials

Open the Complete Version 1.1 Specification