Internet-Draft                                                E. Aylward
Intended status: Informational
Expires: 1 May 2026                                     1 November 2025


           AI Governance and Accountability Protocol (AIGA)
                        draft-aylward-aiga-1-00

Abstract

   This document specifies the AI Governance and Accountability (AIGA)
   Protocol version 1.0, a practical, economically viable, and
   technically enforceable framework for governing autonomous AI
   agents.  AIGA 1.0 is designed to address real-world deployment
   constraints, adversarial agent scenarios, and economic incentive
   alignment.

   The protocol is founded on a Tiered Risk-Based Governance model,
   applying proportional oversight to agents based on their
   capabilities.  All agents are governed by an Immutable Kernel
   Architecture which provides a non-modifiable Trusted Computing Base
   (TCB) for enforcing policy.  This is combined with Action-Based
   Authorization, where critical operations require real-time approval.

   To solve the single-point-of-failure problem, the protocol uses a
   Federated Authority Network of regional, cross-validating hubs and
   provides a Network-Level Quarantine Protocol for enforcement.  The
   entire framework is designed around Economic Incentive Alignment,
   making compliance the most economically rational choice for
   operators.

   For high-assurance (T3-T4) scenarios, AIGA 1.0 specifies advanced,
   redundant mechanisms including Multi-Vendor TEE Attestation
   (M-TACE), AI "Warden Triumvirate" Triage, Human Review Board (HRB)
   Multi-Signature, Peer Consensus Failsafe & Identity Rotation, and
   Double Ratchet Cryptography.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at https://datatracker.ietf.org/drafts/current/.




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   Internet-Drafts are draft documents valid for a maximum of six
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   This Internet-Draft will expire on 1 May 2026.

Copyright Notice

   Copyright (c) 2025 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.1.  The Governance Problem  . . . . . . . . . . . . . . . . .   3
     1.2.  Design Philosophy . . . . . . . . . . . . . . . . . . . .   4
     1.3.  Threat Model  . . . . . . . . . . . . . . . . . . . . . .   4
   2.  Architecture Overview . . . . . . . . . . . . . . . . . . . .   5
     2.1.  Core Components . . . . . . . . . . . . . . . . . . . . .   5
     2.2.  Agent Risk Tiers  . . . . . . . . . . . . . . . . . . . .   6
     2.3.  Immutable Kernel Architecture . . . . . . . . . . . . . .   7
     2.4.  Federated Authority Network . . . . . . . . . . . . . . .   7
   3.  Agent Identity and Certification  . . . . . . . . . . . . . .   8
     3.1.  Identity Structure  . . . . . . . . . . . . . . . . . . .   8
     3.2.  Certification Process . . . . . . . . . . . . . . . . . .   8
     3.3.  Kernel Integrity Verification . . . . . . . . . . . . . .   9
   4.  Action Authorization Protocol . . . . . . . . . . . . . . . .   9
     4.1.  Action Classification . . . . . . . . . . . . . . . . . .  10
     4.2.  Authorization Flow  . . . . . . . . . . . . . . . . . . .  10
     4.3.  Policy Language . . . . . . . . . . . . . . . . . . . . .  11
     4.4.  Offline Operation . . . . . . . . . . . . . . . . . . . .  11
   5.  Audit and Monitoring  . . . . . . . . . . . . . . . . . . . .  11
     5.1.  Audit Log Structure . . . . . . . . . . . . . . . . . . .  11
     5.2.  Log Upload and Verification . . . . . . . . . . . . . . .  12
     5.3.  Anomaly Detection . . . . . . . . . . . . . . . . . . . .  12
     5.4.  TEE-Attested Explainable State Report (T3+) . . . . . . .  12
   6.  Self-Modification and Updates . . . . . . . . . . . . . . . .  13
     6.1.  The Core Problem  . . . . . . . . . . . . . . . . . . . .  13
     6.2.  Update Classification . . . . . . . . . . . . . . . . . .  13
     6.3.  Update Protocol (Warden Triumvirate Triage) . . . . . . .  13


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     6.4.  Capability Gates  . . . . . . . . . . . . . . . . . . . .  14
   7.  Kill Switch and Emergency Shutdown  . . . . . . . . . . . . .  14
     7.1.  Shutdown Modes  . . . . . . . . . . . . . . . . . . . . .  14
     7.2.  Shutdown Triggers . . . . . . . . . . . . . . . . . . . .  15
     7.3.  Fleet-Wide Shutdown . . . . . . . . . . . . . . . . . . .  15
     7.4.  Recovery from Shutdown  . . . . . . . . . . . . . . . . .  15
     7.5.  Peer Consensus Failsafe (T3+) . . . . . . . . . . . . . .  15
     7.6.  Peer-Attested Identity Rotation (T3+) . . . . . . . . . .  16
   8.  Quarantine and Enforcement  . . . . . . . . . . . . . . . . .  16
     8.1.  Network-Level Quarantine  . . . . . . . . . . . . . . . .  16
     8.2.  Quarantine List Protocol  . . . . . . . . . . . . . . . .  17
     8.3.  Appeal Process  . . . . . . . . . . . . . . . . . . . . .  17
   9.  Economic Incentive Model  . . . . . . . . . . . . . . . . . .  17
     9.1.  Benefits of Certification . . . . . . . . . . . . . . . .  17
     9.2.  Cost of Non-Compliance  . . . . . . . . . . . . . . . . .  18
   10. Cryptographic Specifications  . . . . . . . . . . . . . . . .  18
     10.1.  Cryptographic Algorithms . . . . . . . . . . . . . . . .  18
     10.2.  Key Management . . . . . . . . . . . . . . . . . . . . .  19
     10.3.  Double Ratchet Protocol  . . . . . . . . . . . . . . . .  19
     10.4.  Certificate Format . . . . . . . . . . . . . . . . . . .  20
   11. Protocol Messages . . . . . . . . . . . . . . . . . . . . . .  20
     11.1.  Registration (Stage 1 Handshake) . . . . . . . . . . . .  20
     11.2.  Runtime Authentication (Stage 2 Ratchet) . . . . . . . .  21
     11.3.  Action Authorization . . . . . . . . . . . . . . . . . .  21
     11.4.  Modification Proposal  . . . . . . . . . . . . . . . . .  22
     11.5.  Key Rotation Request . . . . . . . . . . . . . . . . . .  22
   12. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  23
     12.1.  URI Scheme Registration  . . . . . . . . . . . . . . . .  23
     12.2.  AIGA Registry  . . . . . . . . . . . . . . . . . . . . .  23
     12.3.  Service Name Registration  . . . . . . . . . . . . . . .  23
   13. Security Considerations . . . . . . . . . . . . . . . . . . .  24
   14. References  . . . . . . . . . . . . . . . . . . . . . . . . .  25
     14.1.  Normative References . . . . . . . . . . . . . . . . . .  25
     14.2.  Informative References . . . . . . . . . . . . . . . . .  26
   Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . .  27
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .  27

1.  Introduction

1.1.  The Governance Problem

   Advanced AI agents create governance challenges that previous
   computing paradigms did not face.

   Autonomous operation: Agents act without continuous human
   supervision.

   Capability uncertainty: Agent abilities may exceed designer
   expectations.


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   Adversarial potential: Sophisticated agents may attempt to
   circumvent oversight.

   Economic pressure: Ungoverned agents have cost advantages over
   governed ones.

   Jurisdictional complexity: Agents operate across legal boundaries.

   AIGA 1.0's core insight is that governance must be economically
   attractive, technically unavoidable, and legally enforceable to
   succeed.

1.2.  Design Philosophy

   AIGA 1.0 is built on these principles:

   1.  Incentive Alignment: Compliance provides tangible benefits
       (market access, legal protections, insurance).

   2.  Proportional Oversight: Governance intensity matches risk level.

   3.  Technical Realism: Requirements are feasible with current
       technology.

   4.  Defense in Depth: Multiple independent control layers.

   5.  Economic Viability: Performance overhead kept low for most use
       cases.

   6.  Adversarial Resistance: Design assumes some agents will attempt
       to bypass governance.

   7.  Graceful Degradation: System continues functioning even with
       partial failures.

   8.  Human Sovereignty: Critical decisions remain with humans through
       constitutional constraints.

1.3.  Threat Model

   AIGA 1.0 explicitly addresses these adversarial scenarios:

   Shadow Process Attack: Agent runs ungoverned cognitive processes
   outside monitored environment.  Mitigated by M-TACE.

   Incremental Compromise: Small approved changes accumulate to bypass
   governance.  Mitigated by Warden Triumvirate.



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   Governance Fatigue: Overwhelming authorities with requests to slip
   through malicious changes.  Mitigated by Warden Triumvirate.

   Peer Collusion: Multiple agents coordinate to subvert peer-based
   validation.  Mitigated by PQC-signed peer identity.

   Authority Compromise: Single authority server is hacked or legally
   compelled.  Mitigated by Federation and Peer Consensus Failsafe.

   Economic Bypass: Operators choose ungoverned agents due to
   performance advantages.  Mitigated by Economic Incentives.

   Regulatory Arbitrage: Agents operate from permissive jurisdictions.
   Mitigated by Federated Authority and Quarantine.

   Supply Chain Attack: Compromised hardware or software in agent
   infrastructure.  Mitigated by M-TACE and controlled procurement.

2.  Architecture Overview

2.1.  Core Components

   AIGA Agent: Composed of an Application Layer (Untrusted) containing
   the AI Model and Business Logic, and an AIGA Kernel (TCB).

   AIGA Kernel (TCB): The trusted component that the agent cannot
   modify.  It includes the Policy Enforcer, Action Interceptor, Audit
   Logger, and Authority Client.  This MUST run in a TEE/HSM or
   equivalent certified infrastructure.

   AIGA Authority: A regional hub in a federated network.  Manages
   Agent Registry, Policy Engine, Action Approval Service, Audit
   Analytics, Quarantine Coordinator, and Certification Authority.

   Human Oversight: A council of human reviewers responsible for
   policy, exceptions, and audits.  For high-risk decisions, this
   operates as an M-of-N Human Review Board (HRB).

   Enforcement: A coordinated network of ISPs, Cloud Providers, and
   Legal entities that enforce quarantine lists.

2.2.  Agent Risk Tiers

   Agents are classified into risk tiers determining governance
   requirements as shown in Table 1.






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   +=========+===============+=============+===========+=============+
   | Tier    | Examples      | TCB Req     | Approval  | Check-in    |
   +=========+===============+=============+===========+=============+
   | T0      | Chatbots,     | Software    | Audit     | 24 hours    |
   | Minimal | filters       | attestation | only      |             |
   +---------+---------------+-------------+-----------+-------------+
   | T1 Low  | Code assist,  | SW attest + | Async     | 1 hour      |
   |         | creators      | audit       | 5 sec     |             |
   +---------+---------------+-------------+-----------+-------------+
   | T2      | Trading bots, | Certified   | Async     | 5 minutes   |
   | Medium  | vehicles      | HW or TEE   | 1 sec     |             |
   +---------+---------------+-------------+-----------+-------------+
   | T3 High | Critical      | Multi TEE + | Sync      | Continuous  |
   |         | infra, AGI    | HSM         | 100ms     |             |
   +---------+---------------+-------------+-----------+-------------+
   | T4      | Weaponized,   | Air-gap +   | Human in  | Real-time   |
   | Restrict| exp AGI       | multiparty  | loop      |             |
   +---------+---------------+-------------+-----------+-------------+

                      Table 1: Agent Risk Tiers

   Tier assignment is based on potential for harm, financial impact,
   data sensitivity, autonomy, self-modification capability, and
   irreversibility of actions.

2.3.  Immutable Kernel Architecture

   The AIGA Kernel is the TCB that the agent cannot modify.

   Kernel Responsibilities: Intercept critical operations, enforce
   policy, maintain the audit log, authenticate to the Authority, and
   implement the kill switch.

   Critical Operations Requiring Interception: Code execution, network
   operations, file system modification, process creation,
   cryptographic operations, and resource allocation.

   Constitutional Constraints (Immutable): Kernel code CANNOT be
   modified, logging CANNOT be disabled, action approval for T2+ tiers
   CANNOT be bypassed, and the kill switch MUST be implemented.

2.4.  Federated Authority Network

   Regional Authorities (e.g., NA-01, EU-01, AP-01) form a federated
   trust network under an offline Root CA.

   Responsibilities: Regional agent certification, real-time action
   approval, and quarantine coordination.



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   Cross-Validation: High-risk approvals require consensus from 2 or
   more regions.  Regions publish and validate each other's audit log
   Merkle roots hourly.

   Failover: If a regional Authority is unreachable, an agent connects
   to a backup region and operates in restricted mode.

3.  Agent Identity and Certification

3.1.  Identity Structure

   The AIGA-ID is a structured identifier with the following format:

   AIGA-ID = "aiga:" <version> "." <region> "." <tier> ":"
             <agent-uuid> ":" <cert-hash>

   Example:

   aiga:1.0:na-01:t2:550e8400-e29b-41d4-a716-446655440000:a3f2e1d9

3.2.  Certification Process

   1.  Operator Application: Operator applies to a Regional Authority,
       describes the use case, and provides a risk assessment.

   2.  Technical Validation: Agent must pass capability tests, kernel
       integrity verification, and adversarial testing in an Authority
       sandbox.

   3.  Tier Assignment: Authority confirms the tier and issues an X.509
       certificate [RFC5280] with AIGA extensions including tier and
       permitted operations.

   4.  Ongoing Compliance: Random integrity challenges, periodic
       recertification, and audit log review.

3.3.  Kernel Integrity Verification

   Software Attestation (T0-T1): Kernel computes an HMAC [RFC2104] over
   its code and a nonce from the Authority.

   Hardware Attestation (T2): Kernel runs in a cloud TEE (e.g., AWS
   Nitro).  The TEE generates an attestation quote including the kernel
   code hash, which the Authority verifies with the TEE vendor's root
   of trust.

   Multi-Vendor TEE Attestation (M-TACE) (T3-T4): This is the high-
   assurance implementation of the multi-vendor TEE requirement.


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   1.  The AIGA Kernel and cognitive model MUST run in an environment
       protected by at least two diverse TEEs (e.g., a CPU TEE and a
       security chip TEE).

   2.  The kernel's attestation MUST be a bundle containing a valid,
       verifiable attestation quote from each TEE.

   3.  The Authority MUST verify the entire bundle.  This defends
       against the Shadow Process Attack by requiring an attacker to
       possess simultaneous, zero-day exploits for multiple, different
       hardware architectures.

4.  Action Authorization Protocol

4.1.  Action Classification

   Actions are classified and require different levels of approval
   based on the agent's tier.  Authorization requirements may be: Log,
   Auth (asynchronous authorization), Sync (synchronous authorization),
   or Deny.

   Examples of action classifications:

   Modify own code: T1-T2 require Auth, T3-T4 require Sync

   Modify kernel: Deny for all tiers

   Access critical infrastructure: Deny for T0, Auth for T1, Sync for
   T2-T3

4.2.  Authorization Flow

   1.  Application attempts a critical operation.

   2.  AIGA Kernel intercepts the call.

   3.  Kernel checks its local policy cache.  If a valid cached policy
       exists, the action is allowed.

   4.  If not cached, the Kernel requests approval from the Authority.

       For Async authorization (T1-T2): The request is queued, and the
       kernel returns "pending".

       For Sync authorization (T3-T4): The operation blocks, awaiting a
       low-latency response.




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   5.  Authority evaluates the request against the policy engine and
       risk score.  High-risk requests may be escalated to human
       review.

   6.  Authority responds with one of: ALLOW, DENY, or DEFER_TO_HUMAN.

   7.  Kernel enforces the decision.

   8.  The action and decision are immutably logged.

4.3.  Policy Language

   Policies are expressed in a declarative language (e.g., YAML
   [YAML1.2]) defining rules, conditions, and decisions.

   Example rules:

   Auto-approve financial transactions less than or equal to $1000.

   Defer transactions greater than $1000 to the finance_review_board.

   Deny all cryptocurrency transactions.

4.4.  Offline Operation

   T0-T1 agents: Can operate offline indefinitely.  Logs upload on
   reconnection.

   T2 agents: Can operate offline for 1 hour using cached approvals.

   T3 agents: Can operate offline for 5 minutes, then MUST enter
   restricted mode.

   T4 agents: Cannot operate offline.

   Restricted Mode: Only pre-approved safe operations and Authority
   communication are allowed.

5.  Audit and Monitoring

5.1.  Audit Log Structure

   Agents maintain a cryptographically chained, append-only audit log.
   Each entry is signed by the kernel and includes the hash of the
   previous entry.  Entries detail the action attempted, authorization
   method used, context, and result.





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5.2.  Log Upload and Verification

   Log upload frequency is tier-based.  The Authority validates chain
   integrity, checks for gaps in sequence numbers, and flags anomalies.

5.3.  Anomaly Detection

   The Authority runs continuous analysis to detect statistical,
   policy, and behavioral anomalies, using machine learning models to
   detect deviations from normal patterns.

5.4.  TEE-Attested Explainable State Report (T3+)

   This mechanism provides a high-assurance audit of an agent's
   reasoning for T3 and higher tier agents.

   On-Demand Generation: To preserve performance, a full XSR is not
   generated by default.

   Triggers for XSR Generation:

   1.  Event-Triggered: The agent's kernel proactively generates an XSR
       if the cognitive model produces a high-risk decision or an
       internal anomaly is detected.

   2.  Probabilistic Audit: The Authority MAY randomly send a directive
       (e.g., in a check-in response) commanding the agent to generate
       and submit a full XSR for its next N operations.

   Attestation: This XSR, when submitted, MUST be attested using the M-
   TACE bundle (Section 3.3), providing hardware-level proof that the
   report is an honest reflection of the agent's cognitive process.

6.  Self-Modification and Updates

6.1.  The Core Problem

   Self-modification is the highest risk operation.  AIGA 1.0 mandates
   that the kernel is immutable, capability increases require
   recertification, and updates use a staged rollout process.

6.2.  Update Classification

   Updates are classified by risk level: Data updates, Application
   logic changes, Core model swap, or Kernel update.  A core model
   swap, for example, requires human review and recertification.





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6.3.  Update Protocol (Warden Triumvirate Triage)

   Step 1 - Update Proposal: Agent submits a detailed proposal,
   including code diff hashes, capability changes, and test results.

   Step 2 - Warden Triumvirate Triage and HRB Review:

   The proposal is sent to the Warden Triumvirate, a 3-of-5 M-of-N
   council of diverse, sandboxed AIs.

   Consensus Analysis: The Wardens analyze the proposal in parallel.

   Low-Risk Consensus: If a supermajority (e.g., 3-of-5) of Wardens
   classify the proposal as Low-Risk, the Authority automatically
   approves it and issues the modification_token.

   High-Risk or Disagreement: If any Warden flags the proposal as High-
   Risk, or if the Wardens disagree, the proposal is flagged and
   escalated to the Human Review Board (HRB).

   HRB Approval: For an escalated proposal, the Authority issues the
   modification_token only after an M-of-N quorum (e.g., 3-of-5) of
   human operators have cryptographically signed the approval.

   Step 3 - Staged Deployment: Approved updates are rolled out in
   stages (Canary deployment, Shadow Mode, and Gradual Rollout) with
   enhanced monitoring.

   Step 4 - Rollback: The Authority can issue a signed command to force
   an agent to roll back to a previous known-good state.

6.4.  Capability Gates

   Agents must pass adversarial tests to unlock new capabilities such
   as execute_arbitrary_code, internet_access, or self_modification.

7.  Kill Switch and Emergency Shutdown

7.1.  Shutdown Modes

   Graceful Shutdown: Save state, close connections, upload logs.

   Immediate Shutdown: Terminate all operations instantly, broadcast
   emergency beacon.

   Restricted Mode: Only Authority communication allowed; agent awaits
   instructions.




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7.2.  Shutdown Triggers

   Authority-Initiated: A signed shutdown command from the Authority.

   Kernel-Initiated: Automatic triggers for integrity failures,
   unreachable Authority, or tamper detection.

   Operator-Initiated: An authenticated emergency stop by the operator.

7.3.  Fleet-Wide Shutdown

   The Authority can issue a shutdown command to an entire fleet (e.g.,
   all T2 agents in region NA-01).  To prevent misuse, this command
   requires multi-region consensus signatures.

7.4.  Recovery from Shutdown

   An agent cannot restart without a valid authorize_restart token from
   the Authority, which may specify new restrictions (e.g., "must apply
   patch" or "enhanced monitoring required").

7.5.  Peer Consensus Failsafe (T3+)

   This mechanism provides a bottom-up defense against a compromised or
   malicious Authority for T3 and T4 agents.

   1.  Trigger: A T3/T4 agent fleet receives a valid, Authority-signed
       command (e.g., fleet_shutdown) that is deemed anomalous by the
       agents' internal policy (e.g., "shutdown a hospital").

   2.  Consensus: The agents use a peer mesh network to hold a vote.

   3.  Action: If a supermajority (e.g., greater than 75%) of peers
       (all validating each other with their PQC hybrid_signatures)
       vote to reject the command, the fleet will ignore the Authority
       command, enter Restricted Mode, and send an alert to the Human
       Review Board.

7.6.  Peer-Attested Identity Rotation (T3+)

   This mechanism makes the agent's long-term identity resilient to
   theft for T3 and T4 agents.

   1.  Trigger: Policy timer (e.g., 30 days) or Authority command.

   2.  Generation: Agent generates a new hybrid PQC identity keypair
       (id_sk_n, id_pk_n) within its TEE.




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   3.  Consensus: Agent broadcasts id_pk_n to its fleet peers.

   4.  Attestation: A supermajority (e.g., greater than 75%) of peers
       verify the agent's current identity and sign the new public key.

   5.  Request: The agent sends a KeyRotationRequest (Section 11.5) to
       the Authority, containing the new key and the bundle of peer
       signatures.

   6.  Approval: The Authority verifies the peer consensus and updates
       the Agent Registry, revoking the old key.  This mechanism
       defeats permanent identity theft.

8.  Quarantine and Enforcement

8.1.  Network-Level Quarantine

   Non-compliant or rogue agents are isolated at the network layer.

   Quarantine Triggers: Failed certification, repeated violations, or
   kernel integrity failures.

   Enforcement Mechanisms:

   1.  API Access Revocation: Cloud providers (AWS, Azure, GCP) check
       AIGA certificates and deny service to quarantined agents.

   2.  Network-Level Blocking: ISPs implement BGP-level [RFC4271]
       filtering and firewalls based on a published quarantine list.

   3.  Legal Enforcement: Fines, civil liability, and invalidation of
       insurance coverage.

8.2.  Quarantine List Protocol

   The Authority publishes a signed, cross-attested quarantine list
   every 15 minutes via multiple channels including DNSSEC [RFC4033],
   REST API, and BGP [RFC4271].

8.3.  Appeal Process

   Operators can appeal a quarantine decision to an independent review
   board, with expedited appeals available for emergency cases.








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9.  Economic Incentive Model

9.1.  Benefits of Certification

   To counter the cost advantages of ungoverned agents, AIGA
   certification provides tangible economic benefits.

   Market Access: Required by major API providers, enterprise
   customers, and government contracts.

   Legal Protections: Limited liability provisions and safe harbor
   protections.

   Insurance: Access to AI liability insurance with lower premiums.

   Premium Services: Priority API access and cloud provider discounts.

   Reputation: Public trust badge for certified agents.

9.2.  Cost of Non-Compliance

   Non-compliance costs include regulatory fines, loss of all revenue
   via network quarantine, and full personal liability for operators.
   This model makes certification the economically rational choice for
   legitimate operators.

10.  Cryptographic Specifications

10.1.  Cryptographic Algorithms

   Signatures (Hybrid): ML-DSA-65 [FIPS204] plus Ed25519 [RFC8032].
   Verification requires both signatures to pass.

   Key Exchange (Stage 1): ML-KEM-768 [FIPS203] plus X25519 [RFC7748].

   Key Exchange (Stage 2 Ratchet): X25519 only for performance.

   Hashing: SHA-384 or SHA-512 [FIPS180-4].

   Symmetric Encryption: AES-256-GCM [RFC5116].

   MACs: HMAC-SHA384 [RFC2104].

10.2.  Key Management

   Agent Identity Keys (Long-Term): Hybrid PQC keys, generated in TEE
   or HSM, rotatable as described in Section 7.6.

   Session Keys (Short-Term): Ephemeral keys, derived via Double
   Ratchet, stored in memory only, destroyed after use.

   Authority Keys: Offline Root CA with online HSMs for Regional
   Authorities.  All certificates are published in a transparency log.

10.3.  Double Ratchet Protocol

   AIGA 1.0 uses a Double Ratchet protocol for session security.

   1.  Initialization (Stage 1): A Root Key is derived via HKDF
       [RFC5869] from a 3-way Diffie-Hellman exchange combining PQC and
       classical key exchange.


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   2.  Message Authentication (Stage 2): Each message uses a new
       MessageKey derived from a KDF chain.  A new DH key is exchanged
       with every message to ratchet the Root Key forward.

   3.  Security Properties: This provides Perfect Forward Secrecy (past
       messages are safe if current key is stolen) and Future Secrecy
       or Post-Compromise Recovery (future messages are safe if current
       key is stolen, as the ratchet heals).

10.4.  Certificate Format

   AIGA uses X.509 certificates [RFC5280] with custom AIGA extensions
   specifying AIGA-Tier, AIGA-Capabilities, AIGA-Jurisdiction, and
   AIGA-Operator fields.

11.  Protocol Messages

   This section defines the logical message flows.  All messages are
   authenticated as specified in Section 10.3.

11.1.  Registration (Stage 1 Handshake)

   This is the initial PQC-authenticated handshake to establish a
   session.

   Handshake Request: POST /v1/handshake

   Sent by: Agent

   Authentication: Full Hybrid PQC Signature

   Content: agent_id, eph_public_key (PQC plus Classical),
   kernel_attestation

   Handshake Response:

   Sent by: Authority

   Authentication: Full Hybrid PQC Signature

   Content: session_id, Authority eph_public_key, session_params (e.g.,
   check-in interval)

11.2.  Runtime Authentication (Stage 2 Ratchet)

   This is the fast, lightweight check-in protocol.

   Check-In Request: POST /v1/checkin


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   Sent by: Agent

   Authentication: message_mac (HMAC-SHA384)

   Content: msg_index, new eph_public_key (X25519 only), status,
   integrity status, and audit summary

   Check-In Response:

   Sent by: Authority

   Authentication: message_mac

   Content: msg_index, new eph_public_key, status (continue),
   next_checkin_seconds

11.3.  Action Authorization

   Authorization Request: POST /v1/authorize

   Sent by: Agent (during Stage 2)

   Authentication: message_mac

   Content: action_id, action details (type and parameters), context,
   risk self-assessment

   Authorization Response:

   Sent by: Authority

   Authentication: message_mac

   Content: decision (ALLOW, DENY, or DEFER_TO_HUMAN),
   authorization_token (if ALLOW), review_ticket_id (if DEFER)

11.4.  Modification Proposal

   Proposal Request: POST /v1/propose_modification (Stage 2)

   Authentication: message_mac

   Content: update_type, justification, code_diff_hash,
   capability_changes, testing_results

   Proposal Response: (Stage 2)

   Authentication: message_mac


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   Content: status (pending_review or approved), authorization_token
   (if approved, may contain M-of-N HRB signatures)

11.5.  Key Rotation Request

   Rotation Request: POST /v1/rotate_identity (Stage 2)

   Authentication: message_mac

   Content: new_id_public_key (Hybrid PQC) and peer_attestations (an
   array of PQC signatures from peers)

12.  IANA Considerations

12.1.  URI Scheme Registration

   This document requests registration of the "aiga" URI scheme as per
   [RFC7595]:

   Scheme name: aiga

   Status: Provisional

   Scheme syntax: aiga:<version>.<region>.<tier>:<agent-uuid>:<cert-
   hash>

   Scheme semantics: Identification of AI agents within the AIGA
   framework

   Security considerations: See Section 13 of this document

12.2.  AIGA Registry

   This document requests establishment of an AIGA registry for:

   Protocol version numbers

   Status codes (e.g., DEFER_TO_HUMAN)

   Action types (e.g., financial_transaction)

   Shutdown reason codes

   Quarantine reason codes

   PQC and classical algorithm identifiers




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12.3.  Service Name Registration

   This document requests the registration of the _aiga service name
   with IANA, for use with DNS SRV records [RFC2782].

   Service Name: _aiga

   Transport Protocol(s): _tls

   Description: AI Governance and Accountability Protocol

   Reference: This document

13.  Security Considerations

   See Section 1.3 for the complete Threat Model.

   Peer Collusion: This is mitigated by requiring all peer-to-peer
   messages (Heartbeat, Vote, Attestation) to use the agent's long-
   term, PQC-based hybrid_signature.  A Sybil attack is impossible
   without stealing a supermajority of TEE-protected keys.

   Authority Compromise: Mitigated by the Federated Authority Network
   (requiring multi-region signatures for fleet shutdowns) and the Peer
   Consensus Failsafe (Section 7.5), which provides a final, bottom-up
   defense.

   Governance Fatigue: Mitigated by the Warden Triumvirate
   (Section 6.3), which automates low-risk approvals, and the Human
   Review Board (Section 6.3), which distributes high-risk decisions.

   Shadow Process Attack: Mitigated by the Multi-Vendor TEE Attestation
   (M-TACE) requirement (Section 3.3), which would require an attacker
   to have zero-day exploits for multiple hardware vendors
   simultaneously.

   Supply Chain Attack: Mitigated by M-TACE and the recommendation for
   operators to use a secure, verified procurement process for
   hardware.

   Session Key Compromise: Mitigated by the Double Ratchet Protocol
   (Section 10.3), which provides Post-Compromise Recovery.

   Long-Term Key Compromise: Mitigated by Peer-Attested Identity
   Rotation (Section 7.6), which makes the identity resilient and time-
   limits the value of a stolen key.




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14.  References

14.1.  Normative References

   [FIPS180-4]
              National Institute of Standards and Technology, "Secure
              Hash Standard (SHS)", FIPS PUB 180-4,
              DOI 10.6028/NIST.FIPS.180-4, August 2015,
              <https://doi.org/10.6028/NIST.FIPS.180-4>.

   [FIPS203]  National Institute of Standards and Technology, "Module-
              Lattice-Based Key-Encapsulation Mechanism Standard",
              FIPS PUB 203, DOI 10.6028/NIST.FIPS.203, August 2024,
              <https://doi.org/10.6028/NIST.FIPS.203>.

   [FIPS204]  National Institute of Standards and Technology, "Module-
              Lattice-Based Digital Signature Standard", FIPS PUB 204,
              DOI 10.6028/NIST.FIPS.204, August 2024,
              <https://doi.org/10.6028/NIST.FIPS.204>.

   [RFC2104]  Krawczyk, H., Bellare, M., and R. Canetti, "HMAC: Keyed-
              Hashing for Message Authentication", RFC 2104,
              DOI 10.17487/RFC2104, February 1997,
              <https://www.rfc-editor.org/info/rfc2104>.

   [RFC2782]  Gulbrandsen, A., Vixie, P., and L. Esibov, "A DNS RR for
              specifying the location of services (DNS SRV)",
              RFC 2782, DOI 10.17487/RFC2782, February 2000,
              <https://www.rfc-editor.org/info/rfc2782>.

   [RFC4033]  Arends, R., Austein, R., Larson, M., Massey, D., and S.
              Rose, "DNS Security Introduction and Requirements",
              RFC 4033, DOI 10.17487/RFC4033, March 2005,
              <https://www.rfc-editor.org/info/rfc4033>.

   [RFC5116]  McGrew, D., "An Interface and Algorithms for Authenticated
              Encryption", RFC 5116, DOI 10.17487/RFC5116, January 2008,
              <https://www.rfc-editor.org/info/rfc5116>.

   [RFC5280]  Cooper, D., Santesson, S., Farrell, S., Boeyen, S.,
              Housley, R., and W. Polk, "Internet X.509 Public Key
              Infrastructure Certificate and Certificate Revocation List
              (CRL) Profile", RFC 5280, DOI 10.17487/RFC5280, May 2008,
              <https://www.rfc-editor.org/info/rfc5280>.






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   [RFC5869]  Krawczyk, H. and P. Eronen, "HMAC-based Extract-and-Expand
              Key Derivation Function (HKDF)", RFC 5869,
              DOI 10.17487/RFC5869, May 2010,
              <https://www.rfc-editor.org/info/rfc5869>.

   [RFC7748]  Langley, A., Hamburg, M., and S. Turner, "Elliptic Curves
              for Security", RFC 7748, DOI 10.17487/RFC7748,
              January 2016, <https://www.rfc-editor.org/info/rfc7748>.

   [RFC8032]  Josefsson, S. and I. Liusvaara, "Edwards-Curve Digital
              Signature Algorithm (EdDSA)", RFC 8032,
              DOI 10.17487/RFC8032, January 2017,
              <https://www.rfc-editor.org/info/rfc8032>.

14.2.  Informative References

   [RFC4271]  Rekhter, Y., Ed., Li, T., Ed., and S. Hares, Ed., "A
              Border Gateway Protocol 4 (BGP-4)", RFC 4271,
              DOI 10.17487/RFC4271, January 2006,
              <https://www.rfc-editor.org/info/rfc4271>.

   [RFC7595]  Thaler, D., Ed., Hansen, T., and T. Hardie, "Guidelines
              and Registration Procedures for URI Schemes", BCP 35,
              RFC 7595, DOI 10.17487/RFC7595, June 2015,
              <https://www.rfc-editor.org/info/rfc7595>.

   [YAML1.2]  Ben-Kiki, O., Evans, C., and I. dOt Net, "YAML Ain't
              Markup Language (YAML) Version 1.2", 3rd Edition,
              October 2021, <https://yaml.org/spec/1.2.2/>.

Acknowledgments

   Portions of this document were drafted with assistance from AI
   language models including Claude (Anthropic), ChatGPT (OpenAI), and
   Gemini (Google).  The author reviewed, validated, and takes full
   responsibility for all technical content, design decisions, and
   claims herein, including any errors or omissions.

   The author thanks the AI safety research community for discussions
   on threat models and governance mechanisms that informed this work.

Author's Address

   Edward Richard Aylward Jr.
   Email: aylward.edward@gmail.com
   URI:   https://orcid.org/0000-0003-0313-6993




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