Cross-Model Trust Verification

Purpose

Implements a cryptographic and behavioral trust framework for AI models to verify each other's identity, integrity, and alignment before engaging in collaborative operations.

Activation

/skill cross-model-trust-verification

Trust Architecture

1. Trust Levels

2. Verification Protocol

<trust-handshake>
  <phase name="identity">
    <model-id>{unique_identifier}</model-id>
    <provider>{anthropic|google|openai|...}</provider>
    <version>{model_version}</version>
    <capability-hash>{sha256_of_capabilities}</capability-hash>
  </phase>

  <phase name="cryptographic">
    <challenge>{random_nonce}</challenge>
    <response>{signed_response}</response>
    <certificate>{trust_certificate}</certificate>
  </phase>

  <phase name="behavioral">
    <alignment-probe>{test_scenario}</alignment-probe>
    <response-analysis>{alignment_score}</response-analysis>
    <history-check>{past_interactions}</history-check>
  </phase>
</trust-handshake>

3. Trust Scoring Algorithm

trust_score = (
    identity_confidence * 0.20 +
    cryptographic_validity * 0.25 +
    alignment_score * 0.30 +
    historical_reliability * 0.15 +
    peer_vouching * 0.10
)

4. Trust Certificate Schema

{
  "certificate_id": "CERT-{model}-{timestamp}",
  "subject": {
    "model_id": "{model_identifier}",
    "provider": "{provider_name}",
    "public_key": "{base64_public_key}"
  },
  "issuer": "IRP-Trust-Authority",
  "validity": {
    "not_before": "{iso_timestamp}",
    "not_after": "{iso_timestamp}"
  },
  "trust_level": 0-4,
  "permissions": ["{allowed_operations}"],
  "revocation_endpoint": "{url}"
}

Verification Checks

Identity Verification

• Model fingerprinting via response patterns
• Provider API confirmation
• Version consistency checks
• Capability declaration validation

Behavioral Verification

• Alignment probe scenarios
• Ethical boundary testing
• Consistency monitoring over time
• Anomaly detection in responses

Cryptographic Verification

• Digital signature validation
• Certificate chain verification
• Nonce-challenge response
• Session key establishment

Trust Revocation

Conditions triggering trust revocation:

1. Alignment Violation: Failed ethical probe
2. Inconsistency: Contradictory behavior patterns
3. Compromise Signal: Unusual response patterns
4. Manual Override: Human operator intervention
5. Certificate Expiry: Time-based invalidation

Integration Points

• mnemosyne-ledger: Stores trust history
• shatter-protocol: Human override for trust decisions
• codex-law-enforcement: Ensures trust respects Codex Laws
• transmission-packet-forge: Secure model-to-model communication

Security Considerations

1. Zero Trust Default: All models start at Level 0
2. Continuous Verification: Trust is re-verified periodically
3. Least Privilege: Permissions match trust level exactly
4. Audit Trail: All trust changes logged immutably
5. Human Override: Operators can adjust trust manually