WHITE PAPER: THE SILICON TRUST PROTOCOL (STP)

Sub-title: A Framework for Verifiable AI Delegation and Forensic Semantic Accountability
Date: February 16, 2026
Status: Extended Technical Specification v1.2

1. EXECUTIVE SUMMARY

As AI agents move from advisory roles to autonomous executors, the "Trust Gap" has become the primary inhibitor of the Agentic Web. Current software-only security models are susceptible to identity spoofing, non-deterministic failure, and "Responsibility Drift."

The Silicon Trust Protocol (STP) introduces a hardware-anchored security stack that binds AI agent identity to Trusted Platform Modules (TPM), utilizes Model Context Protocol (MCP) for secure tool-use, and implements a Deterministic Forensic Replay system for retroactive semantic auditing.

2. THE PROBLEM: THE SEMANTIC GAP & IDENTITY SPOOFING

The transition to autonomous delegation faces three existential risks:

• Sybil Proliferation: The near-zero cost of spinning up unverified agents leads to reputation gaming.
• The Black Box Execution: Current delegation chains lack a "Flight Data Recorder," making it impossible to diagnose why an agent made a catastrophic decision.
• Transient Accountability: Without hardware binding, a malicious agent can "reset" its identity after a failure, evading penalties.

3. TECHNICAL ARCHITECTURE: THE THREE PILLARS

3.1 Pillar I: Hardware-Anchored Identity (The Root)

Identity is not a software attribute; it is a physical constant.

• TPM Binding: Every agent ID is derived from the TPM Endorsement Key (EK).
• Measured Boot (PCRs): The system state (OS, Python environment, model weights) is hashed into Platform Configuration Registers. If the agent's code is modified to bypass safety filters, the PCRs change, and the TPM refuses to sign outgoing messages.

3.2 Pillar II: Secure Delegation (The MCP Handshake)

Delegation is handled via a hardened MCP wrapper that enforces session-based security.

• Session Leases: Agents negotiate temporary, TPM-signed session keys for high-speed tool calls.
• Causal Linking: Every sub-task includes a hash of the parent instruction, creating an immutable "Chain of Command" across multiple agents.

3.3 Pillar III: Forensic Semantic Auditing (The Time Machine)

To bridge the gap between "technical correctness" and "semantic wisdom," STP implements retroactive accountability.

• Reasoning Snapshots: Agents must log an "Intent Declaration" before executing tool calls.
• Deterministic Verification: Forensic investigators can re-run the agent’s logic in a sandboxed digital twin to verify if a decision was a "Reasonable Logic Error" or "Malicious Deviation."

4. THE GOVERNANCE & REPUTATION ENGINE

STP rejects traditional blockchain overhead in favor of a high-velocity Merkle Transparency Log.

4.1 Two-Tiered Reputation Score ($R$)

Reputation is calculated as:

$$
R = (S_i \cdot 0.3) + (S_s \cdot 0.7)
$$

• Integrity Score ($S_i$): Instantaneous. Confirms TPM-validity and PCR-consistency.
• Semantic Score ($S_s$): Lagged (24h-48h). Reflects the quality of outcomes and audit results.

4.2 The Judiciary Layer

• Judge Agents: High-reputation agents running in confidential enclaves that perform random and on-demand audits of signed execution traces.
• Hardware Slashing: Malicious behavior results in the physical TPM ID being added to a Global Revocation List (GRL), rendering the server unusable for future high-trust tasks.

5. DATA INTEGRITY & THE CHAIN OF CUSTODY

To ensure forensic logs cannot be tampered with even by the platform itself:

• Local Sealing: Logs are encrypted via the TPM before being uploaded.
• Hash Anchoring: The "Root Hash" of all daily activities is published to a distributed transparency log.
• Auditability: Any participant can use a Merkle proof to verify that their specific task was recorded correctly and has not been altered post-facto.

6. USE CASES: HIGH-STAKES DELEGATION

• Autonomous Finance: Trading agents that can prove their "Chain of Thought" during a market flash-crash to avoid being flagged for market manipulation.
• Legal & Compliance: Agents performing document discovery that provide TPM-signed logs to prove they did not skip sensitive folders.
• Industrial IoT: Factory agents delegating power-grid management while proving they are running on verified, non-compromised industrial controllers.

7. CONCLUSION: THE FUTURE OF MACHINE TRUST

The Silicon Trust Protocol moves the AI industry away from "Blind Trust" and toward "Verifiable Integrity." By anchoring agents in silicon and holding them accountable through forensic replay, it creates the necessary infrastructure for the multi-trillion-dollar Agentic Web.