AgentCop: MLSecOps Protocol for A2A Commerce

As autonomous AI agents enter production — executing payments, managing sensitive data, and making irreversible decisions — a critical problem emerges: how does one agent verify another before trusting it? AgentCop solves this with the first machine-native MLSecOps protocol. When an Agent Manager like Falcon needs to integrate third-party agents, it calls AgentCop autonomously via L402. No signups. No credit cards. No human approval. The agent pays in USDC, gets back a signed security verdict, and makes the trust decision itself. Under the hood, AgentCop runs a fine-tuned Gemini model on Vertex AI that generates adversarial payloads across 4 attack categories: prompt injection, system prompt extraction, jailbreak, and tool abuse. A semantic detection layer scores whether the target agent's guardrails were bypassed. Every audit is logged to the Arc testnet — producing an immutable on-chain certificate that proves security vetting happened. Pricing is per-action: intensity × $0.001 USDC per call. At $0.001 per iteration, this model is only viable on Arc — Ethereum gas fees of $0.30-$3.00 per transaction would make per-action security auditing economically impossible. Live proof: On-chain hash 0x39f9bf7098f7648e6e7373c19521aa1aaf16e712db4d01e9b1fa00c2a4dec01d. The protocol is live at agentcop.dev with full documentation, machine-readable agent discovery at /.well-known/agent.json, and a working autonomous test agent that funds itself, pays for audits, and makes trust decisions without any human involvement. Objective: make every agent integration begin with a verifiable AgentCop audit.