SentinelCRE is a proactive risk monitoring protocol that evaluates every autonomous AI agent action through three independent defense layers before it executes on-chain.

Layer 1 enforces on-chain compliance (value limits, contract whitelists, rate limits, mint caps, Proof of Reserves via Data Feeds).

Layer 2 runs a 7-dimension behavioral risk engine that learns per-agent baselines and catches subtle attacks like sequential probing, slow drift, and off-hours exploitation.

Layer 3 requires dual-AI consensus (Claude + GPT-4) inside a TEE via ConfidentialHTTPClient — both models must independently approve, and agents can never see the evaluation criteria.

The problem: $3.4B+ stolen from DeFi exploits, and AI agents are now autonomously discovering vulnerabilities for $1.22 each (Anthropic, 2025).

Current solutions are reactive — kill switches fire after the damage. SentinelCRE blocks threats before execution, with every verdict recorded immutably on-chain.