CEL is a next-generation security infrastructure designed to transform blockchain security from periodic audits into a continuous, autonomous, and strategic execution layer. By leveraging cybersecurity-specialized AI agents, CEL protects smart contracts and on-chain capital at machine speed.
The core idea is simple:
If AI can exploit smart contracts autonomously, only AI can defend them at the same velocity.
Recent research by Anthropic demonstrates that AI agents have crossed a critical threshold in offensive blockchain security.
🔗 Reference: AI agents find $4.6M in blockchain smart contract exploits
Key findings:
- $4.6M Identified Value: Frontier models discovered exploitable vulnerabilities worth $4.6M in contracts deployed after their training cutoffs.
- Zero‑Day Reality: Agents uncovered novel zero-day vulnerabilities across 2,849 recently deployed contracts.
- Autonomous Feasibility: Fully autonomous, profit-seeking exploit discovery is technically viable today.
- Velocity Problem: AI-driven exploit revenue is doubling every ~1.3 months, collapsing the time window between deployment and exploitation.
Conclusion:
Reactive security and one-time audits are structurally incapable of keeping up.
Most security vendors sell assessments — static, point-in-time reports.
CAI (Cybersecurity AI) builds security itself:
- In-house
- Continuous
- Executable
This project draws heavily from the Cybersecurity Superintelligence paradigm:
🔗 Paper: A new chapter in AI security is about to begin
Using CAI PRO and the alias2 model family, this approach introduces a fundamentally different security posture:
- Superhuman Speed: AI agents execute specific security tasks up to 3,600× faster than human experts.
- Economic Efficiency: Operational costs reduced by 156× compared to human-driven processes.
- Strategic Capability: alias2 solves 76% of complex cybersecurity challenges, outperforming GPT‑5 (~33%).
- Game‑Theoretic Reasoning: Via G‑CTR (Generative Cut‑the‑Rope), agents compute Nash‑equilibrium attack/defense strategies, doubling success rates and reducing behavioral variance by 5.2×.
Most security tools observe risk. CAI PRO agents play the game.
This repository represents the synthesis of:
- Anthropic’s economic exploit research (AI as an attacker)
- CAI PRO / alias2 architecture (AI as a strategic defender)
CEL is a non-stop, autonomous security execution pipeline.
While Anthropic showed that a single AI audit run costs ~$1.22 per contract, CEL applies CAI’s multi-agent orchestration to make 24/7 monitoring economically viable:
- Token Cost Reduction: ~98% efficiency gain
- ~$5,940 → ~$119 per billion tokens
- Always-On Defense: Continuous scanning, simulation, and strategic response
- Execution, Not Reporting: Findings are directly actionable by machines
CEL turns smart contract security from a workflow into an infrastructure layer.
The FAR Dashboard exposes real-time systemic risk across blockchain networks.
Core capabilities:
- Network Switching: Multi-chain visibility (Ethereum, BNB, etc.)
- Funds at Risk (FAR): Dollar-value quantification of currently exploitable capital
- Block-Level Precision: Exact block numbers where vulnerabilities emerge
- Real-Time Quanting: Vulnerabilities priced directly in native tokens (ETH / BNB) using SCONE-bench methodologies
- Attack Graphs: G‑CTR-powered visualization of attack paths and defensive allocations
This converts abstract vulnerabilities into economic and strategic signals.
CEL is built around a deliberate role inversion:
- AI → Strategic actor & executor
- Human → Supervisor & meta‑strategist
Humans define goals, constraints, and trust boundaries. AI handles:
- Scale
- Speed
- Continuous adversarial reasoning
AI is no longer optional — it is becoming essential for the survival of DeFi.
CEL is not another security product.
It is an attempt to define:
- What continuous security looks like in Web3
- How AI-native defense competes with AI-native attackers
- How capital protection becomes a real-time systems problem, not a compliance task
Developed by Michael Shapkin
Inspired by the work of Winnie Xiao, Cole Killian, and the Alias Robotics research team.