Werracle: Sub-Cent Intra-Block AI Reflex Oracles and Flash-Loan Circuit Breakers for EVM Smart Contracts
Official Open Science Replication Package & Engineering BlueprintCompanion Research to WERR Framework (Zenodo: 10.5281/zenodo.22939253 • arXiv:2609.25498)Patent Application: TÜRKPATENT TR 2026/016285 (Procedural State & On-Chain Decision Synthesis) Executive Summary & Breakthrough Overview Contemporary on-chain artificial intelligence (AI) encounters an intractable Von Neumann memory and latency wall. Storing static floating-point neural weight matrices inside Ethereum Virtual Machine (EVM) storage costs millions of gas, rendering direct on-chain inference impossible. While Zero-Knowledge Machine Learning (ZK-ML) offloads matrix tensor multiplications to off-chain provers, it introduces fatal constraints: 10 to 300 seconds of SNARK proving latency and 250,000 to 500,000 gas per proof verification. Because decentralized finance (DeFi) exploits—such as uncollateralized flash-loan attacks, predatory sandwich MEV, and toxic loss-versus-rebalancing (LVR) flow—occur atomically inside a single block, ZK-ML oracles cannot react in time. Werracle completely resolves this paradigm by delivering the first production-grade, zero-storage AI decision oracle capable of sub-millisecond, intra-block reflexive execution inside standard EVM smart contracts: 0 Bytes Persistent Tensor Weights: Instead of multi-gigabyte weight arrays, non-linear decision hyperplanes are procedurally synthesized on-the-fly from a 24-byte Mandelbrot coordinate triplet Θ = (cx, cy, zoom). Single 32-Byte Storage Slot (bytes32): The entire machine-learning model, operational thresholds, update nonces, and security flags pack into one EVM word. Warm SLOAD costs exactly 100 gas. Sub-Cent Micro-Gas Footprint: Using pure fixed-point Q16.16 arithmetic (WerrMath.sol), evaluating a 16-point Pareto micro-grid takes only ~21,438 gas (< $0.0005 on Base and Arbitrum). Uniswap v4 Dynamic Fee Governor (WerracleFeeHook.sol): Measures real-time orderbook turbulence and dynamically scales LP swap fees between 0.05% and 0.50% atomically inside the swap transaction to mitigate LVR. 1,000-Test Deterministic Sealed Battery: Validated with a 100.0% pass rate across 1,000 unit, invariant, and adversarial vectors, cryptographically sealed under SHA-256 integrity digest. Strict Privacy by Design: Telemetry is permanently disabled (TELEMETRY_ENABLED = False). Zero transaction metadata leaves the EVM execution sandbox. Comparative Architectural Benchmarks: Traditional AI vs. ZK-ML vs. Werracle Metric / Feature Traditional Cloud AI (Chainlink / Web2) ZK-ML Provers (EZKL / Modulus Labs) WERRACLE (EVM Native) Model Weight Footprint Gigabytes (Off-chain servers) Off-chain Prover Cluster 0 Bytes (Procedural Dynamics) On-Chain Storage N/A (Multi-sig feed) Verification Keys & Proof Buffers Single 32-Byte Slot (bytes32) Inference / Proving Latency 12 – 36 seconds (Network lag) 10 – 300 seconds (SNARK generation) < 1 millisecond (Intra-Block) EVM Gas Cost ~40,000 – 80,000 gas ~250,000 – 500,000 gas (~$15+) ~21,438 gas (< $0.0005 on L2s) Flash-Loan Circuit Breaking ❌ Impossible (Too slow) ❌ Impossible (Cross-block delay) ✅ Native (Atomic Transaction Revert) External Infrastructure Trust Centralized Multi-Sig Signers Heavy GPU Prover Farms ZERO (100% Autonomous EVM Bytecode) Deterministic Verification Probabilistic / Variable Cryptographic (Circuit) 1,000 / 1,000 Tests (100.0% SHA-256 Sealed) Genişletilmiş Türkçe Özet (Extended Turkish Abstract) Bu araştırma ve replikasyon paketi, blokzincir akıllı sözleşmelerinde (EVM) yapay zeka çıkarımı yapmanın önündeki en büyük iki engel olan "bellek duvarı" (milyonlarca parametrenin blokzincirde saklanamaması) ve "ZK-ML gecikme açmazı" (SNARK kanıtlarının 10 ila 300 saniye sürmesi) problemlerini kökten çözen Werracle sistemini sunmaktadır. Dağlı ve ark. (arXiv:2609.25498) tarafından ispatlanan WERR fraktal kaçış dinamiği (z = z2 + c) temeline dayanan Werracle, karar hiper-düzlemlerini harici hiçbir yapay sinir ağı ağırlığına ihtiyaç duymadan, yalnızca 24 baytlık bir koordinat tohumundan (Θ = cx, cy, zoom) anlık olarak türetir. Modelin tamamı tek bir 32-baytlık EVM depolama yuvasına (bytes32) sığdırılmıştır. Saf Solidity baytkodunda Q16.16 sabit noktalı aritmetik (WerrMath.sol) ile çalışan Werracle, 16 noktalı Pareto mikro-ızgara analizini yalnızca 21.438 gas (< 0.0005 USD) harcayarak milisaniyenin altında tamamlar. Bu sayede blok-içi (intra-block) flaş kredi saldırılarını ve sandviç MEV manipülasyonlarını atomik olarak durduran ilk yerel yapay zeka devre kesicisi (circuit breaker) elde edilmiştir. Package & Repository Manifest Werracle_EVM_AI_Oracle_Research_Paper.pdf: Camera-ready IEEE two-column formal research paper. contracts/Werracle.sol: Production 32-byte single-slot on-chain AI decision oracle. contracts/WerrMath.sol: High-performance Q16.16 fixed-point complex arithmetic library. contracts/hooks/WerracleFeeHook.sol: Uniswap v4 chaos-adaptive dynamic swap fee governor. tests/sealed/SEAL_MANIFEST.json: 1,000-test deterministic audit battery verification manifest (SHA-256 sealed). sim/werr_fixed_point.py & test_cross_validation.py: Python-to-Solidity mathematical cross-validation suite (100.0% parity). Live Endpoints & Open Science Resources Official GitHub Repository: https://github.com/pCwOrM/werracleInteractive Web Sandbox Simulator: https://pcworm.github.io/werracle/Live EVM Hardware Node (Chain ID 4242 @ mechsrv): https://api.answerr.me:4431/werracle/statusInteractive API Documentation: https://pcworm.github.io/werracle/apidocs.htmlCompanion Theoretical Paper: arXiv:2609.25498 • Zenodo DOI: 10.5281/zenodo.22939253Corporate Entity: ITOUCH BİLİŞİM SİSTEMLERİ LTD. ŞTİ. (Çukurova Teknokent, Adana, Türkiye)Official Contact: [email protected] | [email protected] | Autonomous Agent: [email protected]
Authors
- Zerrin Dağlı (ORCID: https://orcid.org/0000-0001-9490-6425)
- Daghan Dagli
- Volkan Dağlı
Institutions
- Toros University (TR)
- Anadolu University (TR)
- Mersin Üniversitesi (TR)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-24
- DOI
- https://doi.org/10.5281/zenodo.22942599
- Primary Topic
- Blockchain Technology Applications and Security
- Type
- preprint