Safe Edges is a high-performance blockchain security firm advancing the industry with research-driven audits, automated vulnerability detection, and deep protocol analysis across smart contracts, dApps, and Web3 infrastructure.
Trusted by leading L1 and L2 ecosystems, Safe Edges has helped secure billions in onchain value through its advanced static analysis engines, custom fuzzing frameworks, and multi-layer verification models built for high-throughput execution environments such as Fuel, EVM, Move, and UTXO-based systems.
As one of the key contributors shaping emerging smart contract security standards and next-generation auditing methodologies, Safe Edges helps teams deploy high-stakes DeFi, NFT, and protocol-layer platforms with a strong security focus.
Safe Edges is leading the charge in raising global Web3 security standards through advanced auditing and research-driven exploit prevention.
Safe Edges specializes in comprehensive smart contract and protocol audits, combining deep manual analysis with advanced research-driven methodologies. Our team of expert auditors identifies vulnerabilities at the compiler, VM, and protocol levels.
Safe Edges’ EVM Sleuth monitoring system provides advanced onchain threat detection for chains and EVM-compatible networks. It continuously scans smart contracts and blockchain activity for suspicious patterns, including unauthorized minting, hidden backdoors, abnormal fund movements, and potential rug pulls. By combining real-time analytics with deep security expertise, the system generates precise risk scores and alerts, enabling investors, auditors, and DeFi platforms to assess trustworthiness and mitigate threats before they escalate. This proactive approach helps support ongoing project integrity and enhances overall ecosystem security.
SwayScan is a specialized auditing and analysis platform for Sway-based smart contracts on the Fuel network. Designed to address the unique characteristics of UTXO-based execution and parallel transaction processing, SwayScan combines automated detection with deep manual auditing insights to ensure maximum protocol safety.
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