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Implement a blockchain monitoring backend system based on Spring Boot
Develop on-chain hacker address identification and tracking algorithms and alert systems to monitor suspicious transaction activities in real-time
Build transaction relationship graphs to visualize fund flows
Integrate multi-chain monitoring capabilities covering major public chains (ETH, BTC, BSC, etc.)
Build sandbox environments based on Revm to simulate on-chain transaction execution processes and detect potential vulnerabilities and MEV-related risks
Establish a real-time alert system for monitoring high-risk operations across multiple dimensions, such as abnormal gas consumption, permission changes, fund flows, etc.
Research cutting-edge attack methods, optimize detection rule sets, and generate security incident analysis reports
Bachelor's/Master's degree in Computer Science, Network Security, or related technical field
Proficiency in at least one mainstream language (Java/Python/Rust)
3+ years of Java development experience, proficient in Spring Boot, Spring Cloud, and other frameworks
Proficient in Kafka, Redis, Elasticsearch technology stack, with experience using relational databases (MySQL)
Knowledge of using Python/Rust for building blockchain analyzers (such as Revm-based sandboxes)
Understanding of Revm - including simulating attack POCs and sandbox environment testing
Experience in Anti-Money Laundering (AML) or blockchain security analysis
Relevant experience and achievements in on-chain risk analysis - including real-time threat detection, incident analysis, etc.
Deep understanding of mainstream DeFi protocols
Contributions to open-source blockchain security tools or research
MEV expertise - analyzing front-run and back-run patterns, designing anti-MEV protocols
Familiarity with at least one mainstream blockchain platform (such as Ethereum, Solana, etc.) and proficiency in its smart contract mechanisms
Profound understanding of common vulnerabilities in DeFi protocols and their attack methods, capable of analyzing and handling attack incidents
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