LLMs work better together in smart contract audits

Smart contract bugs continue to drain real money from blockchain systems, even after years of tooling and research. A new academic study suggests that large language models can spot more of those flaws when they work in coordinated groups instead of alone. Researchers at Georgia Tech have developed a framework called LLMBugScanner that combines fine tuned language models with ensemble voting to detect vulnerabilities in Ethereum smart contracts. The research evaluates whether pairing domain specific … More → The post LLMs work better together in smart contract audits appeared first on Help Net Security.

Continue reading →