This paper introduces SymGPT , a tool that combines LLMs with symbolic execution to automatically verify smart contracts’ compliance with ERC rules. We begin by empirically analyzing 132 ERC rules from three major ERC standards, examining their content, security implications, and natural language descriptions. Based on this study, SymGPT instructs an LLM to translate ERC rules into a domain-specific language, synthesizes constraints from the translated rules to model potential rule violations, and performs symbolic execution for violation detection. Our evaluation shows that SymGPT identifies 5,783 ERC rule violations in 4,000 real-world contracts, including 1,375 violations with clear attack paths for financial theft. Furthermore, SymGPT outperforms six automated techniques and a security-expert auditing service, underscoring its superiority over current smart contract analysis methods.

@article{paperbot3850,
  title = {SymGPT: Auditing Smart Contracts via Combining Symbolic Execution with Large Language Models},
  author = {Shihao Xia and Mengting He and Shuai Shao and Tingting Yu and Yiying Zhang and Nobuko Yoshida and Linhai Song},
  journal = {Proceedings of the ACM on Programming Languages},
  volume = {10},
  number = {OOPSLA1},
  year = {2026},
  doi = {10.1145/3798217}
}