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paper llmsec-2026-00070

Benchmarking LLM-Based Static Analysis for Secure Smart Contract Development: Reliability, Limitations, and Potential Hybrid Solutions

Stefan-Claudiu Susan, Andrei Arusoaie, Dorel Lucanu

2026-05

Abstract

The irreversible nature of blockchain transactions makes the identification of smart contract vulnerabilities an essential requirement for secure system development. While Large Language Models (LLMs) are increasingly integrated into developer workflows, their reliability as autonomous security auditors remains unproven. We assess whether current generative models are a viable replacement for, or only a complement to, traditional static-analysis tools. Our findings indicate that LLM efficacy is

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Cite This Resource

@article{llmsec202600070,
  title = {Benchmarking LLM-Based Static Analysis for Secure Smart Contract Development: Reliability, Limitations, and Potential Hybrid Solutions},
  author = {Stefan-Claudiu Susan and Andrei Arusoaie and Dorel Lucanu},
  year = {2026},
  url = {https://arxiv.org/abs/2605.11163},
}

Metadata

Added
2026-05-17
Added by
automation
Source
arxiv
arxiv_id
2605.11163