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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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@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