  Large Language Models (LLMs) have emerged as powerful tools across various
domains within cyber security. Notably, recent studies are increasingly
exploring LLMs applied to the context of blockchain security (BS). However,
there remains a gap in a comprehensive understanding regarding the full scope
of applications, impacts, and potential constraints of LLMs on blockchain
security. To fill this gap, we undertake a literature review focusing on the
studies that apply LLMs in blockchain security (LLM4BS).
  Our study aims to comprehensively analyze and understand existing research,
and elucidate how LLMs contribute to enhancing the security of blockchain
systems. Through a thorough examination of existing literature, we delve into
the integration of LLMs into various aspects of blockchain security. We explore
the mechanisms through which LLMs can bolster blockchain security, including
their applications in smart contract auditing, transaction anomaly detection,
vulnerability repair, program analysis of smart contracts, and serving as
participants in the cryptocurrency community. Furthermore, we assess the
challenges and limitations associated with leveraging LLMs for enhancing
blockchain security, considering factors such as scalability, privacy concerns,
and ethical concerns. Our thorough review sheds light on the opportunities and
potential risks of tasks on LLM4BS, providing valuable insights for
researchers, practitioners, and policymakers alike.
