AUTHOR=Proverbio Daniele , Buscemi Alessio , Di Stefano Alessandro , Han The Anh , Castignani German , Liò Pietro 
  
TITLE=Can LLMs effectively provide game-theoretic-based scenarios for cybersecurity?
  
JOURNAL=Frontiers in Computer Science
  
VOLUME=Volume 7 - 2025
  
YEAR=2025
  
URL=https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2025.1703586
  
DOI=10.3389/fcomp.2025.1703586
  
ISSN=2624-9898
  
ABSTRACT=IntroductionGame theory has long served as a foundational tool in cybersecurity to test, predict, and design strategic interactions between attackers and defenders. The recent advent of Large Language Models (LLMs) offers new tools and challenges for the security of computer systems. In this work, we investigate whether classical game-theoretic frameworks can effectively capture the behaviors of LLM-driven actors and bots.MethodsUsing a reproducible framework for game-theoretic LLM agents, we investigate two canonical scenarios—the one-shot zero-sum game and the dynamic Prisoner's Dilemma—and we test whether LLMs converge to expected outcomes or exhibit deviations due to embedded biases. We experiments on four state-of-the-art LLMs and five natural languages (English, French, Arabic, Vietnamese, and Mandarin Chinese) to assess linguistic sensitivity.ResultsFor both games, we observe that the final payoffs are influenced by agents characteristics such as personality traits or knowledge of repeated rounds. We also uncover an unexpected sensitivity of the final payoffs to the choice of languages, which should warn against indiscriminate application of LLMs in cybersecurity applications and call for in-depth studies, as LLMs may behave differently when deployed in different countries. We also employ quantitative metrics to evaluate the internal consistency and cross-language stability of LLM agents.DiscussionIn addition to uncovering unexpected behaviors requiring attention by scholars and practitioners, our work can help guide the selection of the most stable LLMs and optimizing models for secure applications.