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LLM-Based Intelligent Agents for Cybersecurity: A Tutorial and Survey of Automated Vulnerability Discovery

This paper provides a tutorial and survey of LLM-based agents for automated vulnerability discovery and penetration testing. The rapid advancements in Large Language Models (LLMs) have opened new possibilities for their application in cybersecurity. Unlike traditional tools, LLMs can process natural...

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Päätekijät: Robel Addis, Kiran Porter, Jayden Ryan, Micah Stull, Shengjie Xu, Paul Wagner, Robert Honomichl, Steven Forsyth
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: IEEE 2026-01-01
Sarja:IEEE Access
Aiheet:
Large language models (LLMs)
AI agents
cybersecurity
autonomous penetration testing
prompt engineering
vulnerability discovery
Linkit:https://ieeexplore.ieee.org/document/11580353/
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