In recent years, Generative AI has emerged as a transformative force across a variety of domains. In particular, the ability of Large Language Models (LLMs) to produce coherent and functional source code has generated considerable interest within the cybersecurity community. Offensive security, traditionally characterized by manual and labor-intensive processes, is now being reshaped by these powerful AI-driven tools. Generative models can translate high-level natural language descriptions into working offensive code artifacts, thereby accelerating exploit development and lowering the barrier to entry for adversarial activities [1] , [2].
Generative AI in Cybersecurity: Generating Offensive Code from Natural Language
Natella, Roberto;Cotroneo, Domenico
2025-01-01
Abstract
In recent years, Generative AI has emerged as a transformative force across a variety of domains. In particular, the ability of Large Language Models (LLMs) to produce coherent and functional source code has generated considerable interest within the cybersecurity community. Offensive security, traditionally characterized by manual and labor-intensive processes, is now being reshaped by these powerful AI-driven tools. Generative models can translate high-level natural language descriptions into working offensive code artifacts, thereby accelerating exploit development and lowering the barrier to entry for adversarial activities [1] , [2].I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
