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 / Liguori, Pietro; Natella, Roberto; Cotroneo, Domenico. - (2025), pp. 174-175. ( 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume, DSN-S 2025 University of Naples Federico II, ita 2025) [10.1109/dsn-s65789.2025.00059].

Generative AI in Cybersecurity: Generating Offensive Code from Natural Language

Liguori, Pietro
;
Natella, Roberto;Cotroneo, Domenico
2025

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].
2025
Generative AI in Cybersecurity: Generating Offensive Code from Natural Language / Liguori, Pietro; Natella, Roberto; Cotroneo, Domenico. - (2025), pp. 174-175. ( 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume, DSN-S 2025 University of Naples Federico II, ita 2025) [10.1109/dsn-s65789.2025.00059].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/1008381
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