80 citations · 347 across the 29 of their papers we have counts for
5 papers · 1 filter
AI-Generated PowerShell Malware: An Experimental Framework and Dataset
Luciano Pianese, Vittorio Orbinato, Pietro Liguori +1
Generative AI has emerged as a significant cybersecurity threat, with several recent attack campaigns leveraging LLMs to generate code for malicious purposes via scripting language…
Willing but Unable: Separating Refusal from Capability in Code LLMs via Abliteration
Cristina Carleo, Pietro Liguori, Naghmeh Ivaki +1
Producing a labeled vulnerable code at scale is a recurring obstacle for learning-based vulnerability detection: mined corpora carry substantial label noise, and existing LLM-based…
The Power of Words: Generating PowerShell Attacks from Natural Language
Pietro Liguori, Christian Marescalco, Roberto Natella +2
As the Windows OS stands out as one of the most targeted systems, the PowerShell language has become a key tool for malicious actors and cybersecurity professionals (e.g., for pene…
AI Code Generators for Security: Friend or Foe?
Roberto Natella, Pietro Liguori, Cristina Improta +2
Recent advances of artificial intelligence (AI) code generators are opening new opportunities in software security research, including misuse by malicious actors. We review use cas…
Vulnerabilities in AI Code Generators: Exploring Targeted Data Poisoning Attacks
Domenico Cotroneo, Cristina Improta, Pietro Liguori +1
AI-based code generators have become pivotal in assisting developers in writing software starting from natural language (NL). However, they are trained on large amounts of data, of…