140 citations · 600 across the 36 of their papers we have counts for
4 papers · 1 filter
Can Neural Decompilation Assist Vulnerability Prediction on Binary Code?
D. Cotroneo, F. C. Grasso, R. Natella +1
Vulnerability prediction is valuable in identifying security issues efficiently, even though it requires the source code of the target software system, which is a restrictive hypot…
Enhancing AI-based Generation of Software Exploits with Contextual Information
Pietro Liguori, Cristina Improta, Roberto Natella +2
This practical experience report explores Neural Machine Translation (NMT) models' capability to generate offensive security code from natural language (NL) descriptions, highlight…
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…