15 citations · 21 across the 13 of their papers we have counts for
8 papers · 1 filter
Connecting the Dots in Agentic AI Security: A Cross-Dimensional Threat Taxonomy, Evaluation Maturity, and Open Challenges
Heewon Baek, Alsharif Abuadbba, Kristen Moore +2
Agentic AI extends LLM security beyond generated content to persistent state, autonomous actions, tool use, and interactions with humans and other agents. Existing threat classific…
DEFENGRAPH: Knowledge Graph-Enhanced LLMs for Blue Team Cyber Defense
Zhen Wang, Kristen Moore, Qin Wang +7
Large Language Models (LLMs) show promise for supporting decision-making in cybersecurity, but their reliability in high-stakes, time-evolving environments remains limited due to h…
APT-Agent: Automated Penetration Testing using Large Language Models
William Guanting Li, Alsharif Abuadbba, Kristen Moore +1
Penetration testing is essential to securing modern web infrastructures, yet traditional manual methods struggle to keep pace with their scale and complexity. Large Language Models…
Can Current Detectors Catch Face-to-Voice Deepfake Attacks?
Nguyen Linh Bao Nguyen, Alsharif Abuadbba, Kristen Moore +1
The rapid advancement of generative models has enabled the creation of increasingly stealthy synthetic voices, commonly referred to as audio deepfakes. A recent technique, FOICE [U…
From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Alsharif Abuadbba, Chris Hicks, Kristen Moore +4
Large Language Models (LLMs) are set to reshape cybersecurity by augmenting red and blue team operations. Red teams can exploit LLMs to plan attacks, craft phishing content, simula…
From Solitary Directives to Interactive Encouragement! LLM Secure Code Generation by Natural Language Prompting
Shigang Liu, Bushra Sabir, Seung Ick Jang +5
Large Language Models (LLMs) have shown remarkable potential in code generation, making them increasingly important in the field. However, the security issues of generated code hav…
An Investigation into Misuse of Java Security APIs by Large Language Models
Zahra Mousavi, Chadni Islam, Kristen Moore +2
The increasing trend of using Large Language Models (LLMs) for code generation raises the question of their capability to generate trustworthy code. While many researchers are expl…
RAIDER: Reinforcement-aided Spear Phishing Detector
Keelan Evans, Alsharif Abuadbba, Tingmin Wu +5
Spear Phishing is a harmful cyber-attack facing business and individuals worldwide. Considerable research has been conducted recently into the use of Machine Learning (ML) techniqu…