5 papers
From Sands to Mansions: Towards Automated Cyberattack Emulation with Classical Planning and Large Language Models
Lingzhi Wang, Zhenyuan Li, Yi Jiang +4
Evolving attacker capabilities demand realistic and continuously updated cyberattack emulation for threat-informed defense and security benchmarking. Towards automated attack emula…
Automated Penetration Testing with LLM Agents and Classical Planning
Lingzhi Wang, Xinyi Shi, Ziyu Li +8
While penetration testing plays a vital role in cybersecurity, achieving fully automated, hands-off-the-keyboard execution remains a significant research challenge. In this paper,…
GraphFaaS: Serverless GNN Inference for Burst-Resilient, Real-Time Intrusion Detection
Lingzhi Wang, Vinod Yegneswaran, Xinyi Shi +3
Provenance-based intrusion detection is an increasingly popular application of graphical machine learning in cybersecurity, where system activities are modeled as provenance graphs…
AEAS: Actionable Exploit Assessment System
Xiangmin Shen, Wenyuan Cheng, Yan Chen +6
Security practitioners face growing challenges in exploit assessment, as public vulnerability repositories are increasingly populated with inconsistent and low-quality exploit arti…
PentestAgent: Incorporating LLM Agents to Automated Penetration Testing
Xiangmin Shen, Lingzhi Wang, Zhenyuan Li +5
Penetration testing is a critical technique for identifying security vulnerabilities, traditionally performed manually by skilled security specialists. This complex process involve…