Automated system discovers complex attack chains for better defenses
Automated Post-Exploitation Attack Chain Exploration Based on a Phase-guided Hybrid Planning-Monte Carlo Tree Search Algorithm
Cryptography and SecurityComputers and Society
Summary
Cyber attackers often use complicated steps to break into and take control of computer systems, which can be hard to find manually. The authors created APEX, a system that automatically finds these attack routes by combining planning and smart searching methods. This system helps uncover both known and new ways attackers might escalate access on computers. The findings help improve security by revealing hidden threats in real-world environments.
What this means in practice
- •For cybersecurity operations teams: Identify hidden and complex attacker pathways in enterprise networks to strengthen defenses and incident response.
- •For cloud infrastructure administrators: Discover privilege escalation and other attack chains specific to cloud environments to harden configurations.
Authors
Jie Ying, Mengce Zheng, Ruoxi Chen, Wenrui Cheng, Tiantian Zhu, Zhongjie Zhu
Abstract
Advanced attackers in post-exploitation scenarios increasingly craft attack chains that combine benign operations, configuration errors, and vulnerability exploitation to achieve objectives like privilege escalation. While such chains pose significant threats, manually discovering them in complex modern host environments is prohibitively labor-intensive. Automating this discovery is therefore essential for proactive defense, yet existing methods still suffer from inefficiency and lack diversity when exploring these attack chains. To address these limitations, we present APEX, an Automated Post-EXploitation attack chain exploration system. This system transforms attack chain discovery into a planning problem and solves it with a novel phase-guided hybrid Planning-Monte Carlo Tree Search (MCTS) algorithm. By organizing attack actions into semantic phases and integrating symbolic planning with MCTS, APEX enables efficient exploration of the state space while generating multiple diverse chains. Evaluations on a benchmark comprising 5 virtual machines, 30 synthetic problems and 291 cloud instances demonstrate that APEX successfully discovers both known and previously unreported attack chains--including 9 novel privilege escalation vectors--providing actionable intelligence for hardening complex production environments.