Thinking in Graphs: Neo4j-Backed Exploit-Chain Reasoning for LLM Penetration-Testing Agents

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arXiv:2610.20902v1 Announce Type: new Abstract: LLM coding agents such as Claude Code and OpenAI Codex can drive penetration-testing tools, but they reason about an engagement as a flat list of findings in a context window. Attackers think in graphs: isolated low-severity exposures turn catastrophic once chained through credential capture, privilege escalation, and lateral movement. This gap feeds a common belief that AI agents cannot truly chain exploitation; we argue this describes the flat c