Attack-path modeling is the practice of mapping possible chains of actions that connect one finding to the next. In security testing, it helps an analyst move from scattered reconnaissance results to a focused follow-on route, such as turning a weak banner, exposed service, or validation clue into the next probe. Rather than treating each alert as isolated, the model asks: what could an attacker try next, and what conditions would make that step succeed?
This matters because real attacks are usually multi-stage. Adversaries chain low-risk observations into privilege gain, lateral movement, or deeper application testing, while defenders use the same thinking to prioritize controls and close gaps between systems. In automated pentesting, attack-path modeling lets tooling choose the next test based on prior output, speeding up validation and revealing which defenses leak the most useful information. For defenders, it supports hardening, segmentation, and detection planning by showing where one weakness can lead.