🚀 CloudSEK becomes first Indian origin cybersecurity company to receive investment from US state fund Read more An attack graph is a model that maps how an attacker could move through a network, showing the systems, vulnerabilities, and paths that connect an entry point to a critical asset. Attack graphs help security teams predict and disrupt attack paths before execution. The shift toward this approach is well documented. Gartner introduced continuous threat exposure management in 2022 and predicts that organizations prioritizing it will be three times less likely to suffer a breach by 2026. Attack graphs sit at the center of that shift, turning isolated vulnerability lists into the connected attack paths an attacker would actually follow. This guide explains what attack graphs are, the components that make them up, and how they work. It covers attack graphs versus attack trees and attack paths, the main types, how to build one, the benefits, use cases, best practices, and the limitations to plan around. An attack graph is a graphical model of the routes an attacker could take through an environment to reach a target. Nodes represent systems, conditions, or vulnerabilities, and edges represent the exploits or actions that move an attacker from one state to the next. The graph turns a list of separate weaknesses into a connected map of how those weaknesses chain together. Attack graphs answer a question that vulnerability scans cannot. A scan reports which flaws exist, while an attack graph shows which flaws sit on a path to something that matters. That distinction lets teams focus on the exposures that actually lead to a breach. Four traits define an attack graph: An attack graph is built from five components: These components combine into a working model: nodes and edges form the structure, while state information, attack