attack-tree-construction

Systematic visualization and analysis of attack paths with difficulty, cost, and detection metrics. Systematic attack path visualization and analysis. - Provides Python data models for building attack trees with OR/AND logic, leaf attacks, and attributes (difficulty, cost, detection risk, time required) - Includes fluent builder API for constructing trees programmatically and methods to find easiest, cheapest, and stealthiest attack paths - Exports to Mermaid and PlantUML diagram formats for stakeholder communication and threat visualization - Analyzes all possible attack paths, identifies critical nodes, and prioritizes mitigations by coverage impact - Visualizing complex attack scenarios - Identifying defense gaps and priorities - Communicating risks to stakeholders - Planning defensive investments - Penetration test planning - Security architecture review - Start with clear goals - Define what attacker wants - Be exhaustive - Consider all attack vectors - Attribute attacks - Cost, skill, and detection - Update regularly - New threats emerge - Validate with experts - Red team review - Don't oversimplify - Real attacks are complex - Don't ignore dependencies - AND nodes matter - Don't forget insider threats - Not all attackers are external - Don't skip mitigations - Trees are for defense planning - Don't make it static - Threat landscape evolves