How does this skill help identify security gaps?

It maps specific attack paths to their existing mitigations; any 'leaf' attack node without a corresponding mitigation represents a critical defense gap.

Can I export these models for security reporting?

Yes, the skill provides Python templates to export attack tree data to JSON format, allowing for easy integration into security documentation and stakeholder reports.

What is an attack tree?

An attack tree is a visual and mathematical representation of the different ways a system can be attacked, organized in a hierarchical tree structure with a main goal at the root.

What is the difference between AND and OR nodes?

OR nodes represent alternative methods to achieve a sub-goal, while AND nodes represent multiple steps that must all be successfully completed by an attacker.

Attack Tree Construction

Name: Attack Tree Construction
Author: ccf

byccf

Security & Testing

Visualizes and analyzes security threat paths through systematic attack tree modeling and risk assessment.

About

This skill enables security researchers and developers to systematically map out potential attack vectors using a structured hierarchical model. By defining root goals and breaking them down into AND/OR logic nodes with specific attributes like cost, difficulty, and detection risk, it allows for the identification of the easiest or cheapest paths an attacker might take. It is an essential tool for performing architectural reviews, planning penetration tests, and quantifying the impact of defensive investments by pinpointing unmitigated leaf nodes in complex system designs.

Key Features

Quantitative risk modeling using cost, time, and expertise attributes
Automated path analysis to identify the easiest or stealthiest attack routes
Hierarchical AND/OR logic node construction for complex threat scenarios
0 GitHub stars
Mitigation gap analysis to highlight undefended attack vectors
Python-based data model and JSON export for reporting and integration

Use Cases

Prioritizing defensive engineering tasks based on quantified risk paths
Conducting security architecture reviews for new system designs
Planning red team operations and scoping penetration tests

About

Key Features

Quantitative risk modeling using cost, time, and expertise attributes
Automated path analysis to identify the easiest or stealthiest attack routes
Hierarchical AND/OR logic node construction for complex threat scenarios
0 GitHub stars
Mitigation gap analysis to highlight undefended attack vectors
Python-based data model and JSON export for reporting and integration

Use Cases

Prioritizing defensive engineering tasks based on quantified risk paths
Conducting security architecture reviews for new system designs
Planning red team operations and scoping penetration tests