Automated Attack Tree Generator for Penetration Testing
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Solution Overview
Problem
Generating attack trees for penetration testing is inefficient and time-consuming, and their quality depends on the expertise of the system experts who manually create them, making it challenging to simulate various attack paths effectively.
Innovation Solution
Automatically generating attack trees by processing goal data, start-up information, and tool data to create a graphical representation that includes data sets and links between them, allowing for the integration of multiple tools and attack vectors, thereby enabling semi-automated penetration testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If attack trees are manually generated by system experts, then the attack tree quality reflects expert knowledge, but the process is inefficient and time-consuming
Solution Approach 1:
The system performs self-service by automatically generating attack trees using goal data, start-up information, and tool data without requiring manual expert intervention. The processor autonomously processes the input data and generates the attack tree structure, eliminating the time-consuming manual generation process while maintaining quality through systematic data processing.
Solution Approach 2:
The manual mechanical process of expert-generated attack trees is replaced with an automated computational system. The processor uses algorithmic processing of goal data, start-up information, and tool data to substitute the human expert's manual work, achieving both efficiency improvement and consistent quality through systematic data-driven generation.
2Reliability
If attack trees are manually generated by system experts, then the attack tree reflects detailed system knowledge, but the process is complex and requires high expertise
Solution Approach 1:
The attack tree generation process is segmented into distinct input components: goal data, start-up information, and tool data. Each segment serves a specific purpose in the generation process, allowing the system to process complex information in manageable parts while maintaining overall accuracy through structured data integration.
Solution Approach 2:
The system uses processed data as an intermediary between the input information and the final attack tree structure. The processor transforms goal data, start-up information, and tool data into a standardized format that mediates the conversion to attack tree nodes and edges, simplifying the overall process while preserving accuracy.
3Adaptability or versatility
If attack trees are manually generated, then customization to specific systems is possible, but the process is time-consuming and resource-intensive
Solution Approach 1:
The system achieves customization by changing parameters in the input data (goal data, start-up information, tool data) rather than changing the generation process itself. By modifying these input parameters, the same automated system can generate attack trees adapted to different specific systems rapidly, maintaining versatility while eliminating time loss.
Solution Approach 2:
The automated generation system serves as a universal tool that can handle multiple different systems and scenarios through a single process. By accepting varied input data formats and processing them through the same mechanism, the system achieves broad adaptability across different penetration testing contexts without requiring separate manual generation processes for each case.
Data Source
AI summary
Implementations of the present disclosure include methods, systems, and computer-readable storage mediums for receiving goal data and start-up information, the goal data indicating a goal to be achieved during a penetration test, the start-up information indicating initial data for beginning the penetration test, receiving tool data from a register of tools, the tool data including one or more tools that can be used during the penetration test, and, for each tool, input data required to execute the tool and output data provided by the tool, processing the goal data, the start-up information and the tool data to automatically generate attack tree data, the attack tree data including a plurality of data sets and links between data sets, and providing the attack tree data to display a graphical representation of an attack tree on a display.