Adaptive Machine Learning Platform for Faster Penetration Risk Assessment
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Solution Overview
Problem
Existing penetration testing methods are cumbersome and inefficient for internal users and external testers, as they struggle to identify security weaknesses in distributed and industrial systems effectively.
Innovation Solution
A security and risk assessment computer system that performs penetration testing remotely, utilizing an adaptive machine learning platform to gather and analyze publicly available data from various sources, including job portals and social media, to identify potential security risks and generate customized penetration testing plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional penetration testing methods are used, then security weaknesses can be identified, but the process is time-consuming and cumbersome
Solution Approach 1:
The system performs preliminary actions by automatically gathering information from multiple public sources (job portals, social media, documentation) before the actual penetration testing begins. This pre-reconnaissance phase populates a knowledge base with system information, reducing the time needed during the actual testing phase while maintaining comprehensive security assessment coverage.
Solution Approach 2:
The penetration testing system performs self-service by automatically executing multiple testing phases including information gathering, vulnerability identification, exploitation, and reporting without requiring continuous human intervention. The automated orchestration engine manages the entire penetration testing lifecycle, significantly reducing the time investment required from security professionals.
2Ease of operation
If internal users perform penetration testing, then they are familiar with the systems, but they may be blind to the weaknesses
Solution Approach 1:
The system inverts the traditional approach by having an external automated system perform the penetration testing instead of internal users. This external perspective, combined with automated information gathering from public sources, provides objectivity and eliminates the blindness that internal users experience, while still achieving comprehensive security assessment.
Solution Approach 2:
The automated penetration testing system acts as an intermediary between internal users and the actual security assessment. It gathers information that internal users might overlook from external public sources and performs objective vulnerability identification, bridging the gap between system familiarity and unbiased security evaluation.
3Measurement precision
If external third party penetration testers are used, then objectivity is improved, but they do not have knowledge of the internal system
Solution Approach 1:
The system achieves universality by combining multiple functions in one automated platform: it performs information gathering from external public sources, executes penetration testing with objective external perspective, and integrates results into comprehensive security assessments. This multi-functional approach eliminates the need to choose between external objectivity and internal knowledge.
Solution Approach 2:
The system performs preliminary information gathering from multiple public sources before the penetration testing begins, building a knowledge base that compensates for the external tester's lack of internal system knowledge. This pre-populated context enables objective assessment while maintaining relevance to the specific internal system being tested.
4Measurement precision
If comprehensive information gathering is performed, then security assessment accuracy is improved, but the complexity of the process increases
Solution Approach 1:
The system merges multiple information gathering activities and penetration testing phases into a single automated orchestration process. By combining information gathering from job portals, social media, documentation, and technical reconnaissance into one unified workflow, the system achieves comprehensive security assessment without requiring manual coordination of complex separate processes.
Solution Approach 2:
The automated orchestration engine performs self-service by automatically managing the complexity of comprehensive information gathering and penetration testing. It handles data collection, analysis, vulnerability identification, and reporting without requiring human users to navigate complex procedures, thereby maintaining high assessment accuracy while reducing perceived complexity for end users.
Data Source
AI summary
Systems and methods are provided for implementing an adaptive machine learning platform for security penetration and risk assessment. For example, the system can receive publicly-available information associated with a client computer system, process the information to identify an input feature, and implement a machine learning model to identify the corresponding risk associated with the input feature. The system can recommend a penetration test for discovered weaknesses associated with the input feature and help make changes to the client computer system to improve security and reduce risk overall.