Automated Network Segmentation Scanning Agents
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Solution Overview
Problem
Current network segmentation penetration testing is time-consuming and resource-intensive, especially in cloud computing environments, due to the lack of automated tools for self-service and scalability, and there is no technology to automatically certify segmented networks from a PCI DSS perspective.
Innovation Solution
A network segmentation effectiveness system that includes an electronic memory, interactive user interface, and computer processor to receive IP addresses, perform segmentation scans using software agents across multiple network tiers, generate reports, and automatically post results for authorized users, reducing the need for manual reporting and increasing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual penetration testing is performed on network segmentation, then compliance verification can be achieved, but the process becomes time-consuming and resource-intensive
Solution Approach 1:
The system enables automated self-service penetration testing where software agents autonomously perform segmentation verification without requiring manual intervention from security teams. The agents can be automatically deployed across network assets and execute compliance checks independently, transforming a manual process into an automated self-service operation that reduces time loss while maintaining compliance verification reliability
Solution Approach 2:
The patent replaces manual mechanical testing processes with automated software-based agents. These agents use computational methods to perform penetration testing and segmentation verification, substituting human operators and manual procedures with automated software systems that execute tests rapidly and consistently without the time constraints of manual operations
2Adaptability or versatility
If penetration testing is scaled to meet growing demand from cloud computing environments, then coverage is improved, but resources and costs increase significantly
Solution Approach 1:
The software agents are designed with multi-functionality to handle diverse testing scenarios across different cloud computing environments and network configurations. A single agent architecture can adapt to various target systems, compliance requirements, and network topologies, allowing scaled coverage without proportionally increasing resource requirements. The universal agent design eliminates the need for separate specialized tools for each testing scenario
Solution Approach 2:
The system uses software agents that can be replicated and deployed across multiple network assets simultaneously. Instead of allocating unique resources for each testing engagement, the same agent software can be copied and instantiated on numerous targets, enabling scaled coverage with minimal additional resource investment. Each agent instance operates independently but uses the same underlying software blueprint
3Reliability
If frequent penetration tests are conducted to satisfy PCI DSS requirements after infrastructure upgrades, then compliance is maintained, but coordination effort and time increase
Solution Approach 1:
The automated agents perform compliance testing autonomously without requiring coordination with multiple teams. The system self-manages test execution, result collection, and compliance determination, eliminating the complex coordination previously needed between intake/delivery/scheduling teams, business units, and compliance officers. This self-service capability maintains compliance reliability while dramatically reducing operational complexity
4Productivity
If automated tools are implemented for segmentation scanning, then productivity increases, but automation capability must be built from scratch
Solution Approach 1:
The system merges multiple functions into a unified automated scanning platform. The software agents combine network discovery, vulnerability assessment, segmentation verification, and compliance reporting into single integrated tools. This consolidation achieves high productivity through automation while managing complexity by combining previously separate functions into cohesive system components rather than requiring multiple independent tools
Data Source
AI summary
The invention relates to a network segmentation effectiveness attestation system and method. The method may comprise receiving a list of internet protocol (IP) addresses for information technology (IT) assets within a defined scope, and executing a plurality of segmentation scans from outside a cardholder data environment (CDE) using a plurality of software agents. The software agents may be deployed and orchestrated across multiple network tiers. The method may also comprise receiving, automatically interpreting, and certifying results from the segmentation scan, automatically generating a report from the results of the segmentation scan, and automatically posting the report for authorized users to access.