Cloud-Native Vulnerable Flow Mapping Across Runtime and Infrastructure
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Solution Overview
Problem
Existing application security testing solutions are inadequate for cloud-native applications, as vulnerabilities in these systems span multiple code pieces and infrastructure layers, leading to poor security posture, high integration costs, and wasted developer time.
Innovation Solution
A method and system that maps runtime functions, infrastructure configurations, and logical flows in cloud-native applications to identify and validate vulnerable flows by injecting custom-crafted inputs and analyzing behavior, reducing false positives through comprehensive security testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing application security testing solutions are used, then testing can be performed on traditional monolith applications, but the solutions become outdated and ineffective for cloud-native applications with vulnerabilities spanning multiple code pieces and infrastructure layers
Solution Approach 1:
The system dynamically adapts to cloud-native architectures by automatically discovering and mapping runtime functions, infrastructure configurations, and logical flows during execution. This dynamic mapping capability allows the testing solution to effectively analyze vulnerabilities across multiple code pieces and infrastructure layers without requiring pre-configured architecture-specific rules.
Solution Approach 2:
The system introduces an intermediary layer that translates cloud-native runtime behavior into testable models. By mapping runtime functions to logical flows and infrastructure configurations to vulnerability patterns, the intermediary enables traditional testing concepts to work effectively in cloud-native environments without requiring complete redesign of testing frameworks.
2Measurement precision
If comprehensive vulnerability testing is performed across multiple infrastructure layers, then vulnerability detection accuracy improves, but testing complexity and integration cost increase
Solution Approach 1:
The system segments the complex cloud-native application into discrete runtime functions, logical flows, and infrastructure configurations. Each segment can be independently mapped and tested, reducing the complexity of comprehensive vulnerability testing while maintaining detection accuracy across multiple layers through systematic composition of results.
Solution Approach 2:
The system performs preliminary mapping of runtime functions to logical flows and infrastructure configurations before actual vulnerability testing. This pre-establishes the testing framework and data structures, enabling comprehensive vulnerability detection without increasing operational complexity during the testing execution phase.
3Ease of operation
If traditional monolith application security testing is used, then testing process is simple, but vulnerability source and sink locations are unclear in cloud-native applications
Solution Approach 1:
The system implements feedback mechanisms that trace vulnerability flows from source to sink by monitoring runtime function executions and logical flow transitions. This feedback loop provides continuous information about data movement through the application, enabling clear identification of vulnerability sources and sinks while maintaining operational simplicity through automated tracing.
Solution Approach 2:
The system adds a temporal and contextual dimension to vulnerability tracking by mapping runtime functions to logical flows across multiple infrastructure layers. This dimensional expansion enables traceability of vulnerability flows through time and space without complicating the testing process, as the tracing is performed automatically during normal application execution.
Data Source
AI summary
A method for assessing vulnerable flows in a cloud-native application, the method including the steps of: mapping runtime functions in microservices in the cloud-native application; mapping the application cloud-native stack infrastructure configurations; mapping logical flows between microservices and third-party components in the cloud-native application; creating and executing security tests on the mapped logical flows, infrastructure configurations and runtime functions to return tested runtime behavior; and analyzing the tested runtime behavior of the cloud native application to validate the potential vulnerable logical flows so as to return validated vulnerable flows.