Cloud-Native Attack Path Analysis for Dormant Vulnerability Prevention
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing attack path analysis techniques are reactive, failing to detect vulnerabilities until they become active in production systems, providing attackers with a significant window to exploit newly activated paths, as current solutions like CNAPPs scan applications infrequently.
Innovation Solution
A proactive approach that generates variants of cloud-native applications to simulate vulnerabilities, identifies dormant attack paths, and updates an attack path knowledge base, preventing changes that could activate these paths, integrating with CI/CD pipelines for immediate prevention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If reactive attack path analysis is used to scan applications in production, then current vulnerabilities can be detected, but dormant attack paths remain undetected until exploitation occurs
Solution Approach 1:
The system performs preliminary action by generating application variants and identifying dormant attack paths before they can be exploited in production. Attack path analysis is conducted on modified variants during development/testing phases, enabling security teams to prevent vulnerable configurations from reaching production environments.
Solution Approach 2:
The system creates copies (variants) of the application with modified configurations to simulate potential vulnerabilities. These variants include deliberate configuration changes that may activate dormant attack paths, allowing safe analysis without risking production systems.
2Reliability
If application variants are generated to simulate vulnerabilities, then dormant attack paths can be identified early, but computational resources and time are consumed
Solution Approach 1:
The system applies local quality by making targeted, localized modifications to application configurations rather than analyzing entire systems comprehensively. Specific configuration parameters are adjusted to activate particular attack paths, focusing computational resources on high-risk areas.
Solution Approach 2:
The system utilizes parameter changes by systematically modifying configuration parameters in application variants. Different configuration values and settings are tested to reveal how specific parameter combinations may create vulnerable attack paths.
Data Source
AI summary
In one implementation, a device may generate variants of a cloud-native application modified to simulate vulnerabilities. The device may identify dormant attack paths in the variants susceptible to activation. The device may update an attack path knowledge base with the dormant attack paths. The device may prevent changes to the cloud-native application in a production environment that would activate the dormant attack paths identified in the variants.