Synthetic Cyber-Risk Model for Dynamic Vulnerability Assessment
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Solution Overview
Problem
Current network security systems face challenges in effectively detecting and responding to cyber threats due to increasing complexity and sophistication of cyberattacks, as well as the growing number of access points and evolving threats, which existing monitoring and prevention products often fail to keep pace with.
Innovation Solution
The technology generates synthetic security events to simulate cyber threat scenarios, using synthetic test host agents installed across a network to measure the effectiveness of security controls and dynamically update security capabilities in real-time, providing feedback for improving detection and response mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional monitoring and prevention products are used to detect cyber threats, then basic security coverage is provided, but they fail to keep pace with the increasing sophistication and complexity of cyberattacks
Solution Approach 1:
The system dynamically adapts security testing by automatically generating new synthetic attack scenarios based on feedback from previous tests and emerging threat intelligence. The synthetic attacker agents continuously evolve their tactics, techniques, and procedures to match real-world threat sophistication, transforming static security monitoring into a dynamic, adaptive system that improves over time.
Solution Approach 2:
The system performs preliminary security assessment by deploying synthetic attacker agents that simulate cyber threats before real attacks occur. These agents proactively identify vulnerabilities in security controls, allowing organizations to strengthen defenses in advance rather than reacting to actual breaches.
2Reliability
If comprehensive network scanning and monitoring are implemented to cover all access points, then security coverage is improved, but the overwhelming amount of network traffic makes monitoring and scanning impractical
Solution Approach 1:
The system introduces synthetic attacker agents as intermediaries between security controls and actual threats. These agents act as controlled proxies that interact with security monitoring systems, generating manageable amounts of targeted traffic that specifically test security controls without overwhelming the network with comprehensive scanning of all access points.
Solution Approach 2:
The monitoring approach is segmented by focusing testing efforts on specific security controls and attack vectors rather than uniformly scanning all network access points. Synthetic attackers are deployed to target particular vulnerabilities and control mechanisms, dividing the overwhelming monitoring task into manageable, focused assessment campaigns.
3Reliability
If manual security update processes are used across large networks, then control over security measures is maintained, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system enables self-service security testing by automatically generating synthetic attack scenarios, executing them across the network, and collecting results without requiring manual intervention for each test campaign. The synthetic attackers autonomously adapt their behavior based on detected security controls, significantly accelerating the security assessment process while maintaining comprehensive coverage.
Solution Approach 2:
The system efficiently manages security updates by dynamically changing test parameters such as attack vectors, target systems, and synthetic agent behavior based on detected security controls. This allows rapid iteration through multiple security scenarios and accelerated deployment of security measures across large networks by adjusting test configurations rather than manual reconfiguration.
Data Source
AI summary
A system, method, and device are presented for assessing a target network's vulnerability to a real cyberthreat based on determining policy-based synthetic tests configured to model the behavior of the cyberthreat. Real-time feedback from the target network (e.g., servers, desktops, and network/monitoring hardware and/or software equipment) are received, analyzed, and used to determine whether any modifications to the same or a new synthesized test is preferred. The technology includes self-healing processes that, using the feedback mechanisms, can attempt to find patches for known vulnerabilities, test for unknown vulnerabilities, and configure the target network's resources in accordance with predefined service-level agreements.