Adaptive Cyber-Attack Emulation System
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Solution Overview
Problem
Conventional Breach and Attack Simulation (BAS) tools are limited in assessing resilience against new, unknown cyber threats as they rely on reproducing static lists of predefined attack scenarios, failing to effectively evaluate the security of systems against emerging threats.
Innovation Solution
A system and method for adaptive cyber-attack emulation that uses a library of configurable attack-code templates to generate, apply, and adapt emulated attacks on a target computer system, learning from detection outcomes to evade detection and improve attack delivery, incorporating iterative processes that modify attack parameters, obfuscation schemes, and evasion techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional BAS tools use static lists of predefined attack scenarios, then the tools are easy to implement and execute, but they fail to assess resilience against new, unknown cyber threats
Solution Approach 1:
The system dynamically adapts attack scenarios based on outcomes from previous iterations. Instead of using static predefined attack lists, the system modifies attack parameters, techniques, and approaches in real-time based on what it learns about the target system's security controls, enabling assessment against unknown threats while maintaining manageable complexity through automated adaptation
Solution Approach 2:
The system implements feedback loops where outcomes from each attack emulation are analyzed and used to inform subsequent attack generations. The system learns from detection outcomes, evaluates which security controls were effective, and adjusts future attack scenarios accordingly, creating a continuous improvement cycle that enhances adaptability without requiring manual intervention
2Reliability
If the system applies iterative adaptation processes to learn from detection outcomes, then the ability to evade detection improves, but the time and computational resources required increase
Solution Approach 1:
The system performs preliminary actions by pre-generating multiple attack scenarios and preparing adaptation strategies in advance. By anticipating potential detection outcomes and pre-planning alternative approaches, the system reduces the time needed for iterative adaptation during actual execution, maintaining high effectiveness while minimizing time loss
Solution Approach 2:
The system skips unnecessary iterations by intelligently identifying when adaptation is needed and when it is not. By analyzing detection outcomes and directly applying learned insights to generate improved attack scenarios without redundant cycling, the system rushes through the adaptation process efficiently, maintaining reliability while reducing time consumption
Data Source
AI summary
A system for cyber-attack emulation includes a memory and one or more processors. The memory is configured to store a library of attack-code templates, each attack-code template including configurable program code that carries out a respective type of cyber-attack. The one or more processors are configured to specify an attack-emulation campaign based on one or more of the attack-code templates, and, for at least a given attack-code template included in the attack-emulation campaign, to perform an iterative process including (i) generating an emulated attack from the given attack-code template, (ii) applying the emulated attack to a component of a target computer system, (iii) evaluating an interim outcome of the emulated attack, and (iv) adapting the emulated attack depending on the interim outcome.