DNS Resolution Metrics for Adversary Infrastructure Role Classification
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Solution Overview
Problem
Malicious software campaigns utilize dynamic infrastructure, such as domains and IP addresses, to evade detection and disrupt investigations, making it challenging to track and identify adversary networks effectively.
Innovation Solution
A system that collects and analyzes DNS resolution data to determine resolution metrics, including geographic locations and IP address usage patterns, to classify the role of adversary infrastructure and initiate remedy responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dynamic infrastructure is used by adversaries, then the survivability and mobility of malware are improved, but the ability to track and identify adversary networks deteriorates
Solution Approach 1:
The system performs preliminary analysis of DNS resolution data to establish baseline metrics and patterns before malicious activity fully develops. By pre-processing and pre-characterizing infrastructure data, the system creates a foundation for rapid detection and tracking of adversary networks using their own dynamic infrastructure.
Solution Approach 2:
The system implements continuous monitoring and feedback loops that track DNS resolution patterns over time. By analyzing recurring patterns, frequency of resolutions, and geographic distributions, the system adapts to adversary behavior changes and maintains tracking capability despite infrastructure dynamics.
2Adaptability or versatility
If dynamic domain infrastructure is used, then the mobility of malware is improved, but the traceability of adversary operations deteriorates
Solution Approach 1:
The system introduces DNS resolution metrics as an intermediary layer between the adversary's dynamic infrastructure and the tracking system. By measuring and characterizing DNS resolution patterns, the system creates a stable observational layer that preserves traceability information even as the underlying infrastructure changes.
Solution Approach 2:
The system characterizes different infrastructure roles by identifying distinctive patterns in DNS resolution data, effectively 'coloring' different infrastructure types with unique behavioral signatures. This allows differentiation between command and control infrastructure, parking domains, and other roles despite dynamic IP addresses and domain names.
3Device complexity
If infrastructure roles are not classified, then the complexity of response actions increases, but the precision of targeted responses decreases
Solution Approach 1:
The system segments adversary infrastructure into distinct roles (command and control, parking, data exfiltration, etc.) based on DNS resolution pattern analysis. By dividing the infrastructure into categorized segments, the system reduces the complexity of response actions while maintaining high precision in characterizing each infrastructure's specific function.
Data Source
AI summary
In some embodiments, an apparatus includes a memory and a processor operatively coupled to the memory. The processor is configured to receive a set of domain name resolutions associated with a domain. Each domain name resolution from the set of domain name resolutions includes a mapping between a domain name and an Internet Protocol (IP) address. The processor is then configured to determine, based on the set of domain name resolutions, a set of resolution metrics associated with a first geolocation and a set of resolution metrics associated with a second geolocation. The processor is also configured to compare and identify a role of an adversary infrastructure at the first geolocation and a role of an adversary infrastructure at the second geolocation, and subsequently send a signal such that a remedy response associated with at least one of the set of IP addresses or the domain name is initiated.