Malware Analysis with Coverage-Guided Environmental Fuzzing
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Solution Overview
Problem
Existing malware analysis systems struggle to effectively detect and analyze environment-sensitive malware, which employs sophisticated evasion techniques to avoid detection by fingerprinting execution environments, leading to inconclusive or misleading results and requiring manual intervention.
Innovation Solution
A method and system that utilizes an execution monitor to interpose on program accesses to environmental information, record coverage information, and generate execution policies through fuzzing mutations to expose unseen behaviors and interactions with the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If malware analysis systems use traditional detection methods, then they can identify known malware patterns, but evasive malware with sophisticated fingerprinting techniques can avoid detection by adapting to the analysis environment
Solution Approach 1:
The system dynamically generates and modifies execution policies during malware analysis, transitioning from static detection rules to adaptive policy-based control. The execution monitor continuously observes malware behavior and adjusts policies in real-time, preventing evasive malware from successfully fingerprinting and adapting to the environment.
Solution Approach 2:
The system changes environmental parameters and execution conditions to observe how malware responds to different contexts. By varying execution parameters and monitoring coverage information, the system can identify environment-sensitive behaviors that indicate evasive or targeted malware without relying on fixed detection patterns.
2Productivity
If malware analysis systems increase automation to handle sophisticated evasion techniques, then analysis speed improves, but the complexity of the analysis system increases requiring more sophisticated tools and methods
Solution Approach 1:
The execution monitor serves as an intermediary layer between the malware and the analysis system, mediating all interactions through policy-based control. This intermediary manages the complexity by providing a standardized interface for observing and controlling malware execution, simplifying the overall system architecture while enabling sophisticated analysis capabilities.
Solution Approach 2:
The system implements continuous feedback loops where the execution monitor observes malware behavior, analyzes coverage information, and adjusts execution policies accordingly. This automated feedback mechanism enables the system to handle complex evasion techniques without manual intervention, maintaining high productivity while managing system complexity through self-regulation.
3Measurement precision
If malware analysis systems manually intervene to dissect environment-sensitive malware, then detection accuracy improves, but analysis time increases significantly
Solution Approach 1:
The execution monitor enables the malware analysis system to self-analyze environment-sensitive behaviors through automated policy execution and coverage tracking. The system serves itself by automatically identifying suspicious patterns and adjusting execution policies without requiring manual dissection, thereby maintaining high detection precision while eliminating time-consuming manual analysis.
4Loss of information
If malware analysis systems use coverage-guided fuzzing to explore execution paths, then unseen malware behaviors are exposed, but the computational resources and time required for analysis increase
Solution Approach 1:
The system applies partial fuzzing by focusing computational resources on specific execution paths and environmental parameters most likely to reveal environment-sensitive behaviors. Rather than exhaustively fuzzing all possible paths, the execution monitor identifies and targets critical coverage gaps, achieving effective malware analysis with reduced computational overhead and time investment.
Data Source
AI summary
The present invention concerns methods and systems for analyzing a software program as a potential environment-sensitive malware sample. The methods and systems described here may comprise monitoring access to environmental information, altering according to an execution policy the contents of environmental information items before retrieval by the program, recording as coverage information the internal states and the externally observable actions from the program execution, using recoded coverage information to generate in a fuzzing fashion execution policies with new contents for environmental information items, and identifying execution policies that induce previously unseen internal states and externally observable actions for the program.