Dynamic Malware Analysis Using Instrumented Virtual Machine Time Allocation
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Solution Overview
Problem
Current approaches to dynamic malware analysis in instrumented virtual machine environments are inefficient in terms of computing resources and time allocation, often failing to detect malware effectively due to fixed analysis times and inability to simulate realistic user interactions, which allows advanced threats to evade detection.
Innovation Solution
Implementing a dynamic time allocator and browser helper objects within the instrumented virtual machine environment to dynamically adjust analysis time based on URL content, including modifying timeout and refresh delays, and simulating user interactions to enhance malware detection efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed analysis time is allocated for malware detection, then the analysis process is simple to manage, but malware detection accuracy deteriorates due to insufficient time for complex URL analyses
Solution Approach 1:
The patent implements a dynamic time allocation mechanism that adjusts the analysis time period based on the specific characteristics of each URL sample. The system determines whether to allocate a first time period or a second time period (where the second period is longer than the first) based on factors such as URL complexity and detected behavior patterns, thereby optimizing detection accuracy without requiring overly complex fixed-time management structures.
Solution Approach 2:
The system changes the time parameter dynamically based on the analysis needs. By modifying the analysis time period from a fixed value to a variable that can be adjusted based on URL characteristics and detected behaviors, the system achieves both improved detection accuracy and manageable complexity through structured parameter adaptation.
2Measurement precision
If a longer analysis time is allocated to ensure detection accuracy, then malware detection accuracy improves, but computing resource efficiency deteriorates due to resource wastage on simple URLs
Solution Approach 1:
The patent employs dynamic time allocation that adapts to each URL sample's characteristics. Simple URLs receive a shorter first time period, while complex URLs that require deeper analysis receive a longer second time period. This dynamic adjustment ensures that computing resources are not wasted on simple cases while maintaining sufficient analysis time for complex malware detection scenarios.
Solution Approach 2:
The system changes the analysis time parameter based on the complexity assessment of each URL. By implementing parameter changes that align time allocation with actual analysis needs, the system optimizes the balance between detection accuracy and resource efficiency, avoiding both under-analysis and resource wastage.
3Reliability
If traditional detection methods are used, then the detection process is fast and resource-efficient, but advanced threats deteriorate detection effectiveness by evading traditional methods
Solution Approach 1:
The patent implements preliminary actions by executing the URL sample in a controlled virtual machine environment before committing to full analysis. The system performs initial assessments, modifies timeout and refresh delays proactively, and simulates user interactions in advance to trigger malware behaviors earlier, thereby improving detection effectiveness without excessive time consumption.
Solution Approach 2:
The system introduces a virtual machine environment as an intermediary between the URL sample and the analysis system. This intermediary allows for controlled execution, modification of URL behaviors (such as adjusting timeout delays), and simulation of user interactions, enabling more effective detection of advanced threats while managing analysis time through structured intervention.
Data Source
AI summary
Various techniques for performing malware analysis of a URL (e.g., a URL sample) using a browser executed in an instrumented virtual machine environment are disclosed. In some embodiments, a system for performing dynamic malware analysis of a URL using a browser executed in an instrumented virtual machine environment includes the instrumented virtual machine environment executed on a processor that receives a URL sample for dynamic malware analysis using the browser executed in the instrumented virtual machine environment; and a dynamic time allocator executed on the processor that dynamically determines a period of time allocated for performing the dynamic malware analysis of the URL sample using the browser executed in the instrumented virtual machine environment, in which the URL sample is rendered using the browser executed in the instrumented virtual machine environment and monitored using the instrumented virtual machine environment for the period of time allocated for performing the dynamic malware analysis of the URL sample.