Burnyard: Future of Malware Analysis

2026-06-23

AI Summary

This work addresses the limitations of traditional sandboxing approaches—namely high resource overhead, prolonged analysis time, and risks of sample leakage—by proposing a lightweight binary emulation framework. Instead of relying on heavyweight virtual machines, the system employs instruction-level emulation to safely execute suspicious binaries within a strongly isolated environment, capturing their runtime behaviors and exporting them as structured CSV event traces. This approach substantially reduces computational resource consumption, eliminates exposure of malicious samples to host systems, and enables efficient, scalable dynamic malware analysis suitable for large-scale deployment scenarios.

Abstract

Malware analysis is a critical aspect of modern cybersecurity. The prevailing industry practice, sandboxing, involves executing suspicious binaries within isolated virtual machines in large-scale data centers. However, this approach can unintentionally expose samples to public platforms such as VirusTotal and MalwareBazaar, and it is both resource-intensive and time-consuming. Burnyard addresses these limitations through a lightweight binary emulation platform that captures observable runtime behavior and records it as structured CSV event traces.

Problem

• malware analysis
• sandboxing
• resource-intensive
• public exposure
• runtime behavior

Innovation

• lightweight binary emulation
• malware analysis
• structured event tracing
• sandbox alternative
• runtime behavior capture