Analysis of High Level Intermediate Representation in a Distributed Environment for Large Scale Malware Processing

Explore a conference talk on distributed reverse engineering techniques for large-scale malware analysis. Delve into the use of intermediate representation in clustered environments to identify algorithmic commonalities between malware families. Learn about the analysis of a dataset containing 2 million malware samples using data mining and machine learning tools. Discover how higher-level abstractions of malware code are constructed from abstract syntax trees to extract characteristics like object-oriented types, domain generation algorithms, and custom encryption. Gain insights into the researchers' findings and access the gathered representation, raw sample information, and analysis tools made available on Github for further exploration and development in the field of malware analysis.