Mitigating Distribution Shift in Graph-Based Android Malware Classification Via Function Metadata and LLM Embeddings

Graph-based malware classifiers can achieve over 94% accuracy on standard Android datasets, yet we find they suffer accuracy drops of up to 45% when evaluated on previously unseen malware variants from the same family - a scenario where strong generalization would typically be expected. This...

FLARE Script Series: Reverse Engineering WebAssembly Modules Using the idawasm IDA Pro Plugin

Introduction This post continues the FireEye Labs Advanced Reverse Engineering FLARE script series. Here, we introduce idawasm, an IDA Pro plugin that provides a loader and processor modules for WebAssembly modules. idawasm works on all operating systems supported by IDA Pro, and can be obtained...