Leveraging Artificial Intelligence for Automated Reverse Engineering of Legacy Software Systems

We present an AI-assisted reverse engineering framework that achieves dramatic speedups—on the order of hundreds of times faster than traditional manual methods—by orchestrating specialized agents for evidence curation, struct recovery, and code drafting. Using this approach, we recreated a bootable prototype of Apple System 7.1 from binary analysis in just 3 days, a task that would normally require months or years. The framework enforces strict provenance tracking, tying each change to either disassembly bytes or runtime verification under QEMU. Rather than reporting abstract accuracy percentages, we emphasize artifact-based validation: screenshots, serial logs, and resource extractions that demonstrate Chicago font rendering, menu bar behavior, desktop patterns, and icon display. This work shows how carefully scoped AI assistance, coupled with human review and a structured verification loop, can transform reverse engineering from a slow artisanal process into a systematic, reproducible workflow for preserving computing history and modernizing legacy systems.