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Gemini LLM extracts opcode tables for disassembling undocumented architectures

A new method uses the Gemini LLM to extract opcode tables for disassembling undocumented CPU architectures, overcoming limitations of traditional tools like Ghidra and dis51. This approach prompts the LLM to reconstruct, normalize, and export instruction mappings into a Python structure, which then powers a lightweight linear sweep disassembler. The process decouples data extraction from execution logic, enabling faster and more accurate disassembly of legacy or modified systems. AI

IMPACT Enables faster and more accurate disassembly of legacy or modified CPU architectures, potentially aiding in software archaeology and security research.

RANK_REASON Article presents a novel methodology for reverse engineering using an LLM. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Gemini LLM extracts opcode tables for disassembling undocumented architectures

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36 / 100
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Article presents a novel methodology for reverse engineering using an LLM. [lever_c_demoted from research: ic=1 ai=1.0]
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product, infra
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High
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · ddupard ·

    Reverse Engineering Undocumented Architectures: LLM-Driven Opcode Table Extraction vs. Legacy Tooling Constraints

    <h2> Executive Summary </h2> <p>When building a custom disassembler for an undocumented, legacy, or modified CPU architecture, the primary challenge is not writing the decoding loop, but obtaining a structured, machine-readable <strong>opcode-to-instruction mapping table</strong>…