# SoK: AI-Augmented Binary Reversing

> A systematization-of-knowledge survey of machine-learning, LLM and agentic approaches to binary reversing. Version 2 collects 246 papers published since 2015, found through keyword searches of 11 security, software-engineering and AI venues plus citation snowballing, and organizes them into 22 domains by inference task: from code-boundary detection and recovery of function names, types and struct layouts to code similarity, malware and vulnerability analysis, and decompilation. Its taxonomy links conventional triage, static, dynamic and security-testing analyses to AI pipelines through the binary-derived artifacts they exchange, and it derives 12 insights and open directions such as binary-aligned ground truth and goal-driven agentic reversing.

- Authors: Yujeong Kwon; Yiyue Zhang; Kexin Pei; Dokyung Song; Hyungjoon Koo
- Venue: arXiv
- Status: Preprint
- Publication / posting date: June 16, 2026
- Date source: arXiv v1 submission; the reviewed v2 revision of 2026-09-04 does not change the first-submission date.
- First arXiv submission: June 16, 2026
- arXiv: 2606.17398
- Reviewed arXiv version: v2
- Sources reviewed: 2026-10-18
- Added to the catalog: 2026-10-19
- Original paper: <https://arxiv.org/abs/2606.17398>
- PDF: <https://arxiv.org/pdf/2606.17398v2>
- Project: <https://sok-aire.vercel.app>
- BibTeX: <https://awesomerea.org/papers/citations/paper-sok-ai-binary-reversing.bib>
- Catalog page: <https://awesomerea.org/papers/paper-sok-ai-binary-reversing/>
- Record JSON: <https://awesomerea.org/papers/paper-sok-ai-binary-reversing/record.json>
- Chinese version: [简体中文](https://awesomerea.org/zh/papers/paper-sok-ai-binary-reversing/index.md)

## Scope and limitations

A literature systematization with no new experiments, benchmark or tool; it classifies and summarizes reported results without reproducing them. The corpus covers papers available up to July 31, 2026, applies citation thresholds that fall from 12 for 2015–2016 papers to 2 for 2025–2026 papers, excludes methods that need source code at inference time, and leaves out Android and interpreted-language bytecode. Detailed per-stage tables draw on 88 top-venue studies rather than the full corpus. It is an arXiv preprint with no stated venue.

## Why it fits this collection

Provides a structured map of ML, LLM and agent research across binary reversing tasks, helping place the collection’s binary-analysis papers and locate related work that still needs individual review.

## Publication and review notes

Reviewed arXiv v2 (2026-09-04; comment “21 pages, 7 tables, 4 figures”), which lists five authors and 246 papers; this record follows the v2 author list. v1 (2026-06-16; “20 pages, 7 tables, 3 figures”) listed six authors, Yujeong Kwon, Yiyue Zhang, Shakhzod Yuldoshkhujaev, Kexin Pei, Dokyung Song and Hyungjoon Koo, and analyzed 144 papers published between 2015 and 2025. Neither version states a venue or journal reference. Footnote 1 in both versions links the companion site, an interactive JavaScript table of the surveyed papers grouped by domain with links to their publications; no source repository is linked. The site and its paper list may change after this review.

## Primary sources

1. <https://arxiv.org/abs/2606.17398v2>
2. <https://arxiv.org/pdf/2606.17398v2>
3. <https://arxiv.org/abs/2606.17398v1>
4. <https://arxiv.org/pdf/2606.17398v1>
5. <https://sok-aire.vercel.app>

## About this entry

Reviewed against the paper and its primary sources. Cite the original authors using the linked paper or BibTeX.
Original editorial content: MIT. Linked projects, papers and assets retain their own rights and licenses.