REPORT

The state of AI reverse engineering

Snapshot captured 5 November 2026 · 502 projects · preserved release

People now use AI models to decompile games, read firmware, decode protocols and port old software. This report counts what the Reversed with AI directory records about that work: what gets reverse engineered, with which models and tools, and how often the author reports a working result.

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This release preserves the directory at capture time. Counts describe public documented projects and author-reported outcomes; they are not model benchmarks or independent tests.

Only these aggregate statistics and charts: CC BY 4.0. Credit Reversed with AI and link to this release. This licence does not cover the catalogue, project-level records or other site content. Linked sources retain their own licences.

Reversed with AI. The state of AI reverse engineering. 2026-11-05. https://reversedwithai.com/state-of-ai-reverse-engineering/releases/2026-11-05

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Projects by target
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Reported outcomes
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Model families (overlapping)
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Summary

Key findings

  • 502 projects are recorded. 253 (50%) are reported as working, 168 as partial and 81 as research.
  • Games and mods make up 60% of the directory, followed by firmware and hardware at 16%.
  • Claude models appear in 418 of the 464 projects that name a model (90%), ahead of GPT / Codex with 56.
  • Among 300 games, 137 use static recompilation, with 46% reported as working. 35 aim for a matching decompilation, where the rebuilt code compiles to the original bytes.
  • 35 projects (7%) connected the model to a tool through an MCP server. 67 used Ghidra and 4 used IDA.
  • Only 43 authors (9%) say how long the work took. Of those, 13 finished in under a day, 14 in a few days, 9 in weeks and 7 took months or more.
Targets

What people reverse engineer with AI

Projects by the kind of target. The working share is the part the author reports as doing what it set out to do.

TargetProjectsWorksPartialResearchWorking share
Games and mods3001281373543%
Firmware and hardware815715970%
Apps42324676%
Research and benchmarks27711926%
APIs and protocols24165367%
File formats1191182%
Malware (defensive)80170%
Legacy software724129%
Websites2200100%
Models

Which models people use, and how often it works

464 of 502 projects name the model they used. A project that used more than one family counts once in each. Version-level figures and benchmark results are on the model leaderboard.

Model familyProjectsWorksPartialResearchWorking share
Claude4182211465153%
GPT / Codex5620162036%
Open or local1341831%
Gemini520340%
Games

Games by method and platform

Method and original platform are read from each entry; the full list is on AI game decompilation.

MethodProjectsWorksPartialResearchWorking share
Matching decompilation35920626%
Decompilation591634927%
Static recompilation13763601446%
Port or rebuild361814450%
Mod or tool17133176%
Original platform (5 or more games)ProjectsWorksPartialResearchWorking share
PC653323951%
PlayStation 232722322%
Nintendo 6425186172%
PlayStation251014140%
Xbox 36021109248%
GameCube1788147%
Nintendo Switch17410324%
DOS and home computers1595160%
Xbox1575347%
Nintendo DS111829%
Arcade972078%
Game Boy Advance816113%
Dreamcast641167%
PSP614117%
SNES632150%
Tools

The tools around the model

The reverse engineering tools and agents projects name most often. General build tools and libraries are left out. Each tool has its own page in the tools directory.

ToolProjectsWorking share
Claude Code14058%
Ghidra6538%
REA2255%
Codex CLI1553%
PS2Recomp922%
PSXRecomp863%
xboxrecomp743%
GhidraMCP560%
JADX580%
Effort

Time and cost

Most authors don't say how long the work took or what it cost, so these figures cover only those who did. They are the authors' own numbers and are not measured by this site.

Under a day
13
Days
14
Weeks
9
Months or more
7

Time reported by 43 projects. 5 report a dollar cost: median $21, highest $91.

Method

How these figures are made

  • Every live entry in the directory is counted, 502 at the date above. Each links to its primary source.
  • Outcome, model, tools, time and cost are what the entry records from the author's repo, write-up or post. The site does not rerun the work.
  • The directory covers public, documented projects, so it leans toward work people chose to share. It is not a random sample.
  • Game platform and method are matched from each entry's target, title and write-up, and a few games are hard to classify.

To cite: Reversed with AI, “The state of AI reverse engineering”, 5 November 2026, https://reversedwithai.com/state-of-ai-reverse-engineering/releases/2026-11-05. For a single project, cite its primary source.