REPORT

The state of AI reverse engineering

Figures as of 31 October 2026 · 490 projects · updates as the directory grows

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 result works.

Summary

Key findings

  • 490 projects are recorded. 242 (49%) are reported as working, 168 as partial and 80 as research.
  • Games and mods make up 60% of the directory, followed by firmware and hardware at 16%.
  • Claude models appear in 403 of the 449 projects that name a model (90%), ahead of GPT / Codex with 56.
  • Among 295 games, static recompilation is the most common method (134), with 47% reported as working. 36 aim for a matching decompilation, where the rebuilt code compiles to the original bytes.
  • 33 projects (7%) connected the model to a tool through an MCP server. 65 used Ghidra and 4 used IDA.
  • Only 42 authors (9%) say how long the work took. Of those, 14 finished in under a day, 14 in a few days, 8 in weeks and 6 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 mods2951251363442%
Firmware and hardware775315969%
Apps38275671%
Research and benchmarks27711926%
APIs and protocols24165367%
File formats1191182%
Legacy software834138%
Malware (defensive)80170%
Websites2200100%
Models

Which models people use, and how often it works

449 of 490 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
Claude4032111454752%
GPT / Codex5620162036%
Gemini520340%
Open or local1341831%
Games

Games by method and platform

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

MethodProjectsWorksPartialResearchWorking share
Matching decompilation36821722%
Decompilation601734928%
Static recompilation13463591247%
Port or rebuild341713450%
Mod or tool15113173%
Original platform (5 or more games)ProjectsWorksPartialResearchWorking share
PC633322852%
PlayStation 234922326%
PlayStation251014140%
Nintendo 6423156265%
Xbox 36021109248%
GameCube1678144%
Nintendo Switch1549227%
Xbox1575347%
DOS and home computers1494164%
Nintendo DS121928%
Arcade871088%
Game Boy Advance816113%
SNES742157%
PSP614117%
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 Code13658%
Ghidra6439%
REA2152%
Codex CLI1553%
PS2Recomp922%
PSXRecomp863%
xboxrecomp743%
GhidraMCP560%
JADX475%
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
14
Days
14
Weeks
8
Months or more
6

Time reported by 42 projects. 5 report a dollar cost: median $21, highest $91.

Method

How these figures are made

  • Every live entry in the directory is counted, 490 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”, 31 October 2026, https://reversedwithai.com/state-of-ai-reverse-engineering. For a single project, cite its primary source.