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State of AI reverse engineering — 2026-11-05

Reversed with AI's 5 November 2026 snapshot of its directory records 502 AI-assisted reverse engineering projects, of which 253 (50%) are reported as working, 168 as partial and 81 as research. Claude models appear in 418 of the 464 projects that name a model (90%), ahead of GPT / Codex at 56, and games and mods make up 60% of the directory, followed by firmware and hardware at 16%. Among 300 games, 137 use static recompilation with 46% reported as working, while 35 projects (7%) connected a model to a tool through an MCP server, 67 used Ghidra and 4 used IDA.

read6 min views1 publishedNov 5, 2026
State of AI reverse engineering — 2026-11-05
Image: Reversedwithai (auto-discovered)

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.

Download, cite and reuse #

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

[View current figures](https://reversedwithai.com/state-of-ai-reverse-engineering)

Charts to share

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.

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.

Target Projects Works Partial Research Working share
Games and mods 300 128 137 35 43%
Firmware and hardware 81 57 15 9 70%
Apps 42 32 4 6 76%
Research and benchmarks 27 7 1 19 26%
APIs and protocols 24 16 5 3 67%
File formats 11 9 1 1 82%
Malware (defensive) 8 0 1 7 0%
Legacy software 7 2 4 1 29%
Websites 2 2 0 0 100%

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 family Projects Works Partial Research Working share
Claude 418 221 146 51 53%
GPT / Codex 56 20 16 20 36%
Open or local 13 4 1 8 31%
Gemini 5 2 0 3 40%

Games by method and platform #

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

Method Projects Works Partial Research Working share
Matching decompilation 35 9 20 6 26%
Decompilation 59 16 34 9 27%
Static recompilation 137 63 60 14 46%
Port or rebuild 36 18 14 4 50%
Mod or tool 17 13 3 1 76%
Original platform (5 or more games) Projects Works Partial Research Working share
PC 65 33 23 9 51%
PlayStation 2 32 7 22 3 22%
Nintendo 64 25 18 6 1 72%
PlayStation 25 10 14 1 40%
Xbox 360 21 10 9 2 48%
GameCube 17 8 8 1 47%
Nintendo Switch 17 4 10 3 24%
DOS and home computers 15 9 5 1 60%
Xbox 15 7 5 3 47%
Nintendo DS 11 1 8 2 9%
Arcade 9 7 2 0 78%
Game Boy Advance 8 1 6 1 13%
Dreamcast 6 4 1 1 67%
PSP 6 1 4 1 17%
SNES 6 3 2 1 50%

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.

Tool Projects Working share
Claude Code 140 58%
Ghidra 65 38%
REA 22 55%
Codex CLI 15 53%
PS2Recomp 9 22%
PSXRecomp 8 63%
xboxrecomp 7 43%
GhidraMCP 5 60%
JADX 5 80%

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.

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.

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