🔍 Read the full analysis: AI And Reverse Engineering: Finding Your Way Into A Codebase on ThorstenMeyerAI.com
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TL;DR
A source article published by Thorsten Meyer on October 19, 2026, describes Reverse Engineer Anything (REA), an open-source toolkit that lets AI coding agents inspect existing software through analysis tools. A QuickBooks Desktop case study reported that an independently built accounting app matched several financial statements from Intuit’s sample company account by account, to the cent; that result is a claim from the case study, not an independently verified finding in the supplied material.
A report published by Thorsten Meyer on October 19, 2026, describes how Reverse Engineer Anything (REA), an open-source toolkit, can help AI coding agents inspect existing software and document how particular behaviors work. The report’s central example is Ledger Reborn, a locally built accounting app whose author says its financial statements matched those produced by QuickBooks Desktop for Intuit’s sample company, account by account and to the cent.
REA connects coding agents such as Claude Code, Codex, Cursor and Gemini CLI to software-analysis tools. The source describes three parts: a local Model Context Protocol (MCP) server that agents can call, a command-line interface for setup and analysis, and an agent skill that guides investigations. Its analysis options cover native applications, JavaScript and Electron apps, .NET and Android software, firmware, saved network traffic, WebAssembly, SQLite databases and older DOS programs. For websites, it can observe activity in a browser controlled by the user.
The report argues that an investigation should focus on a specific behavior and the design decision it informs, rather than asking an agent to explain an entire program. A useful inquiry might ask how a partial invoice payment affects the remaining balance and which account receives the posting. The agent should identify stored data, calculations and conditions that change the result, while labeling findings as observed, inferred or unknown. A concrete example with inputs and outputs can help reveal whether the investigation reached the underlying behavior or only described the interface.
In the Ledger Reborn example, the author says the investigation examined inventory calculations, budget signs by account type, reconciliation balances and cash-basis report logic in QuickBooks Desktop for Mac 2024. The case study used REA version 6.4.0 and Ghidra, according to Meyer. The source says the project’s profit-and-loss statement, balance sheet and trial balance matched QuickBooks’ official sample-company results. The supplied material does not include the underlying test data or an independent replication.
Infographic 01 · Reverse Engineer Anything
Five places to point REA first, and how to tell when the answer is wrong.
REA gives coding agents such as Claude Code and Codex tools to inspect programs, apps and browser sessions. Each investigation needs a finishable question and a check.
npx rea-agents@latest setupThe five investigations
What to ask, and the check that catches a wrong answer.
- 1
Ask a question you can finish
One behaviour, one decision it informs. Example: how a partial payment changes an invoice balance.
It’s wrong ifThe agent can't walk through one concrete example with real inputs and outputs. - 2
Get REA connected and confirmed
Run the guided setup, then doctor, then call binary_session inside the agent before any real target.
It’s wrong ifAnswers arrive without a single REA tool call: you're reading the model's guesses. - 3
Turn a business rule into a spec
Inputs, stored fields, formula, edge cases, plus test cases checked against the original's own output.
It’s wrong ifYour version and the original disagree on a test case, even by one cent. - 4
See what has to survive a copy
Find what an app writes to the clipboard and what it keeps locally, then design your own copy and paste.
It’s wrong ifThe explanation doesn't predict what lands in a plain text editor, an email and your app. - 5
Your own app, your equipment, an old program
Start with software you own or rely on. Ask what it sends, stores or calculates when you do one thing.
It’s wrong ifIt only works for the example you watched. Test with a new file or a read-only command first.
Sources: REA on GitHub (stars via GitHub API, 19 Oct 2026); REA installation guide; REA security policy.
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From Software Behavior to App Specs
For developers, the reported approach addresses a gap between reproducing a familiar screen and building software that behaves consistently when records change. An interface may show an invoice balance, for example, without revealing how partial payments, account selection or reporting rules produce that number. Documenting those rules can give an AI coding agent a more testable specification for a replacement or companion app.
The QuickBooks comparison is relevant because accounting results depend on linked calculations and business rules, not just visual similarity. If independently checked, matching statements could provide evidence that the new app reproduces some of the tested behaviors. It would not, on its own, establish that every QuickBooks feature, workflow or edge case has been recreated. Meyer’s report presents the project as an example of a method, rather than proof that AI agents can reliably reverse engineer any application.
REA’s local analysis setup may also matter to teams examining software they are authorized to inspect. However, the report says analysis results are passed to the AI agent and then to its model provider, subject to that provider’s data policy. Local processing of the target does not mean the entire workflow stays on the user’s machine.
software reverse engineering tools
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How REA Fits Into Agent Workflows
REA is described in the source as an MIT-licensed project on GitHub, maintained by an anonymous maintainer. Meyer reports that it had about 325,000 stars and 82,000 forks on October 19, following a period on GitHub’s trending page earlier in the month. Those figures are a snapshot reported by the source, not an independent measure of adoption or product performance. Version 6.7.0 was released October 18, according to the article.
The source says setup can be run with a guided installer and that REA requires Node.js 22.19 or newer. Native-program analysis may also require a disassembler such as Ghidra, which requires Java, or a licensed tool such as Hopper or IDA. Meyer recommends checking that setup files and prerequisites are present, then confirming inside the coding agent that REA tools are actually available. The article cautions that a setup diagnostic checks files and prerequisites but does not verify the live agent connection.
The distinction matters because an agent can produce plausible explanations without consulting the analysis tools. Meyer’s suggested check is to ask the agent to call REA’s session tool before opening a target. If the agent answers questions about a program without making an REA tool call, the response may be based on the model’s prior knowledge or guesses rather than evidence gathered from the software.
“This is not a sandbox.”
— Reverse Engineer Anything project, as quoted in Meyer’s report
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Limits of the QuickBooks Comparison
The supplied report does not provide the full case-study text, detailed test procedures, inputs, screenshots or datasets needed to independently assess the claimed account-by-account match. It also does not establish how many QuickBooks workflows were tested, which edge cases were excluded, or whether another researcher reproduced the results. The reported agreement applies to the statements and sample company described by Meyer; it should not be read as confirmation that Ledger Reborn fully duplicates QuickBooks.
REA’s popularity figures, supported software list and version details are also reported by Meyer and are not independently verified in the supplied material. The source names several supported analysis engines but does not specify compatibility limits for every target or agent. Its safety warning and data-sharing caveat mean users must assess both the software they inspect and the policies of the AI provider receiving analysis results.
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Verify Tools Before Investigating
The practical next step in Meyer’s account is to confirm the agent connection, inspect a harmless application the user owns, and then ask a narrowly framed question with a decision in view. For each finding, the agent should distinguish direct observations from inferences and unknowns, and explain one complete example with real inputs and outputs. These checks can help users catch answers based on guesswork before using them to guide implementation.
The source does not announce a new release beyond version 6.7.0 or identify a forthcoming independent evaluation of Ledger Reborn. Further evidence would require access to the full case study, its test materials and a repeatable comparison against QuickBooks outputs. Until then, the project is a reported example of AI-assisted reverse engineering, not an independently established measure of REA’s accuracy across software.
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Key Questions
What is Reverse Engineer Anything?
REA is an open-source toolkit that connects AI coding agents to analysis tools for investigating existing software. Meyer describes it as an MCP server, a command-line tool and an agent skill.
Did Ledger Reborn reproduce all of QuickBooks?
The report says Ledger Reborn’s profit-and-loss statement, balance sheet and trial balance matched results for Intuit’s sample company, account by account and to the cent. It does not show that every QuickBooks feature or edge case was reproduced.
Does REA keep all analysis data on the user’s computer?
The source says REA analyzes targets locally, but results are sent to the coding agent and the model provider under that provider’s data policy. Local analysis does not mean the full workflow stays local.
Can REA safely inspect any program?
No. The project warns that REA is not a sandbox and that its tools run with the user’s permissions. The report advises treating unknown binaries as untrusted files and inspecting only software the user is authorized to examine.
Source: ThorstenMeyerAI.com
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