🔍 Read the full analysis: Could AI Help You Navigate Software You Didn’t Build? on ThorstenMeyerAI.com
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TL;DR
Reverse Engineer Anything (REA) is an open-source toolkit that connects coding agents to tools for examining existing programs. A case study described by ThorstenMeyerAI.com says an app built from research into QuickBooks Desktop matched selected financial reports to the cent; that result is a reported example, not proof that AI can reliably reproduce software in general.
Reverse Engineer Anything (REA), an open-source toolkit for AI coding agents, can help developers investigate how existing software behaves, according to a report published October 19 by ThorstenMeyerAI.com. The report points to a developer’s QuickBooks Desktop case study, in which a locally built accounting app reportedly matched selected financial statements from Intuit’s sample company to the cent—an example of what targeted software analysis may support, not evidence that an AI can automatically reproduce any program.
REA connects agents such as Claude Code, Codex, Cursor and Gemini CLI to analysis tools through the Model Context Protocol, or MCP. It also includes a command-line interface and an agent skill that guides an investigation. The project’s engines can examine several kinds of software and technical artifacts, including JavaScript and Electron apps, .NET and Android programs, firmware, databases, saved network traffic and native binaries. For websites, the report says, it can observe behavior in a Chrome-family browser controlled by the user.
The account described in the report involved QuickBooks Desktop for Mac 2024. The case-study author used REA 6.4.0 and Ghidra to investigate selected accounting behaviors, including inventory calculations, budget sign conventions, reconciliation balances and cash-basis report logic. The resulting project, Ledger Reborn, reportedly produced a profit-and-loss statement, balance sheet and trial balance for QuickBooks’ official sample company that matched the original account by account, to the cent. The available source excerpt does not provide an independent audit of that comparison.
The report describes REA as local analysis software, but says findings are passed to the connected AI agent and may also be sent to its model provider under that provider’s data policy. It identifies version 6.7.0, released October 18, and says the project is MIT-licensed and hosted on GitHub. It also warns that REA is not a sandbox: analysis tools run with the user’s permissions, so unknown programs should be treated as untrusted files.
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.
Powered by Thorsten Meyer AI
From Software Behavior to Specifications
For developers working with software they did not create, the hard part is often not reproducing its screens but understanding the rules behind them. A payment feature, for example, may depend on stored records, calculations and conditions that are not visible in the interface. REA’s proposed value is to give an agent tools to investigate a specific behavior and help turn observations into a specification a developer can test.
That approach could matter when replacing a legacy system, building an integration or checking how a business process is represented in existing software. But the QuickBooks result is one reported project, involving a defined set of accounting outputs and a sample company. It does not establish that the recreated application matches every feature, edge case or future update of QuickBooks. For readers considering this workflow, the key distinction is between evidence about a bounded behavior and a broad claim that an agent understands an entire product.
software reverse engineering tools
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How REA Fits Into Agent Workflows
The source report argues that open-ended requests such as “figure out how this program works” are difficult to verify. It recommends asking about one behavior tied to a practical decision, then asking the agent to report what data is stored, how a result is calculated and which conditions change it. A useful check, the report says, is whether the agent can explain a concrete example using real inputs and outputs rather than merely describing what appears on screen.
Setup is another point of failure. The report says REA’s guided installer supports Claude Code, Codex and other agents, and that it requires Node.js 22.19 or newer. Native analysis may also require a disassembler such as Ghidra, which requires Java, or a licensed tool such as Hopper or IDA. Its diagnostic command checks installed files and prerequisites, but the report cautions that this does not confirm the agent’s live connection. Developers should check that the agent actually calls an REA tool before relying on answers as observations.
““This is not a sandbox.””
— REA project documentation, as quoted in the ThorstenMeyerAI.com report
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Limits, Security and Verification
The source describes a single case study and does not supply independent testing, a complete account of the methods used to compare the financial statements, or results across a wider set of programs. It is also unclear from the provided material how much of Ledger Reborn’s behavior was validated beyond the three named reports, or how its performance would compare across different versions, configurations or unusual transactions. The reported match should be read as a result for the specified sample company and outputs, not a general guarantee.
Security and privacy depend on how REA is used and which agent or model provider is connected. The report says analysis happens locally, while results go to the agent and potentially its provider; it does not detail the data policies of each provider. It also does not establish whether every supported analysis engine can safely handle every target. Users need to verify the agent’s observations against concrete tests and avoid opening untrusted programs on systems where they have sensitive access.
open-source software investigation toolkit
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Testing a Bounded Investigation
The report’s practical next step is to connect an agent, verify the connection, and begin with a harmless application the user owns. A developer can then ask one focused question, request a worked example and label findings as observed, inferred or unknown. That process makes it easier to identify guesses and decide when the investigation has answered the original design question.
No broader benchmark, independent replication or future product milestone is identified in the supplied material. Developers interested in REA will need to consult the project’s current documentation for version-specific setup details, and treat results as hypotheses until they have been checked against the original program. Whether the approach saves time or produces reliable specifications across more complex applications remains to be established through further testing.
Ghidra reverse engineering software
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Key Questions
What does REA do?
REA is an open-source toolkit that lets compatible AI coding agents call software-analysis tools. It can support investigations into specific behaviors in existing applications and other technical files.
Did the QuickBooks project reproduce all of QuickBooks?
No such conclusion is supported by the source. It reports that Ledger Reborn matched a profit-and-loss statement, balance sheet and trial balance for QuickBooks’ official sample company, to the cent. It does not establish a match across every feature or case.
Does REA send software or results to an AI provider?
The report says REA performs analysis locally, but the connected agent receives results, and the model provider may receive them under its own data policy. The report does not specify the policies for every provider, so users should check the terms of the service they use.
Is REA safe to use with an unknown program?
The project documentation quoted in the report says REA is not a sandbox. Its tools run with the user’s permissions, so unknown programs should be treated as untrusted files and handled with suitable security precautions.
Source: ThorstenMeyerAI.com
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