🔍 Read the full analysis: Can You Use AI To Understand An App You Didn’t Create? on ThorstenMeyerAI.com
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TL;DR
Reverse Engineer Anything, or REA, is an open-source toolkit that lets AI coding agents inspect existing programs and trace specific behaviors. A developer’s reported QuickBooks Desktop project shows how that work can inform a replacement app, but the result depends on human verification, and REA is not a security sandbox.
An open-source toolkit called Reverse Engineer Anything (REA) is giving coding agents a way to inspect existing programs and trace how specific features work, according to a report published Oct. 19. The report points to a developer’s QuickBooks Desktop case study, in which a locally built accounting app reportedly matched selected reports from Intuit’s sample company account by account, to the cent.
REA connects tools for software analysis to agents such as Claude Code, Codex, Cursor and Gemini CLI. The project includes a local Model Context Protocol server, a command-line utility and an agent skill that guides investigations. Its listed analysis targets include JavaScript and Electron applications, .NET and Android apps, firmware, databases, WebAssembly and native programs analyzed with tools such as Ghidra, Hopper or IDA.
The report says a developer used REA 6.4.0 and Ghidra to investigate QuickBooks Desktop for Mac 2024, focusing on inventory arithmetic, budget signs, reconciliation balances and cash-basis report logic. The developer then created Ledger Reborn, a local accounting app. According to the report, its profit-and-loss statement, balance sheet and trial balance matched those for Intuit’s official sample company. That is a reported result from a particular test, not an independent assessment of the replacement app or proof that it reproduces every QuickBooks feature.
REA’s current version is listed as 6.7.0, released Oct. 18. The source report describes the project as MIT-licensed and says its setup tool can configure supported agents. It recommends checking that setup completed and confirming the agent actually calls REA tools; an answer generated without those calls may be a model’s guess rather than an analysis of the target program.
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 Build Decisions
The approach matters to developers who need to understand software they did not write before replacing a feature, integrating with it or documenting its behavior. Instead of asking an agent to broadly “figure out” an application, a developer can ask about one decision-relevant behavior: for example, how a partial invoice payment changes a balance and which accounts receive entries. A useful investigation should identify stored data, calculations and conditions, then show a concrete example.
That can help turn familiar but undocumented behavior into a specification for a new system. The QuickBooks example illustrates the potential: accounting output can be compared against a known sample, giving the developer a way to test whether selected rules have been reproduced. But matching a handful of reports does not establish full compatibility, correctness across all cases or suitability for business use. The report supplies a case study, not a controlled evaluation of REA’s accuracy.
There is also a privacy and security trade-off. REA performs analysis locally, but its report says results are sent to the connected AI agent and may then be handled by the model provider under that provider’s data policy. The project explicitly says it is not a sandbox: opening an untrusted program exposes it to analysis tools running with the user’s permissions. Developers must consider both where analysis results go and whether the target file is safe to inspect.
software reverse engineering tools
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How REA Guides a Narrow Investigation
REA is designed to give coding agents access to analysis utilities, rather than to make a general-purpose chatbot automatically know how an application works. The report’s recommended workflow begins with a bounded question tied to a decision. An investigator then asks the agent to separate what it directly observed from what it inferred or could not establish, and to stop after explaining one complete example.
Installation alone does not prove the connection is working. The project’s diagnostic command checks setup files and prerequisites, but the documentation says it does not verify a live agent connection. The report advises confirming tool availability within the agent and trying a harmless program the user owns before examining a more complex target. Native program analysis may also require separate software, such as Ghidra and Java, or licensed disassemblers.
The report says REA drew attention on GitHub in early October and had about 325,000 stars and 82,000 forks as of Oct. 19. Those figures describe activity on the project page; the source provides no baseline or comparison period for interpreting them. Its maintainer is described as anonymous.
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Limits of the QuickBooks Test
The published account does not establish whether Ledger Reborn matches QuickBooks across transactions, company configurations or reporting situations beyond the sample company and reports described. It also does not provide an independent replication, detailed test protocol or a broader accuracy evaluation of REA. The reported match is evidence about that project’s stated test, not a guarantee that another agent or target will produce reliable findings.
It remains unclear how often REA’s analysis produces incomplete or mistaken explanations, and how much expertise is needed to detect those problems. The report’s proposed check is practical: require the agent to walk through a concrete input and output, and distinguish observed facts from inference and unknowns. A screen-level description alone does not show that the underlying mechanism has been found.
Data handling depends in part on the connected model provider, according to the report, and the source does not spell out the policies of each provider or each agent configuration. The safety of a target file also depends on the analysis environment; REA’s local operation should not be mistaken for isolation from the user’s machine.
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Verify Tools Before Trusting Findings
Developers considering REA can start by checking its current documentation and requirements, installing it for their chosen agent, and confirming that the agent can call the analysis tools. The report identifies Node.js 22.19 or newer as a requirement and says native analysis may need additional disassembly software. A first test on a harmless program the developer owns can help separate setup problems from analysis results.
For an actual investigation, the next step is to choose one behavior and a decision it informs, then ask for the relevant data, calculation and conditions with a worked example. Developers should validate the explanation against known outputs or other evidence and keep unconfirmed conclusions labeled as such. The source report does not announce a new release beyond version 6.7.0 or provide a timeline for further evaluations; the reliability and breadth of results remain matters for testing.
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Key Questions
What is Reverse Engineer Anything?
REA is an open-source toolkit that connects coding agents to software-analysis tools. It includes a local MCP server, a command-line tool and guidance for running investigations.
Can REA explain any app automatically?
No such capability is established by the source report. REA supports different kinds of targets, but a useful result depends on selecting a specific behavior, having the necessary analysis tools and checking the agent’s evidence.
Did the QuickBooks project prove Ledger Reborn is a full replacement?
No. The report says selected financial statements for Intuit’s official sample company matched account by account, to the cent. It does not establish full compatibility across all features or situations.
Does REA keep analysis private because it runs locally?
Not necessarily. The report says analysis runs on the user’s machine, but results go to the connected agent and may be handled by its model provider under that provider’s data policy.
Is REA safe for inspecting unknown programs?
The project warns that REA is not a sandbox. Its analysis tools run with the user’s permissions, so the report advises treating unknown binaries like other untrusted files.
Source: ThorstenMeyerAI.com
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