morluto
a4010016a3
* fix(pcap): report a refused tool launch as an unavailable tool When a capture read's tool launch was refused with EPERM, pcap reported it as unreadable tool output (AnalysisProtocolError) instead of an unavailable tool. Pcap also never told "not executable" apart from "missing". Add classifyLaunchFailure in src/process as the one owner of which spawn errnos mean missing (ENOENT, ENOTDIR) and which mean present but not executable (EACCES, EPERM, ENOEXEC, EISDIR). Pcap, apktool and gdb used three different errno lists; all three now use it. * refactor(process): classify owned command outcomes through one owner Add ProviderOutcome, read once from the supervisor's facts, and classifyProviderOutcome, the one mapping from an outcome to a typed error. Migrate pcap and the shared artifact producer command failure (TShark, sigrok). Add the rea/provider-failure-classifier lint rule with a shrink-only baseline of per-site (cause: unknown) => AnalysisError functions. * refactor(process): classify Java and adb launch refusals with the shared owner (#10598) The Ghidra and JADX Java probes and adb's version probe now take missing-versus-not-executable from classifyLaunchFailure instead of their own errno checks. ELOOP and ENAMETOOLONG join the owner's missing set, so adb keeps its existing classification and both Java probes now treat a non-directory path component as a missing runtime. * fix(pcap): preserve command launch attribution * test(pcap): expect an unknown failing stage when a limited capture tool exits unsuccessfully * refactor(process): classify owned command outcomes through one owner Add ProviderOutcome, read once from the supervisor's facts, and classifyProviderOutcome, the one mapping from an outcome to a typed error. Migrate pcap and the shared artifact producer command failure (TShark, sigrok). Add the rea/provider-failure-classifier lint rule with a shrink-only baseline of per-site (cause: unknown) => AnalysisError functions. * test(lint): cover baselined files in the provider-failure classifier rule * fix(apktool): report the decoder JVM's heap exhaustion as memory, not a target refusal The supervisor now watches for a managed runtime's out-of-memory report while output streams (JVM java.lang.OutOfMemoryError, V8 'JavaScript heap out of memory'), so a retention budget cannot hide it. ProviderOutcome gains a runtime-exhausted kind and classifyProviderOutcome maps it once. Apktool decode opts in and moves to the shared classifier; Ghidra's single-purpose output token becomes the JVM runtime option and its area matching reuses the shared table. * fix(process): keep the runtime's out-of-memory report on the memory error it supports * fix(pcap): attribute a limited capture's exit through the prlimit wrapper * fix(process): keep a shortened out-of-memory line marked as shortened * fix(process): identify the refused executable for every launcher shape Name the executable on errnos Node throws synchronously from spawn (ENOEXEC, ENOTDIR, ...) and read the Windows native launcher's executable-launch constraint, so pcap attributes those refusals to the selected tool or limiter instead of an unknown stage. * test(pcap): prove synchronous launch naming with ENOTDIR on every POSIX host * fix(apktool): advise the JVM limit that governs the reported memory area * fix(ghidra): read the supervisor's parsed OOM area instead of reparsing lines * fix(sqlite,capture): read V8 heap exhaustion from streamed output, not retained stderr (#10724) The SQLite worker and the Node capture decoders now declare runtime: "v8", so the supervisor observes V8's heap report as output streams. Both classifiers read the runtime-exhausted outcome instead of matching retained stderr, so a report beyond the retention budget, or one whose process then overflowed its output budget, is still reported as memory exhaustion. * refactor(evm): classify EVMole worker outcomes through the shared provider classifier (#10716) * refactor(evm): classify EVMole worker outcomes through the shared provider classifier The EVMole worker's cancellation, deadline, output budget and CPU/file-size signals now go through classifyProviderOutcome; only the prlimit launch refusal and the reserved EFBIG exit remain in its dialect. The worker is opted into V8 exhaustion scanning so a heap report names its fixed 256 MiB heap. providerOutcomeOf now reads a launch refusal only from a spawn errno, so a private-storage or carrier read errno is no longer reported as a limiter launch failure. * fix(evm): keep a stream failure's exit status and update Linux worker expectations * refactor(process): read launch refusals through the launcher identity owner * refactor(wasm): classify WABT command outcomes through the shared provider classifier (#10727) * refactor(wasm): classify WABT command outcomes through the shared provider classifier WABT's cancellation, command deadline, output budget, and inherited-limit signals now go through classifyProviderOutcome; its dialect keeps only the configuration-probe and launch-refusal unavailability and the unclassified-exit output error. A tool ended by SIGXCPU/SIGXFSZ or the memory limit is now a resource constraint instead of an output error, and a refused launch in the producer phase is reported as unavailable. The shared timeout context gains the analysis setting that selected the deadline, and the output-limit context may name its exceeded budget. * fix(wasm): keep setup guidance when a WABT version probe's output cannot be collected * refactor(providers): classify raw provider failures through one owner * refactor(process): build classified cancellations with cancelledBy and the carried caller reason * chore(lint): count runOwned's close-failure mapper from main in the classifier baseline * fix(process): carry the runtime's exhaustion report on every memory error that claims it SQLite and historical-capture memory errors recognised a streamed V8 heap report but dropped it, so a report outside retained output reached callers without its source line or omission flags. One projection, runtimeExhaustionReport, now owns that shape for the shared classifier and both consumers. Also lowers the EVMole and WABT cancellation-constructor baselines. * fix(process): keep the provider's recovery for a native-thread exhaustion report The shared classifier replaced the provider-supplied recovery with generic capacity advice whenever the JVM reported it could not create a native thread, dropping Apktool's launcher guidance and flipping retryable to true. The provider's recovery now wins; the capacity advice remains the fallback for providers that supply none. * refactor(pwntools): classify pwntools failures through the shared provider classifier (#10782) * refactor(pwntools): classify pwntools failures through the shared provider classifier pwntools' per-site classifier is replaced by pwntoolsFailureDialect for classifyProviderFailure. Command outcomes go through classifyProviderOutcome, launch refusals through launcherRefusalOf instead of a 'spawn ' syscall prefix check, the input limit through the file dialect's fileSize, and the cleanup report through commandCleanup. The shared read cancellation now carries the reader's partial observation, and resource-signal reports accept provider detail. * fix(pwntools): report a failed command's output once and expect resource_constraint for overflow The shared outcome owner already attaches the command's output as capturedOutput, so the pwntools adapter fallback no longer copies the same text into diagnostics.stdout, diagnostics.stderr and diagnostics.captured_output; diagnostics keep the exit facts. Update the overflow expectations the dialect migration missed (layout provider cleanup and over-budget rows, pwntools cleanup) to resource_constraint. * refactor(wasm): leave WABT cancellation to the shared owners WabtFailures matched any Error named AbortError as a cancellation. No WABT path produces one: reads, path checks and owned commands report cancellation as ArtifactReaderFailure or OwnedCommandFailure, which classifyProviderFailure and classifyProviderOutcome already classify with the caller's reason. The provider's two signal checks now build the cancellation with cancelledBy. Lowers the AnalysisCancelledError constructor baseline for both WABT files to zero. * fix(wasm): report a cancelled snapshot write as the caller's cancellation The private snapshot write passed the caller's signal to Node's writeFile, whose abort envelope reached the dialect's unclassified output failure once the name-based AbortError guess was removed. The write now turns the envelope carrying its own signal's reason into cancelledBy at the producer. * refactor(firmware): classify firmware failures through the shared provider classifier (#10810) Firmware producers now report their own deadline expiry: the start check, the output inventory and launcher admission throw the phase timeout where they observe the abort, and a read the phase signal cancelled reports it through the dialect's interruption. The classifier no longer rereads a cancellation's reason as a timeout. A new readCleanup hook keeps firmware's cleanup report shape. * refactor(captures): classify TShark, sigrok and pcap failures through the shared provider classifier TsharkCaptureProvider and SigrokRecordingProvider replace #failure with a dialect, and PcapProvider replaces analysisFailure and the tool-identity classifier. ArtifactAnalysisResources exposes its command context and a readCleanupFailure composer so the readCleanup hook keeps each provider's cleanup report shape. * refactor(jeb): classify JEB failures through the shared provider classifier JEB's raw MCP failures go through classifyProviderFailure with a JEB dialect; a typed attribution step reports a shared phase's failure under the REA operation. Each MCP phase deadline now reports its own interruption when it aborts, deciding a cancellation's owner from the caller's own signal instead of comparing abort reasons. A refusal carrying the JVM's OutOfMemoryError report becomes a resource constraint naming JEB's Java heap. * fix(jeb): advise the JVM limit that governs the reported memory area * refactor(ghidra): classify Ghidra failures through the shared provider classifier PSP extension inspection reports through classifyProviderFailure with a Ghidra dialect. The startup deadline decides at abort time whether the shared startup owner closed it, so Ghidra and Hopper no longer compare the abort reason with the owner's sentinel, and Ghidra's startup no longer compares a producer cancellation's reason with the deadline's. Three helpers that only construct one error kind now name that kind instead of AnalysisError. * refactor(hopper): classify original-source read failures through the shared provider classifier (#10838) * test(ghidra): pin the aborted startup deadline over a producer cancellation * refactor(kuna): classify Kuna failures through the shared provider classifier Session operations, the workspace copy and the project export report raw failures through classifyProviderFailure with Kuna dialects; the copy and export keep their cleanup report shapes through the readCleanup hook. * refactor(adb): report a pulled file's digest failure from its own type * refactor(sqlite): classify worker-reply read failures through the shared provider classifier * refactor(ida): classify IDA operation failures through the shared provider classifier * refactor(process): let artifact-resource consumers classify through the shared provider classifier (#10867) * test(providers): pin attribution of a cleanup-failed read's typed primary * refactor(sqlite): classify database failures through the shared provider classifier * refactor(providers): keep a cancelled read's partial observation and provider diagnostics * refactor(ghidra): classify Ghidra failures through the shared provider classifier (#10836) * refactor(ghidra): classify Ghidra failures through the shared provider classifier PSP extension inspection reports through classifyProviderFailure with a Ghidra dialect. The startup deadline decides at abort time whether the shared startup owner closed it, so Ghidra and Hopper no longer compare the abort reason with the owner's sentinel, and Ghidra's startup no longer compares a producer cancellation's reason with the deadline's. Three helpers that only construct one error kind now name that kind instead of AnalysisError. * refactor(hopper): classify original-source read failures through the shared provider classifier (#10838) * test(ghidra): pin the aborted startup deadline over a producer cancellation * refactor(kuna): classify Kuna failures through the shared provider classifier (#10843) Session operations, the workspace copy and the project export report raw failures through classifyProviderFailure with Kuna dialects; the copy and export keep their cleanup report shapes through the readCleanup hook. * chore(guards): shrink the cancellation construction baseline after merging the base * refactor(ida): classify IDA operation failures through the shared provider classifier (#10859) * refactor(ida): classify IDA operation failures through the shared provider classifier * refactor(process): let artifact-resource consumers classify through the shared provider classifier (#10867) * test(providers): pin attribution of a cleanup-failed read's typed primary
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REA: Reverse Engineer Anything
One MCP for reverse engineering across binaries, applications, and runtime behavior.
See a feature you like. Understand how it works, down to the binary level.
Quick start · How REA works · What you can analyze · Showcases · Build RL environments · FAQ · Documentation
npx rea-agents setup
Important
Get REA from morluto/rea, rea.tools, or the rea-agents npm package. Follow the installation and release links from these official sources. A similar repository name or copied README does not establish that a download is official.
See a feature in an app that you want in your own product? Ask your agent to investigate it with REA. It can inspect the app without its source code, explain how the feature works, show the evidence, and build a version for your project.
REA connects your agent to tools for inspecting native binaries, JavaScript and Electron apps, .NET assemblies, and websites. You can also use the same tools from your terminal. Analysis runs locally, and results include the evidence and limitations behind each conclusion.
Setup registers REA with your agent and installs matching workflow instructions. Native analysis can use an existing Hopper, Ghidra, IDA or Kuna installation; setup can optionally install Hopper with approval. Static JavaScript analysis needs no native analysis engine.
Visit the REA website for setup instructions, illustrated guides, and real case studies.
Quick start
On Linux, Ghidra, JADX, firmware tool launches and static JavaScript/Electron
analysis require a procps-compatible system ps for process ownership
checks. Recovery steps are in docs/getting-started/installation.md under
"Linux owned-process prerequisite".
Set up your agent
With Node.js and npm installed, run:
npx rea-agents setup
Choose your agents, review the proposed changes, and approve them. Setup adds REA's MCP server and matching workflow instructions, with backups of existing configuration. Restart your agent afterward. Setup records the selected runtime and REA entry script directly. If acquired through a package runner, keep its cache entry available. Run package acquisition from a trusted directory outside the target project. Installation and recovery details are in the setup guide below.
Setup supports Claude Code, Codex, Cursor, Gemini CLI, Grok Build and other agents. See installation and setup for provider configuration, manual MCP registration, Claude Code/Codex plugins, and the Cursor Marketplace plugin.
MCP uses compact input schemas by default to reduce context overhead. Set
REA_MCP_INPUT_SCHEMA_PROFILE=full in your MCP registration when you need the
complete advertised field guidance and nested validation details. Both profiles
keep the full tool set and canonical server validation. See
"Compact input schema profile" in the MCP contracts guide.
Output schemas are omitted from tools/list by default: no model API reads
them, and REA validates every result itself. Set
REA_MCP_OUTPUT_SCHEMA_PROFILE=compact to advertise each output schema within
a 4,096-byte budget, or full for complete output schemas (for MCP clients
that validate results). All settings keep canonical server-side validation and
complete structured results. See "Output schemas" in the MCP contracts guide.
Ask your agent
Understand how search works in the Notes app, show me the evidence, and build a
similar feature for my project.
Replace Notes with your target app and the feature you want to understand.
Use the terminal
Inspect an extracted JavaScript/Electron app directory or ASAR:
npx -y rea-agents@latest analyze-javascript-application /absolute/path/to/app --json
The result includes modules, imports, Electron boundaries and their evidence.
Replace the path with your target, such as "D:/apps/example" on Windows.
To install the rea command for regular use:
npm install --global rea-agents
rea --help
For native analysis, configure a provider first. See the CLI and Evidence guide for native commands, provider selection, snapshots and scripting.
Update REA
REA changes quickly, and new releases include frequent bug fixes. Keep your installation up to date.
For a CLI installed with npm install --global or bun add --global:
rea update
rea --update is an alias for this verified workflow and accepts the same global
output flags. Use rea update when combining it with other command controls.
Updater commands retain at most 4 MiB of stdout and stderr combined. Oversized metadata replies are rejected after the command exits; verbose installs continue with bounded diagnostics. Human progress output respects terminal backpressure and waits for submitted writes to finish.
Bun global updates require Bun 1.2.17 or later. With an older Bun release,
upgrade Bun manually before running rea update.
To refresh your agent registrations and skill, run the setup command printed by the update.
If you use npx, update your agent setup with:
npx rea-agents@latest setup
Review the setup changes and restart your agent. For one-off CLI commands,
use npx rea-agents@latest followed by the command. With Bun, use
bunx rea-agents@latest in place of npx rea-agents@latest.
How REA works
Your agent calls REA through MCP to inspect the target and trace relevant code. REA returns findings with their evidence. The agent uses them to ask follow-up questions, explain the behavior, or write and test an implementation. CLI commands use the same workflows.
What you can analyze
REA requires Node.js 22.x (>=22.23.4), 24.x (>=24.22.1), or 26.12.1+, plus npm. Additional tools and host support depend on the target:
| Target | What REA returns | Requirements and guide |
|---|---|---|
| Desktop installations | Runtime candidates, supporting files, component markers and next probes | Built-in bounded directory/header inspection; desktop applications |
| Native binaries | Pseudocode, assembly, strings, symbols, calls and references | Hopper, Ghidra, IDA or Kuna; native analysis |
| Offline ELF layout | Sections, segments, original symbols/relocations and static mitigation candidates | Caller-supplied pwntools on Linux x64; binary diagnostics |
| Go binaries | Embedded compiler version, modules, replacements and build settings | Built-in static ELF/PE/thin Mach-O inspection; no Go installation required |
| GPU code objects | CUDA/HIP targets, selected kernel parameters and resources, retained PTX text | Built-in static ELF/PE/fatbin/CUBIN/PTX inspection; GPU code objects |
| Model artifacts | GGUF / safetensors metadata, tensor declarations and derived totals | Built-in header inspection; optional full-file hash; model files |
| IL2CPP metadata | Unity global-metadata.dat assembly images, type and method names and index ranges | Built-in static decoding of versions 24, 27, 29, 31 and 39; no Unity required |
| Godot PCK | Archive inventory and extraction, original header/directory facts and selected content identities | Built-in static formats 2, 3 and 4; no Godot required |
| Rust binaries | Embedded cargo-auditable crate names, versions, sources and dependency edges | Built-in static ELF/PE/thin Mach-O inspection; Rust binaries |
| PE certificates | Authenticode WIN_CERTIFICATE entries and PKCS#7 signer/X.509 identity fields | Built-in static PE inspection; PE certificates |
| PE imports | Import and delay-load DLL names, ordinals, IAT RVAs and pefile import hash | Built-in static PE inspection; PE imports |
| Windows shortcuts | Shell Link target, arguments, working dir, ExtraData and Tracker droid facts | Built-in static LNK inspection; Windows shortcuts |
| ELF notes | PT_NOTE/SHT_NOTE owners, types, GNU build-id and ABI-tag fields | Built-in static ELF inspection; ELF notes |
| Binary hardening | PIE, NX, RELRO, CFG and related header flags for ELF, PE and Mach-O | Built-in static header inspection; binary hardening |
| Apple IPS crashes | .ips metadata, threads, images, registers and documented crash classes | Built-in static JSON inspection; Apple IPS |
| Linux kernel modules | .modinfo keys, __versions CRCs, this_module presence, and signature trailer | Built-in static ELF inspection; kernel modules |
| Erlang BEAM | IFF chunks, atoms, exports, imports, lambdas and the Code header | Built-in static BEAM inspection; Erlang BEAM |
| WASM artifact | Validation, sections, exact import/export WAT forms and decoded WAT | Caller-supplied WABT 1.0.42; inspect_wasm_artifact |
| EVM bytecode | Dispatch selectors, byte offsets, inferred arguments and mutability | Local raw/hex carrier on Linux x64; offline EVM guide |
| SQLite databases | Tables, columns, indexes, views, triggers and selected ordinary-table rows | Local database/WAL snapshot; Node.js 24.x >=24.15 or 26+ with native SQLite limits |
| Recorded Linux crashes | Raw notes, every recorded thread's registers/signals and optional mapping candidates | Caller-supplied pwntools on Linux x64; optional GDB/pwndbg; recorded crashes |
| JavaScript / Electron | Modules, imports, source maps, routes, IPC, native add-ons, rea audit-release-exposure |
Node.js and npm; Linux: procps-compatible ps; application analysis |
| Websites | Page structure, scripts, network observations and requested screenshots | A Chrome-family browser; browser analysis |
| Saved network captures | Requests, responses, exposed payloads and source locations | HAR or Fiddler Everywhere SAZ; mitmdump on Linux for native mitmproxy; capture guide |
| .NET assemblies | Metadata, CIL instructions, declared native dependencies and build comparisons | None (static only); managed-code guide |
| Android APKs | Manifest declarations, classes, decompiled methods and references | Headless JADX and a full JDK on Linux/macOS/Windows x64; Android guide |
| APK signatures | v1/v2/v3/v3.1 signers, certificate fingerprints, key rotation and digest self-consistency | None (static only); inspect_apk_signature |
| Android devices | Devices, packages, processes, logs, dumps, screen captures, and APK/file transfers | Caller-supplied adb (emulator or hardware); ADB guide |
| JEB projects | Engine-backed project units, artifact digests and type/method pseudo-code | A caller-started JEB client serving MCP, selected with REA_JEB_MCP_URL; JEB guide |
| Android resources | Decoded manifest, string tables, locales and version facts | Caller-supplied Apktool launcher; resource guide |
| Flutter apps | Dart snapshot hash, per-ABI library digests and engine build provenance | None (static APK parsing); Flutter guide |
| Firmware | Regions, extraction results and native-analysis handoffs | Binwalk / Unblob on Linux; firmware guide |
| Recorded packets | Selected fields, repeated values, filters and decode-as rules | Linux: TShark 4.x + prlimit; capture guide |
| Packet summaries | Endpoints, DNS, TLS SNI, protocol distribution and HTTP requests | Caller-supplied tshark and capinfos (Linux-verified); pcap guide |
| Recorded logic signals | Decoder annotations, sample ranges and diagnostics | Linux: sigrok-cli 0.7.2 + prlimit; signal recordings |
| Packages and resources | File inventories, digests, plists, Apple bundle anatomy and extracted resources | Artifact and JavaScript guide, Apple applications |
| Process behavior | Terminal output, interactions, exit and filesystem observations, and run comparisons | Linux/macOS with a native PTY; process capture |
| PyInstaller executables | CArchive members, Python version, entry scripts and extracted bytecode | None (static only); Python packaged applications |
| Deno compile binaries | Virtual files, entry point, recorded options, npm snapshot length | None (static only); Deno compile executables |
Static JavaScript and .NET inspection read the supplied files without running the application. Runtime capture runs or interacts with the selected target using your user permissions; each runtime guide describes its effects.
For offline native-binary inspection, REA also supports caller-supplied GNU objdump and Rizin. See the reverse-engineering tools guide for provider setup, CLI commands, and Evidence limitations. REA does not install or update either provider.
Native formats and host support vary by provider. See
Hopper and Ghidra setup, the
IDA guide (including an optional native MCP bridge), the
Kuna decompiler guide, and
experimental Windows Ghidra support.
Ghidra also supports 16-bit DOS analysis.
For large binaries, raise the provider's startup deadline with
REA_GHIDRA_STARTUP_TIMEOUT_MS or REA_HOPPER_STARTUP_TIMEOUT_MS.
For provider selection, see the CLI guide.
Check release availability
for features added since the latest npm release.
Showcases
DX-Ball: reconstruct a sound-pan calculation
Follow a sound call into its position-to-pan helper, inspect the instructions, and turn incomplete pseudocode into C. The reconstruction passes 3,205 original-x86 cases and reproduces all 63 compiled function bytes.
Read the case study · Reconstruction repository
Notion: trace the Electron clipboard bridge
Find the renderer's clipboard API, follow it through preload and IPC into the main process, and inspect the rich clipboard format.
TH04: recover a DOS bullet-ring calculation
Inspect the original PC-98 game's 16-bit instructions, recover the fixed and aimed angle calculations, and compare the reconstructed C++ with the historical compiler output.
Read the case study · Reconstruction repository
Build RL environments with REA
Record a web app session, turn its API into tools, and export an environment an AI agent can use. Run it with AgentEnv, then add tasks and reward checks for RL training or evaluation.
Read the guide · Watch the video
If you've used REA on something interesting, we'd love to see it. Share your case in an issue or a pull request, including the target, your question, how REA helped, and what you found.
Build RL environments
Give an AI agent a local environment to practice tasks such as finding an issue or creating a folder, without running the original app. Use it for reinforcement learning (RL) or to test how well an agent completes tasks.
REA turns recorded API requests and responses into tools the agent can call. The environment uses the recorded data and supports changes only when the recording confirms their effects.
With REA set up in your agent, replace the example URL and folder tasks below with your own:
Use REA to build an RL environment from my test web app at
http://127.0.0.1:3000.
Cover listing, creating, renaming, and deleting folders. You may create and
remove test folders. Leave existing data unchanged.
Save it in a folder named my-env. Check which operations work and tell me
how to run it.
Use the command line instead
Use these commands if you already have a file containing the app’s recorded browser requests and responses. Running the result also requires AgentEnv and Docker.
rea environment-build ./session.har ./my-env --name my-env --json
agent-env run ./my-env
REA exports a runnable environment with a basic test to check that it starts and responds. Use it with your RL framework to define task goals, add reward checks, and run training.
Build an environment · Environment reference · Watch the demo on X
Desktop app environments
REA can also build an environment of a Linux desktop app, which an agent uses through screenshots, the mouse and the keyboard. From a one-line request, such as "Build me a Gnote environment where the agent adds olive oil to the shopping list note", your agent installs the app on a local build computer, writes the task, exports the environment and checks the task in a fresh computer. The machine that builds it needs Linux on amd64 or arm64, Docker and the agentenv framework version the guide pins.
Set up desktop app environments
FAQ
Which agents can use REA?
Any agent that supports local MCP servers. Setup configures the supported agents; other clients can use manual MCP registration.
Do I need a native analysis engine?
Deep native analysis uses Hopper, Ghidra, IDA or Kuna, depending on the target and operation. Static JavaScript and .NET inspection work without a native analysis engine. Setup can install Hopper after approval; Ghidra, IDA and Kuna use your existing installations. See provider setup for the options and their supported targets.
Do I need to start Hopper first?
REA starts Hopper when an operation needs it. On macOS, a first-run dialog may ask you to choose demo mode or activate your license. Complete that prompt in the same user session before your first CLI/MCP operation or unattended job. Open Hopper manually if needed. See Hopper startup and troubleshooting.
What does installing the skill from skills.sh do?
The skill supplies investigation instructions for your agent. Use npx rea-agents setup
to register REA's MCP server and install the matching instructions, then restart
your agent. See skill-only installation.
What code does REA return?
Native analysis returns pseudocode and assembly. JavaScript/Electron analysis recovers modules and their relationships. Your agent uses these findings to write and test an implementation; the showcases give worked examples.
Does REA upload my app?
REA analyzes targets locally. Your agent receives the tool results, and its model provider has its own data policy.
What should I do if I hit a bug?
Update first; a recent release may already fix it.
For a CLI installed with npm install --global or bun add --global:
rea update
For agent setup through npx:
npx rea-agents@latest setup
If you're using an agent, complete the setup refresh and restart it. Retry the same task. If the problem persists, open an issue with your REA version, target type, steps to reproduce and error output.
Documentation
Start with the website's worked guides. For exact options, prerequisites and result contracts:
- Installation and setup: agent registration, provider configuration, updates and uninstall.
- Readiness and troubleshooting: diagnose one agent or analysis engine.
- CLI and Evidence: commands, provider selection, snapshots, import/export and exit statuses.
- MCP contracts and agent prompts: tool results, sessions and guided investigations.
- Tool catalog: generated inventory of tools, providers and CLI commands.
- Roadmap: planned work and capability trackers.
Report vulnerabilities through SECURITY.md.
Star history
🎉 400,000 GitHub stars — thank you!
Thanks to everyone using REA, reporting bugs, requesting features, testing builds, and contributing fixes.
Disclaimer
See DISCLAIMER.md for responsible-use guidance.
The project's position on illegal or unauthorized use covers all REA versions, distribution channels, and platforms; each copy retains its applicable licenses.
REA is for lawful research, education, interoperability, software preservation, and analysis of software you own or are authorized to examine.
Contributing
We'd love your help with REA! Open an issue to report a bug or suggest a feature, or send a pull request to improve the code or docs.
See CONTRIBUTING.md for development setup and checks, testing for verification lanes, and the architecture map for selected layers and dependency paths.
License
REA-authored code is licensed under MIT. Third-party material retains its own licenses and copyright notices; see Third-party notices for the dependency inventory, preserved license texts, and external-tool terms.
You must legally obtain and be authorized to use commercial tools, including IDA Pro / Hex-Rays decompilers, Hopper, and JEB, under their applicable licenses. REA grants no tool license, key, or activation entitlement. Trials and demos remain subject to vendor terms, including user, feature, automation, and output sharing restrictions. Cracked copies, stolen keys, unauthorized key sharing, and bypassing license restrictions are not authorized. This guidance does not amend MIT or third-party licenses.