{"content_id":"8zzqjhcwre","slug":"rea-ai-reverse-engineering-capabilities-and-limits","locale":"en","schema_type":"TechArticle","category":"knowledge_base","category_name":"Knowledge Base","title":"REA AI Reverse Engineering: How It Works and Clone Limits","summary":"REA connects AI agents to existing analysis tools to examine software. It does not guarantee recovery of the original source code or replication of a finished product. The ArtCraft case also shows why implementing features must be distinguished from making a product ready for real-world use.","sponsorship_disclosure":null,"affiliate_disclosure":null,"commerce_disclosure":null,"author":{"name":"Injoys Editorial Team","url":"https://injoys.com/ko/about"},"key_points":["REA is a reverse engineering tool that connects AI agents to Ghidra, Hopper, IDA and other tools.","Decompiled output provides clues to how a program works, but is not the same as its original source code.","REA's Evidence records help track the basis for an analysis and its limitations, but do not guarantee accuracy.","FilmCraft presented functional scope and readiness for real-world use separately in its self-assessment on October 10, 2026.","CLI and MCP support expands the app's automation options, but does not replace performance and compatibility testing."],"content_markdown":"REA is a reverse engineering tool that helps AI analyze apps without source code. It connects existing analyzers to support the reimplementation of functionality. However, it does not guarantee complete recovery of the original code. Nor does it prove that the software era is over.\n\nThe completeness figures below are based on FilmCraft's self-assessment dated October 10, 2026.\n\n## What is REA?\n\nREA stands for Reverse Engineer Anything. Reverse engineering is the process of examining a finished program's structure and behavior. REA lets AI agents call the tools needed for this work.\n\nIt connects through MCP and CLI. MCP is a protocol that connects AI to external tools. With CLI, users operate tools by entering commands in a terminal. Supported targets are listed in the [REA README](https://github.com/morluto/rea).\n\n| Component | Role | What to check when reading the results |\n| --- | --- | --- |\n| AI agent | Sets research questions and interprets results | Check whether explanations are supported by evidence |\n| REA | Calls tools and delivers analysis results | Check the scope of analysis and any omissions |\n| Ghidra·Hopper·IDA | Analyze the internal structure of executable files | Check supported formats and each analyzer's limitations |\n| Runtime observation tools | Observe actual behavior and output | Check the inputs tested and the runtime environment |\n\nREA and ArtCraft are projects with different roles. REA connects analysis tools. ArtCraft's Crafting Apps are apps that perform editing tasks. The existence of both projects alone does not establish a connection between their development processes.\n\n## What can you learn from an executable file?\n\nDecompilation converts executable code into a form that is easier for people to read. The result cannot be treated as identical to the original source code. Original names and comments may be lost during compilation.\n\nGhidra is a reverse engineering tool developed and maintained by the NSA. It provides decompilation and instruction analysis. It also supports automation and scripting. Its capabilities are listed in the [Ghidra README](https://github.com/NationalSecurityAgency/ghidra).\n\n| Analysis target | Clues you can obtain | What the clues alone cannot establish |\n| --- | --- | --- |\n| Native executable file | Pseudocode, instructions, strings, call relationships | All of the source code originally written |\n| JavaScript·Electron app | Modules, import relationships, internal app connections | Implementations that run only on the server |\n| Website | Page structure, scripts, observed communications | All server code and private data |\n| Running program | Output, interactions, file changes | Behavior for every input that was not tested |\n\nRequests observed on the client can provide clues for server analysis. Those requests alone cannot fully reconstruct the server's internals. REA's support for each target is also distinguished in the [official README](https://github.com/morluto/rea).\n\n## How does REA help AI analyze programs?\n\nREA selects and delivers the analysis results needed, and stores supporting evidence. This structure reduces the need for AI to repeatedly read long outputs in full. The workflow is described in the official CLI documentation and MCP specification.\n\n### A structure for reading only what is needed\n\nREA can retrieve summaries or selected entries from stored analysis results. This narrows the investigation to particular functions or modules. It reduces the burden of placing lengthy results into a conversation unchanged. The approach is explained in the [CLI and Evidence documentation](https://github.com/morluto/rea/blob/main/docs/cli.md).\n\n### Reusing analysis state and results\n\nThe Ghidra integration keeps a decompiler available for an open program. An MCP session can store analysis evidence. Separate CLI runs, however, are separate processes. The extent of what persists is described in the [installation documentation](https://github.com/morluto/rea/blob/main/docs/installation.md).\n\n### Keeping an Evidence record\n\nEvidence is a record of the basis and limitations of an analysis result. Items that were not observed can remain marked as unverified. An empty result does not, by itself, establish that a feature is absent. This distinction is set out in the [MCP runtime contracts](https://github.com/morluto/rea/blob/main/docs/mcp-contracts.md).\n\nEvidence can be compared to a receipt. But having a receipt does not guarantee that the interpretation is accurate. Important conclusions should be checked again against the original evidence and test results.\n\n## What do the ArtCraft apps reimplement?\n\nArtCraft publishes Rust apps for familiar creative tasks. Its official list identifies apps in early alpha or under development. Whether an app is available for free and whether it can replace a tool in professional work must be judged separately. The list is on the [Crafting Apps page](https://getartcraft.com/apps).\n\n| App | Main task |\n| --- | --- |\n| PhotoCraft | Image editing |\n| VectorCraft | Creating vector illustrations |\n| FilmCraft | Video editing |\n| LightCraft | Photo management and RAW processing |\n| PdfCraft | Opening PDFs and processing documents |\n| EffectCraft | Motion graphics and visual effects |\n| DesignCraft | Page layout and publication editing |\n\nPhotoCraft aims to reimplement Photoshop workflows. FilmCraft aims to reimplement Premiere Pro workflows. These are the project goals described by the development team. They are not independent proof of full compatibility.\n\n## Comparing implemented features and readiness for professional work\n\nA feature's existence is different from its suitability for professional work. FilmCraft evaluates these separately. The comparison target on October 10, 2026, was Premiere Pro 26.5.2.\n\n| FilmCraft self-assessment category | Published figure | What the figure describes |\n| --- | --- | --- |\n| Feature coverage | About 86% | The range of implemented items, including menus, effects, panels, and formats |\n| Readiness for professional work | About 56% | The team's estimate of how well it can serve as a replacement in real projects |\n\nThe estimated readiness for professional work at that time was **about 56%**. The two figures use different assessment criteria. Their difference should not be read as an error rate or the time remaining in development. The figures and limitations are published in the Status section of the [FilmCraft README](https://github.com/storytold/filmcraft).\n\nThe official documentation identifies processing speed for large videos as an area for improvement. It also says that opening Premiere project files directly is not supported. Plugin hosting has limitations too.\n\nFor these reasons, a similar-looking interface is not enough to determine whether the app can serve as a replacement. The full workflow, including saving and reopening, needs to be checked. In video editing, the synchronization of exported files also needs to be verified.\n\nThe following checklist can be used to compare apps.\n\n| Check | What to test directly |\n| --- | --- |\n| File compatibility | Whether you can open and save the files you use |\n| Playback quality | Whether playback stutters or audio is delayed with footage from actual work |\n| Output | Whether the exported video's colors, subtitles, and sound match what you intended |\n| Resuming work | Whether you can reopen a saved project and continue working |\n| Existing workflow | Whether the app supports the plugins and interchange formats you need |\n\n## How CLI and MCP change the way apps are used\n\nCLI and MCP provide ways to operate apps other than clicking through an interface. According to PhotoCraft's description, multiple interfaces call the same engine. Those interfaces are UI, CLI, a JSON control channel, and MCP. The structure is documented in the [PhotoCraft README](https://github.com/storytold/photocraft).\n\nThis provides a basis for AI to call app features as individual tasks. The agent is responsible for turning a natural-language request into actual commands. A separate process is needed to check the results.\n\n| Way to operate the app | Suitable tasks | What to check |\n| --- | --- | --- |\n| On-screen UI | Editing that requires visual judgment | Whether the preview matches the final result |\n| CLI | Repetitive tasks and running scripts | Input options and exit status |\n| MCP | Tasks combined by an AI agent | Features called and verification of the results |\n\nThere is not enough evidence here to predict the disappearance of the UI. People may still need to inspect results visually. Automation and visual editing interfaces can be used together.\n\n## Common mistakes when understanding REA\n\nConfusing REA's analysis capabilities with the ability to copy a finished product leads to misunderstandings. The number of tools alone also says little about analysis quality. Each of the following claims needs separate evidence.\n\n| Common claim | What to check separately |\n| --- | --- |\n| It reconstructs any app in minutes | Measurements for each target, analysis scope, and environment |\n| There are always 126 tools | The actual tool list for the installed version |\n| Evidence prevents hallucinations | The difference between recording evidence and interpreting it accurately |\n| Building it in Rust always makes it fast | Processing performance measured in actual work |\n| If the interface looks the same, the features are the same | Tests that include saving, compatibility, and output |\n| Separating agents makes it a legal clean-room implementation | How access is separated and which terms of use apply |\n\nYou can check the tool list with `tools/list` for the installed version. You also need to check whether each tool can be used for the task at hand. The relevant criteria are explained in the [MCP specification](https://github.com/morluto/rea/blob/main/docs/mcp-contracts.md).\n\nA GitHub trending ranking needs a collection time and period. A developer's motivation should also be verified against their original statement. The claim that the project began because of an early termination fee was not accepted as a verified fact.\n\nThe claim that Claude Opus 5.5 was used also requires separate development records. The fact that an app is public does not prove which model was used. Check that claim against the developer's work records or original announcement.\n\n## Conditions for clean-room reimplementation\n\nClean-room reimplementation separates access to information between analysis and implementation. The role of producing a functional specification is separated from the role of writing new code. Putting agents in different chat windows is not enough.\n\nThe REA installation documentation explains restrictions on file and network access. These are intended to prevent the implementation environment from accessing analysis outputs. The separation method is described in the [Installation and setup documentation](https://github.com/morluto/rea/blob/main/docs/installation.md).\n\nThe REA DISCLAIMER does not guarantee the accuracy of results. Obtaining analysis results does not grant rights to the original program, either. Rights and terms of use must be checked for each program. The scope of these limitations is stated in the [REA DISCLAIMER](https://github.com/morluto/rea/blob/main/DISCLAIMER.md).\n\n\u003e Decompilation, reconstruction, heuristics, and AI-assisted analysis may be incomplete or incorrect.\n\u003e\n\u003e REA DISCLAIMER, Analysis results and generated output\n\nThis means AI analysis may be incomplete or incorrect. Calling a process clean-room does not automatically make it lawful. If you plan to publish or commercialize a result, check the target's terms of use first.\n\n## The difference between local analysis and sending data to AI\n\nLocal analysis does not mean that no information is sent externally. REA says it processes target files locally. An agent that receives tool results is subject to the model provider's policies. This distinction is explained in the [REA FAQ](https://github.com/morluto/rea).\n\nAnalysis results may contain strings from inside files. Execution logs may include account information. If you are investigating a work app, check these points first.\n\n- Personal and confidential information that may be included in analysis results\n- Tool output the agent sends to the model provider\n- The model service's storage, training, and retention policies\n- Who may receive analysis reports and logs\n\nA target may also contain instructions intended to deceive the AI. The REA documentation says to treat these as untrusted data. Instructions inside a file must not be accepted as commands from the user. The handling principle is in the [MCP specification](https://github.com/morluto/rea/blob/main/docs/mcp-contracts.md).\n\n## Steps for direct verification\n\nStart by defining a narrow feature to reproduce. A goal of understanding an entire app has unclear completion criteria. Setting an input and expected result makes it easier to judge whether the analysis is useful.\n\n1. Choose a program you are authorized to analyze.\n2. Define the feature to check and the test input.\n3. Record the versions of REA and the analyzer.\n4. Save supporting evidence and unverified items separately.\n5. In an authorized environment, compare actual behavior with the analysis results.\n6. If you reimplemented the feature, compare the results using the same input.\n7. Record inputs that failed and conditions that are not supported.\n\nYou can also record a hash of the target file in the report. A hash is a value used to distinguish whether files are the same. Keeping the version and test conditions makes it easier for others to verify the results again.\n\n## Where does software retain its competitive value?\n\nEven if reimplementation becomes easier, not all of a product's value can be copied. Analyzing a client does not, by itself, provide access to server data. User relationships and the ability to operate a service are separate too.\n\nThe public documentation suggests that the basis for competition may change. How quickly features are implemented alone will become a less useful measure. Verifiable quality and operational capability also need to be considered.\n\n| Competitive factor | What REA and reimplementation examples show |\n| --- | --- |\n| Feature implementation | It is becoming easier to connect tools that investigate existing behavior |\n| Product maturity | The existence of features and readiness for professional work need separate assessments |\n| Access to automation | Callable interfaces such as CLI and MCP expand the ways a product can be used |\n| Service operations | Server data and user relationships must be built separately |\n\nThis table is an interpretation based on official documentation. It is not a measurement of changes in revenue across the market. The effect on each company may vary with its product quality and operational structure.","content_html":"\u003cp\u003eREA is a reverse engineering tool that helps AI analyze apps without source code. It connects existing analyzers to support the reimplementation of functionality. However, it does not guarantee complete recovery of the original code. Nor does it prove that the software era is over.\u003c/p\u003e\n\u003cp\u003eThe completeness figures below are based on FilmCraft's self-assessment dated October 10, 2026.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#what-is-rea\" class=\"anchor\" id=\"what-is-rea\"\u003e\u003c/a\u003eWhat is REA?\u003c/h2\u003e\n\u003cp\u003eREA stands for Reverse Engineer Anything. Reverse engineering is the process of examining a finished program's structure and behavior. REA lets AI agents call the tools needed for this work.\u003c/p\u003e\n\u003cp\u003eIt connects through MCP and CLI. MCP is a protocol that connects AI to external tools. With CLI, users operate tools by entering commands in a terminal. Supported targets are listed in the \u003ca href=\"https://github.com/morluto/rea\"\u003eREA README\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eComponent\u003c/th\u003e\n\u003cth\u003eRole\u003c/th\u003e\n\u003cth\u003eWhat to check when reading the results\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eAI agent\u003c/td\u003e\n\u003ctd data-label=\"Role\"\u003eSets research questions and interprets results\u003c/td\u003e\n\u003ctd data-label=\"What to check when reading the results\"\u003eCheck whether explanations are supported by evidence\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eREA\u003c/td\u003e\n\u003ctd data-label=\"Role\"\u003eCalls tools and delivers analysis results\u003c/td\u003e\n\u003ctd data-label=\"What to check when reading the results\"\u003eCheck the scope of analysis and any omissions\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eGhidra·Hopper·IDA\u003c/td\u003e\n\u003ctd data-label=\"Role\"\u003eAnalyze the internal structure of executable files\u003c/td\u003e\n\u003ctd data-label=\"What to check when reading the results\"\u003eCheck supported formats and each analyzer's limitations\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eRuntime observation tools\u003c/td\u003e\n\u003ctd data-label=\"Role\"\u003eObserve actual behavior and output\u003c/td\u003e\n\u003ctd data-label=\"What to check when reading the results\"\u003eCheck the inputs tested and the runtime environment\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eREA and ArtCraft are projects with different roles. REA connects analysis tools. ArtCraft's Crafting Apps are apps that perform editing tasks. The existence of both projects alone does not establish a connection between their development processes.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#what-can-you-learn-from-an-executable-file\" class=\"anchor\" id=\"what-can-you-learn-from-an-executable-file\"\u003e\u003c/a\u003eWhat can you learn from an executable file?\u003c/h2\u003e\n\u003cp\u003eDecompilation converts executable code into a form that is easier for people to read. The result cannot be treated as identical to the original source code. Original names and comments may be lost during compilation.\u003c/p\u003e\n\u003cp\u003eGhidra is a reverse engineering tool developed and maintained by the NSA. It provides decompilation and instruction analysis. It also supports automation and scripting. Its capabilities are listed in the \u003ca href=\"https://github.com/NationalSecurityAgency/ghidra\"\u003eGhidra README\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eAnalysis target\u003c/th\u003e\n\u003cth\u003eClues you can obtain\u003c/th\u003e\n\u003cth\u003eWhat the clues alone cannot establish\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Analysis target\"\u003eNative executable file\u003c/td\u003e\n\u003ctd data-label=\"Clues you can obtain\"\u003ePseudocode, instructions, strings, call relationships\u003c/td\u003e\n\u003ctd data-label=\"What the clues alone cannot establish\"\u003eAll of the source code originally written\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Analysis target\"\u003eJavaScript·Electron app\u003c/td\u003e\n\u003ctd data-label=\"Clues you can obtain\"\u003eModules, import relationships, internal app connections\u003c/td\u003e\n\u003ctd data-label=\"What the clues alone cannot establish\"\u003eImplementations that run only on the server\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Analysis target\"\u003eWebsite\u003c/td\u003e\n\u003ctd data-label=\"Clues you can obtain\"\u003ePage structure, scripts, observed communications\u003c/td\u003e\n\u003ctd data-label=\"What the clues alone cannot establish\"\u003eAll server code and private data\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Analysis target\"\u003eRunning program\u003c/td\u003e\n\u003ctd data-label=\"Clues you can obtain\"\u003eOutput, interactions, file changes\u003c/td\u003e\n\u003ctd data-label=\"What the clues alone cannot establish\"\u003eBehavior for every input that was not tested\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eRequests observed on the client can provide clues for server analysis. Those requests alone cannot fully reconstruct the server's internals. REA's support for each target is also distinguished in the \u003ca href=\"https://github.com/morluto/rea\"\u003eofficial README\u003c/a\u003e.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#how-does-rea-help-ai-analyze-programs\" class=\"anchor\" id=\"how-does-rea-help-ai-analyze-programs\"\u003e\u003c/a\u003eHow does REA help AI analyze programs?\u003c/h2\u003e\n\u003cp\u003eREA selects and delivers the analysis results needed, and stores supporting evidence. This structure reduces the need for AI to repeatedly read long outputs in full. The workflow is described in the official CLI documentation and MCP specification.\u003c/p\u003e\n\u003ch3\u003e\n\u003ca href=\"#a-structure-for-reading-only-what-is-needed\" class=\"anchor\" id=\"a-structure-for-reading-only-what-is-needed\"\u003e\u003c/a\u003eA structure for reading only what is needed\u003c/h3\u003e\n\u003cp\u003eREA can retrieve summaries or selected entries from stored analysis results. This narrows the investigation to particular functions or modules. It reduces the burden of placing lengthy results into a conversation unchanged. The approach is explained in the \u003ca href=\"https://github.com/morluto/rea/blob/main/docs/cli.md\"\u003eCLI and Evidence documentation\u003c/a\u003e.\u003c/p\u003e\n\u003ch3\u003e\n\u003ca href=\"#reusing-analysis-state-and-results\" class=\"anchor\" id=\"reusing-analysis-state-and-results\"\u003e\u003c/a\u003eReusing analysis state and results\u003c/h3\u003e\n\u003cp\u003eThe Ghidra integration keeps a decompiler available for an open program. An MCP session can store analysis evidence. Separate CLI runs, however, are separate processes. The extent of what persists is described in the \u003ca href=\"https://github.com/morluto/rea/blob/main/docs/installation.md\"\u003einstallation documentation\u003c/a\u003e.\u003c/p\u003e\n\u003ch3\u003e\n\u003ca href=\"#keeping-an-evidence-record\" class=\"anchor\" id=\"keeping-an-evidence-record\"\u003e\u003c/a\u003eKeeping an Evidence record\u003c/h3\u003e\n\u003cp\u003eEvidence is a record of the basis and limitations of an analysis result. Items that were not observed can remain marked as unverified. An empty result does not, by itself, establish that a feature is absent. This distinction is set out in the \u003ca href=\"https://github.com/morluto/rea/blob/main/docs/mcp-contracts.md\"\u003eMCP runtime contracts\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eEvidence can be compared to a receipt. But having a receipt does not guarantee that the interpretation is accurate. Important conclusions should be checked again against the original evidence and test results.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#what-do-the-artcraft-apps-reimplement\" class=\"anchor\" id=\"what-do-the-artcraft-apps-reimplement\"\u003e\u003c/a\u003eWhat do the ArtCraft apps reimplement?\u003c/h2\u003e\n\u003cp\u003eArtCraft publishes Rust apps for familiar creative tasks. Its official list identifies apps in early alpha or under development. Whether an app is available for free and whether it can replace a tool in professional work must be judged separately. The list is on the \u003ca href=\"https://getartcraft.com/apps\"\u003eCrafting Apps page\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eApp\u003c/th\u003e\n\u003cth\u003eMain task\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"App\"\u003ePhotoCraft\u003c/td\u003e\n\u003ctd data-label=\"Main task\"\u003eImage editing\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"App\"\u003eVectorCraft\u003c/td\u003e\n\u003ctd data-label=\"Main task\"\u003eCreating vector illustrations\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"App\"\u003eFilmCraft\u003c/td\u003e\n\u003ctd data-label=\"Main task\"\u003eVideo editing\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"App\"\u003eLightCraft\u003c/td\u003e\n\u003ctd data-label=\"Main task\"\u003ePhoto management and RAW processing\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"App\"\u003ePdfCraft\u003c/td\u003e\n\u003ctd data-label=\"Main task\"\u003eOpening PDFs and processing documents\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"App\"\u003eEffectCraft\u003c/td\u003e\n\u003ctd data-label=\"Main task\"\u003eMotion graphics and visual effects\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"App\"\u003eDesignCraft\u003c/td\u003e\n\u003ctd data-label=\"Main task\"\u003ePage layout and publication editing\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003ePhotoCraft aims to reimplement Photoshop workflows. FilmCraft aims to reimplement Premiere Pro workflows. These are the project goals described by the development team. They are not independent proof of full compatibility.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#comparing-implemented-features-and-readiness-for-professional-work\" class=\"anchor\" id=\"comparing-implemented-features-and-readiness-for-professional-work\"\u003e\u003c/a\u003eComparing implemented features and readiness for professional work\u003c/h2\u003e\n\u003cp\u003eA feature's existence is different from its suitability for professional work. FilmCraft evaluates these separately. The comparison target on October 10, 2026, was Premiere Pro 26.5.2.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eFilmCraft self-assessment category\u003c/th\u003e\n\u003cth\u003ePublished figure\u003c/th\u003e\n\u003cth\u003eWhat the figure describes\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"FilmCraft self-assessment category\"\u003eFeature coverage\u003c/td\u003e\n\u003ctd data-label=\"Published figure\"\u003eAbout 86%\u003c/td\u003e\n\u003ctd data-label=\"What the figure describes\"\u003eThe range of implemented items, including menus, effects, panels, and formats\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"FilmCraft self-assessment category\"\u003eReadiness for professional work\u003c/td\u003e\n\u003ctd data-label=\"Published figure\"\u003eAbout 56%\u003c/td\u003e\n\u003ctd data-label=\"What the figure describes\"\u003eThe team's estimate of how well it can serve as a replacement in real projects\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eThe estimated readiness for professional work at that time was \u003cstrong\u003eabout 56%\u003c/strong\u003e. The two figures use different assessment criteria. Their difference should not be read as an error rate or the time remaining in development. The figures and limitations are published in the Status section of the \u003ca href=\"https://github.com/storytold/filmcraft\"\u003eFilmCraft README\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eThe official documentation identifies processing speed for large videos as an area for improvement. It also says that opening Premiere project files directly is not supported. Plugin hosting has limitations too.\u003c/p\u003e\n\u003cp\u003eFor these reasons, a similar-looking interface is not enough to determine whether the app can serve as a replacement. The full workflow, including saving and reopening, needs to be checked. In video editing, the synchronization of exported files also needs to be verified.\u003c/p\u003e\n\u003cp\u003eThe following checklist can be used to compare apps.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eCheck\u003c/th\u003e\n\u003cth\u003eWhat to test directly\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Check\"\u003eFile compatibility\u003c/td\u003e\n\u003ctd data-label=\"What to test directly\"\u003eWhether you can open and save the files you use\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Check\"\u003ePlayback quality\u003c/td\u003e\n\u003ctd data-label=\"What to test directly\"\u003eWhether playback stutters or audio is delayed with footage from actual work\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Check\"\u003eOutput\u003c/td\u003e\n\u003ctd data-label=\"What to test directly\"\u003eWhether the exported video's colors, subtitles, and sound match what you intended\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Check\"\u003eResuming work\u003c/td\u003e\n\u003ctd data-label=\"What to test directly\"\u003eWhether you can reopen a saved project and continue working\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Check\"\u003eExisting workflow\u003c/td\u003e\n\u003ctd data-label=\"What to test directly\"\u003eWhether the app supports the plugins and interchange formats you need\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003ch2\u003e\n\u003ca href=\"#how-cli-and-mcp-change-the-way-apps-are-used\" class=\"anchor\" id=\"how-cli-and-mcp-change-the-way-apps-are-used\"\u003e\u003c/a\u003eHow CLI and MCP change the way apps are used\u003c/h2\u003e\n\u003cp\u003eCLI and MCP provide ways to operate apps other than clicking through an interface. According to PhotoCraft's description, multiple interfaces call the same engine. Those interfaces are UI, CLI, a JSON control channel, and MCP. The structure is documented in the \u003ca href=\"https://github.com/storytold/photocraft\"\u003ePhotoCraft README\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eThis provides a basis for AI to call app features as individual tasks. The agent is responsible for turning a natural-language request into actual commands. A separate process is needed to check the results.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eWay to operate the app\u003c/th\u003e\n\u003cth\u003eSuitable tasks\u003c/th\u003e\n\u003cth\u003eWhat to check\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Way to operate the app\"\u003eOn-screen UI\u003c/td\u003e\n\u003ctd data-label=\"Suitable tasks\"\u003eEditing that requires visual judgment\u003c/td\u003e\n\u003ctd data-label=\"What to check\"\u003eWhether the preview matches the final result\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Way to operate the app\"\u003eCLI\u003c/td\u003e\n\u003ctd data-label=\"Suitable tasks\"\u003eRepetitive tasks and running scripts\u003c/td\u003e\n\u003ctd data-label=\"What to check\"\u003eInput options and exit status\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Way to operate the app\"\u003eMCP\u003c/td\u003e\n\u003ctd data-label=\"Suitable tasks\"\u003eTasks combined by an AI agent\u003c/td\u003e\n\u003ctd data-label=\"What to check\"\u003eFeatures called and verification of the results\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eThere is not enough evidence here to predict the disappearance of the UI. People may still need to inspect results visually. Automation and visual editing interfaces can be used together.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#common-mistakes-when-understanding-rea\" class=\"anchor\" id=\"common-mistakes-when-understanding-rea\"\u003e\u003c/a\u003eCommon mistakes when understanding REA\u003c/h2\u003e\n\u003cp\u003eConfusing REA's analysis capabilities with the ability to copy a finished product leads to misunderstandings. The number of tools alone also says little about analysis quality. Each of the following claims needs separate evidence.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eCommon claim\u003c/th\u003e\n\u003cth\u003eWhat to check separately\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Common claim\"\u003eIt reconstructs any app in minutes\u003c/td\u003e\n\u003ctd data-label=\"What to check separately\"\u003eMeasurements for each target, analysis scope, and environment\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Common claim\"\u003eThere are always 126 tools\u003c/td\u003e\n\u003ctd data-label=\"What to check separately\"\u003eThe actual tool list for the installed version\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Common claim\"\u003eEvidence prevents hallucinations\u003c/td\u003e\n\u003ctd data-label=\"What to check separately\"\u003eThe difference between recording evidence and interpreting it accurately\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Common claim\"\u003eBuilding it in Rust always makes it fast\u003c/td\u003e\n\u003ctd data-label=\"What to check separately\"\u003eProcessing performance measured in actual work\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Common claim\"\u003eIf the interface looks the same, the features are the same\u003c/td\u003e\n\u003ctd data-label=\"What to check separately\"\u003eTests that include saving, compatibility, and output\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Common claim\"\u003eSeparating agents makes it a legal clean-room implementation\u003c/td\u003e\n\u003ctd data-label=\"What to check separately\"\u003eHow access is separated and which terms of use apply\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eYou can check the tool list with \u003ccode\u003etools/list\u003c/code\u003e for the installed version. You also need to check whether each tool can be used for the task at hand. The relevant criteria are explained in the \u003ca href=\"https://github.com/morluto/rea/blob/main/docs/mcp-contracts.md\"\u003eMCP specification\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eA GitHub trending ranking needs a collection time and period. A developer's motivation should also be verified against their original statement. The claim that the project began because of an early termination fee was not accepted as a verified fact.\u003c/p\u003e\n\u003cp\u003eThe claim that Claude Opus 5.5 was used also requires separate development records. The fact that an app is public does not prove which model was used. Check that claim against the developer's work records or original announcement.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#conditions-for-clean-room-reimplementation\" class=\"anchor\" id=\"conditions-for-clean-room-reimplementation\"\u003e\u003c/a\u003eConditions for clean-room reimplementation\u003c/h2\u003e\n\u003cp\u003eClean-room reimplementation separates access to information between analysis and implementation. The role of producing a functional specification is separated from the role of writing new code. Putting agents in different chat windows is not enough.\u003c/p\u003e\n\u003cp\u003eThe REA installation documentation explains restrictions on file and network access. These are intended to prevent the implementation environment from accessing analysis outputs. The separation method is described in the \u003ca href=\"https://github.com/morluto/rea/blob/main/docs/installation.md\"\u003eInstallation and setup documentation\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eThe REA DISCLAIMER does not guarantee the accuracy of results. Obtaining analysis results does not grant rights to the original program, either. Rights and terms of use must be checked for each program. The scope of these limitations is stated in the \u003ca href=\"https://github.com/morluto/rea/blob/main/DISCLAIMER.md\"\u003eREA DISCLAIMER\u003c/a\u003e.\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp\u003eDecompilation, reconstruction, heuristics, and AI-assisted analysis may be incomplete or incorrect.\u003c/p\u003e\n\u003cp\u003eREA DISCLAIMER, Analysis results and generated output\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003cp\u003eThis means AI analysis may be incomplete or incorrect. Calling a process clean-room does not automatically make it lawful. If you plan to publish or commercialize a result, check the target's terms of use first.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#the-difference-between-local-analysis-and-sending-data-to-ai\" class=\"anchor\" id=\"the-difference-between-local-analysis-and-sending-data-to-ai\"\u003e\u003c/a\u003eThe difference between local analysis and sending data to AI\u003c/h2\u003e\n\u003cp\u003eLocal analysis does not mean that no information is sent externally. REA says it processes target files locally. An agent that receives tool results is subject to the model provider's policies. This distinction is explained in the \u003ca href=\"https://github.com/morluto/rea\"\u003eREA FAQ\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eAnalysis results may contain strings from inside files. Execution logs may include account information. If you are investigating a work app, check these points first.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003ePersonal and confidential information that may be included in analysis results\u003c/li\u003e\n\u003cli\u003eTool output the agent sends to the model provider\u003c/li\u003e\n\u003cli\u003eThe model service's storage, training, and retention policies\u003c/li\u003e\n\u003cli\u003eWho may receive analysis reports and logs\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eA target may also contain instructions intended to deceive the AI. The REA documentation says to treat these as untrusted data. Instructions inside a file must not be accepted as commands from the user. The handling principle is in the \u003ca href=\"https://github.com/morluto/rea/blob/main/docs/mcp-contracts.md\"\u003eMCP specification\u003c/a\u003e.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#steps-for-direct-verification\" class=\"anchor\" id=\"steps-for-direct-verification\"\u003e\u003c/a\u003eSteps for direct verification\u003c/h2\u003e\n\u003cp\u003eStart by defining a narrow feature to reproduce. A goal of understanding an entire app has unclear completion criteria. Setting an input and expected result makes it easier to judge whether the analysis is useful.\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003eChoose a program you are authorized to analyze.\u003c/li\u003e\n\u003cli\u003eDefine the feature to check and the test input.\u003c/li\u003e\n\u003cli\u003eRecord the versions of REA and the analyzer.\u003c/li\u003e\n\u003cli\u003eSave supporting evidence and unverified items separately.\u003c/li\u003e\n\u003cli\u003eIn an authorized environment, compare actual behavior with the analysis results.\u003c/li\u003e\n\u003cli\u003eIf you reimplemented the feature, compare the results using the same input.\u003c/li\u003e\n\u003cli\u003eRecord inputs that failed and conditions that are not supported.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eYou can also record a hash of the target file in the report. A hash is a value used to distinguish whether files are the same. Keeping the version and test conditions makes it easier for others to verify the results again.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#where-does-software-retain-its-competitive-value\" class=\"anchor\" id=\"where-does-software-retain-its-competitive-value\"\u003e\u003c/a\u003eWhere does software retain its competitive value?\u003c/h2\u003e\n\u003cp\u003eEven if reimplementation becomes easier, not all of a product's value can be copied. Analyzing a client does not, by itself, provide access to server data. User relationships and the ability to operate a service are separate too.\u003c/p\u003e\n\u003cp\u003eThe public documentation suggests that the basis for competition may change. How quickly features are implemented alone will become a less useful measure. Verifiable quality and operational capability also need to be considered.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eCompetitive factor\u003c/th\u003e\n\u003cth\u003eWhat REA and reimplementation examples show\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Competitive factor\"\u003eFeature implementation\u003c/td\u003e\n\u003ctd data-label=\"What REA and reimplementation examples show\"\u003eIt is becoming easier to connect tools that investigate existing behavior\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Competitive factor\"\u003eProduct maturity\u003c/td\u003e\n\u003ctd data-label=\"What REA and reimplementation examples show\"\u003eThe existence of features and readiness for professional work need separate assessments\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Competitive factor\"\u003eAccess to automation\u003c/td\u003e\n\u003ctd data-label=\"What REA and reimplementation examples show\"\u003eCallable interfaces such as CLI and MCP expand the ways a product can be used\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Competitive factor\"\u003eService operations\u003c/td\u003e\n\u003ctd data-label=\"What REA and reimplementation examples show\"\u003eServer data and user relationships must be built separately\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eThis table is an interpretation based on official documentation. It is not a measurement of changes in revenue across the market. The effect on each company may vary with its product quality and operational structure.\u003c/p\u003e\n","tags":["Context Engineering","AI Agents","AI Development","Technology strategy","Development Tools"],"faqs":[{"question":"Does REA recover the original source code?","answer":"It does not guarantee recovery of source code identical to the original. Native analysis provides clues such as pseudocode and instructions. The agent uses these to explain behavior or write an implementation."},{"question":"Do I need Ghidra to use REA?","answer":"It depends on what you are analyzing. Native analysis uses tools such as Ghidra, Hopper, and IDA. Static JavaScript and .NET analysis can be done without a native analysis tool."},{"question":"Does REA have 126 tools?","answer":"It is difficult to treat that as a fixed number without specifying a version. Check the list in tools/list for the version you installed. Some listed tools may not be available in your current environment."},{"question":"Can I trust an AI explanation if there is an Evidence record?","answer":"Evidence helps track the supporting evidence and limitations. An interpretation can still be wrong even when a record exists. Verify important conclusions by running the software or conducting separate tests."},{"question":"Are REA and ArtCraft the same tool?","answer":"They are different projects. REA connects reverse engineering tools and agents. ArtCraft's Crafting Apps perform editing tasks involving images, videos, documents, and other content."},{"question":"Can I start using FilmCraft instead of Premiere Pro right away?","answer":"First, check the compatibility and output quality your work requires. FilmCraft's official documentation describes its alpha status and functional limitations. On October 10, 2026, its own estimate of readiness for practical use was about 56%."},{"question":"Does FilmCraft's 86% feature coverage mean its performance is the same?","answer":"No, it does not mean the performance is the same. The approximately 86% figure from October 10, 2026, is a self-assessment of the scope of implemented features. It is not a measure of processing speed or error rate."},{"question":"Does support for CLI and MCP make a graphical UI unnecessary?","answer":"More ways to automate tasks do not make a UI unnecessary. Visual editing or checking results may require a screen. You can use multiple ways to control the software together, depending on the task."},{"question":"Does analyzing locally keep company information from being sent outside the company?","answer":"Local analysis and data transmission by the agent are separate matters. Tool results may be sent to an external model service. Check the settings of the agent you use and the provider's data policy."},{"question":"Does separating AI agents complete a clean-room reimplementation?","answer":"Dividing up roles alone is not enough. You must also separate the implementation environment's access to files and networks. This technical separation does not automatically guarantee legality."},{"question":"Can REA alone copy a server's data and code?","answer":"Client analysis alone cannot reveal everything inside a server. Observed requests and responses provide only limited clues. They are not evidence of the server's entire private implementation or all its data."},{"question":"Is this article based on firsthand experience using REA and ArtCraft?","answer":"This is a technical explanation based on official documentation. The apps were not run, and no performance tests were conducted. It presents published feature descriptions separately from the development team's own assessments."}],"sources":[{"url":"https://github.com/morluto/rea","title":"REA README: Supported targets, how it works, FAQ","type":"source"},{"url":"https://github.com/NationalSecurityAgency/ghidra","title":"Ghidra Software Reverse Engineering Framework","type":"source"},{"url":"https://github.com/morluto/rea/blob/main/docs/cli.md","title":"REA CLI and Evidence","type":"source"},{"url":"https://github.com/morluto/rea/blob/main/docs/mcp-contracts.md","title":"REA MCP runtime contracts","type":"source"},{"url":"https://github.com/morluto/rea/blob/main/docs/installation.md","title":"REA Installation and setup","type":"source"},{"url":"https://github.com/morluto/rea/blob/main/DISCLAIMER.md","title":"REA DISCLAIMER: Scope of use and limitations of analysis results","type":"source"},{"url":"https://getartcraft.com/apps","title":"Official list of ArtCraft Crafting Apps","type":"source"},{"url":"https://github.com/storytold/filmcraft","title":"FilmCraft README: Features, alpha status, and self-assessment on October 10, 2026","type":"data_point"},{"url":"https://github.com/storytold/photocraft","title":"PhotoCraft README: Editing engine and agent control","type":"source"}],"images":[{"id":1962,"url":"https://injoys.com/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6MzAxOTUsInB1ciI6ImJsb2JfaWQifX0=--945925f39590e27477cbcb5280f3e9984ab90869/ai-ed2a455d.webp","is_representative":true,"generation_method":"ai_photo","license":"ai_generated","mime_type":"image/webp","width":1536,"height":1024,"translations":{"ko":{"alt":"검은 스웨터를 입은 남성이 두 미리보기 화면과 편집 타임라인이 표시된 태블릿을 살펴본다.","caption":"기능을 재현했다고 해서 실무에 쓸 수 있는 완성품이 되는 것은 아닙니다.","description":null},"en":{"alt":"A man in a dark sweater studies a tablet showing two video previews and an editing timeline.","caption":"Recreating features does not guarantee a production-ready replica.","description":null},"ja":{"alt":"黒いセーターの男性が、二つの映像プレビューと編集タイムラインを表示したタブレットを見つめる。","caption":"機能を再現できても、実務で使える完成品になるとは限りません。","description":null},"es":{"alt":"Un hombre con un suéter oscuro observa una tableta con dos vistas previas de vídeo y una línea de tiempo de edición.","caption":"Recrear funciones no garantiza una réplica lista para el uso profesional.","description":null},"id":{"alt":"Pria bersweter gelap mengamati tablet yang menampilkan dua pratinjau video dan linimasa penyuntingan.","caption":"Mereplikasi fitur tidak menjamin hasil yang siap dipakai untuk pekerjaan nyata.","description":null},"pt":{"alt":"Um homem de suéter escuro observa um tablet com duas prévias de vídeo e uma linha do tempo de edição.","caption":"Recriar funcionalidades não garante uma réplica pronta para uso profissional.","description":null},"zh-hant":{"alt":"穿深色毛衣的男子查看平板上的兩個影片預覽畫面和剪輯時間軸。","caption":"重現功能不代表複製品已達到實務使用的完成度。","description":null},"de":{"alt":"Ein Mann im dunklen Pullover betrachtet ein Tablet mit zwei Videovorschauen und einer Schnitt-Timeline.","caption":"Nachgebildete Funktionen garantieren noch keine praxistaugliche Kopie.","description":null}}},{"id":1963,"url":"https://injoys.com/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6MzAyMDEsInB1ciI6ImJsb2JfaWQifX0=--9d6b6cad7c57d623804982aaeddbe8270740975f/ai-33a9acb5.webp","is_representative":false,"generation_method":"ai_semi","license":"ai_generated","mime_type":"image/webp","width":1536,"height":1024,"translations":{"ko":{"alt":"파란 스웨터를 입은 여성이 모니터를 보고, 유리벽 너머 남성도 컴퓨터로 작업한다. 두 사람 사이에 연결망 그래픽이 겹쳐 있다.","caption":"REA는 AI 에이전트를 기존 분석 도구와 연결해 소프트웨어 조사를 돕습니다.","description":null},"en":{"alt":"A woman in a blue sweater faces a monitor while a man works behind glass, with a network graphic overlaid between them.","caption":"REA connects AI agents with existing analysis tools to help investigate software.","description":null},"ja":{"alt":"青いセーターの女性がモニターを見つめ、ガラス越しに男性が作業する。二人の間にネットワーク図が重なる。","caption":"REAはAIエージェントを既存の解析ツールにつなぎ、ソフトウェアの調査を支援します。","description":null},"es":{"alt":"Una mujer con jersey azul mira un monitor mientras un hombre trabaja tras un cristal; entre ambos aparece una red de nodos.","caption":"REA conecta agentes de IA con herramientas de análisis existentes para facilitar el estudio del software.","description":null},"id":{"alt":"Perempuan bersweter biru menatap monitor, sementara pria bekerja di balik kaca; grafis jaringan tampak di antara mereka.","caption":"REA menghubungkan agen AI dengan alat analisis yang sudah ada untuk membantu menyelidiki perangkat lunak.","description":null},"pt":{"alt":"Uma mulher de blusa azul olha para um monitor enquanto um homem trabalha atrás do vidro, com uma rede gráfica entre eles.","caption":"O REA conecta agentes de IA a ferramentas de análise existentes para ajudar a investigar softwares.","description":null},"zh-hant":{"alt":"穿藍色毛衣的女子看著螢幕，男子在玻璃隔間另一側工作，兩人之間疊有網絡節點圖形。","caption":"REA將AI代理與既有分析工具連接，協助調查軟體。","description":null},"de":{"alt":"Eine Frau im blauen Pullover blickt auf einen Monitor, während ein Mann hinter Glas arbeitet; dazwischen liegt eine Netzgrafik.","caption":"REA verbindet KI-Agenten mit bestehenden Analysewerkzeugen, um Software zu untersuchen.","description":null}}}],"published_at":"2026-10-19T23:23:10+09:00","updated_at":"2026-10-19T23:23:10+09:00","license":"cc_by","translation_status":"reviewed","available_locales":["ko","en","ja","es"],"data_locales":["ko","en","ja","es","id","pt","zh-hant","de"],"url":"https://injoys.com/en/articles/rea-ai-reverse-engineering-capabilities-and-limits"}