Offline macOS App Data Extraction
Budget: $2 – $8 USD
Role Description
We're looking for an experienced reverse engineering specialist to extract offline medical education data from a macOS application. If you have strong skills in macOS internals, browser-based storage systems, and application analysis, this project might be perfect for you.
Project Overview:
We need to extract downloaded QBank (question bank) content from a macOS medical education application. The data is stored locally on the device after download, but uses non-standard storage formats (IndexedDB/LevelDB) rather than traditional databases like SQLite. Your task will be to analyze the app's container directory, understand the storage structure, and extract all QBank content into a clean, structured format.
Scope of Work:
Analyze macOS application container directory and local storage files
Examine IndexedDB/LevelDB or similar browser-based storage implementations
Reverse engineer the storage structure to understand data encoding/organization
Work without access to the application's encryption key (requires analyzing app logic)
Extract complete offline QBank dataset including:
Questions and answer choices
Correct answers and explanations
Associated metadata (exam names, subjects, topics, IDs, etc.)
Deliver data in structured JSON or CSV format with extraction documentation
Required Skills & Experience:
macOS file system architecture and application container directories
IndexedDB, LevelDB, or similar browser-based storage systems
Reverse engineering techniques for desktop applications
Data extraction, decoding, and structuring methodologies
Experience with binary data analysis and custom format parsing
Familiarity with medical/educational content structures (preferred)
Deliverables:
Complete structured dataset in JSON/CSV format
Clear documentation of extraction methodology
Summary of data structure and organization
Important Notes:
Only local, already-downloaded data will be accessed
No server-side access, account bypassing, or network interaction required
Strictly technical data extraction from local storage only
How to Apply:
Please include in your proposal:
Examples of similar data extraction or reverse engineering projects
Your experience with macOS applications and browser-based storage
Your approach to this specific challenge
Estimated timeline
We're looking for an experienced reverse engineering specialist to extract offline medical education data from a macOS application. If you have strong skills in macOS internals, browser-based storage systems, and application analysis, this project might be perfect for you.
Project Overview:
We need to extract downloaded QBank (question bank) content from a macOS medical education application. The data is stored locally on the device after download, but uses non-standard storage formats (IndexedDB/LevelDB) rather than traditional databases like SQLite. Your task will be to analyze the app's container directory, understand the storage structure, and extract all QBank content into a clean, structured format.
Scope of Work:
Analyze macOS application container directory and local storage files
Examine IndexedDB/LevelDB or similar browser-based storage implementations
Reverse engineer the storage structure to understand data encoding/organization
Work without access to the application's encryption key (requires analyzing app logic)
Extract complete offline QBank dataset including:
Questions and answer choices
Correct answers and explanations
Associated metadata (exam names, subjects, topics, IDs, etc.)
Deliver data in structured JSON or CSV format with extraction documentation
Required Skills & Experience:
macOS file system architecture and application container directories
IndexedDB, LevelDB, or similar browser-based storage systems
Reverse engineering techniques for desktop applications
Data extraction, decoding, and structuring methodologies
Experience with binary data analysis and custom format parsing
Familiarity with medical/educational content structures (preferred)
Deliverables:
Complete structured dataset in JSON/CSV format
Clear documentation of extraction methodology
Summary of data structure and organization
Important Notes:
Only local, already-downloaded data will be accessed
No server-side access, account bypassing, or network interaction required
Strictly technical data extraction from local storage only
How to Apply:
Please include in your proposal:
Examples of similar data extraction or reverse engineering projects
Your experience with macOS applications and browser-based storage
Your approach to this specific challenge
Estimated timeline