feat:Dark Web Extraction feature #378
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Issue #377 - Deep Web Content Extraction Module
Changes Proposed
Explanation of Changes
This PR introduces a complete Deep Web Content Extraction Module that significantly enhances TorBot's OSINT capabilities for analyzing dark web content. The implementation consists of:
Core Architecture
base.py: Abstract base class (BaseExtractor) defining the extraction interface andExtractionResultdata structureorchestrator.py: MainDeepExtractorclass that coordinates all specialized extractors and manages the extraction pipelineSpecialized Extractors (10 modules)
breach_detector.py: Detects and analyzes data breach indicators, leaked credentials patternscommunication_extractor.py: Extracts communication channels (email, Jabber, IRC, etc.)credentials_extractor.py: Identifies credentials, API keys, tokens, and authentication datacrypto_extractor.py: Extracts cryptocurrency addresses and payment informationhidden_services_extractor.py: Discovers and catalogs .onion links and hidden serviceslinguistic_analyzer.py: Performs NLP-based content analysis and language pattern detectionmarketplace_extractor.py: Identifies marketplace-specific data (products, vendors, pricing)pii_extractor.py: Extracts Personally Identifiable Informationthreat_indicators_extractor.py: Detects IOCs (Indicators of Compromise) and threat intelligenceIntegration
main.pyto add deep extraction CLI commandsrequirements.txtwith necessary dependencies for NLP, pattern matching, and data extractionpyproject.tomlto reflect new module dependenciesinfo.pyStatistics
Screenshots of new feature/change