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Issue #377 - Deep Web Content Extraction Module

Changes Proposed

  • Added comprehensive deep web content extraction framework with modular architecture
  • Implemented 10 specialized extractors for different types of dark web intelligence gathering
  • Integrated deep extraction functionality into main TorBot CLI
  • Updated project dependencies to support advanced NLP and pattern matching capabilities
  • Enhanced OSINT capabilities for Tor hidden services analysis

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 and ExtractionResult data structure
  • orchestrator.py: Main DeepExtractor class that coordinates all specialized extractors and manages the extraction pipeline

Specialized Extractors (10 modules)

  1. breach_detector.py: Detects and analyzes data breach indicators, leaked credentials patterns
  2. communication_extractor.py: Extracts communication channels (email, Jabber, IRC, etc.)
  3. credentials_extractor.py: Identifies credentials, API keys, tokens, and authentication data
  4. crypto_extractor.py: Extracts cryptocurrency addresses and payment information
  5. hidden_services_extractor.py: Discovers and catalogs .onion links and hidden services
  6. linguistic_analyzer.py: Performs NLP-based content analysis and language pattern detection
  7. marketplace_extractor.py: Identifies marketplace-specific data (products, vendors, pricing)
  8. pii_extractor.py: Extracts Personally Identifiable Information
  9. threat_indicators_extractor.py: Detects IOCs (Indicators of Compromise) and threat intelligence

Integration

  • Modified main.py to add deep extraction CLI commands
  • Updated requirements.txt with necessary dependencies for NLP, pattern matching, and data extraction
  • Updated pyproject.toml to reflect new module dependencies
  • Cleaned up deprecated code in info.py

Statistics

  • 3,113 insertions across 16 files
  • Fully modular and extensible architecture
  • Each extractor operates independently with consistent interface

Screenshots of new feature/change

@vaishcodescape
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New Feature added successfully @KingAkeem Can you review and merge it ?
Thanks : )

@KingAkeem
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@vaishcodescape This merge request is too large, you need to break this down into smaller chunks that separates the areas of concern. (e.g. dependency updates vs. functional updates). Also provide ways to test each merge request, thank you.

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2 participants