Comprehensive OSINT toolkit for authorized investigations
Inspired by: github.com/osintambition/Social-Media-OSINT-Tools-Collection
Multi-platform background investigation tool
- ✅ Search across 10 social media platforms
- ✅ People search databases (Whitepages, Spokeo, TruePeopleSearch, Pipl)
- ✅ Phone number reverse lookup
- ✅ Email address investigation
- ✅ Location-based searching
- ✅ Cross-reference analysis
- ✅ Confidence scoring
- ✅ Comprehensive reporting
- Ultimate Scraper - Network interception, API capture
- Activity Scraper - Complete activity tracking, liked videos, comments
- Advanced Scraper - Deep JSON extraction, comprehensive analysis
- Basic Scraper - Quick profile checks
- Profile Analysis - Complete public profile data
- Post Extraction - All visible posts with metadata
- Engagement Analytics - Performance metrics, patterns
⚠️ Note: Liked posts are private (cannot be scraped)
# Clone repository
git clone https://github.com/husseytaylor/scrape.git
cd scrape
# Create virtual environment (recommended)
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Install browsers
playwright install chromium
python osint_background_checker.py
Edit the parameters in the script:
investigation_params = {
'full_name': 'John Doe', # Person's full name
'username': 'johndoe', # Known username
'birthday': '1990-01-15', # Birthday (optional)
'phone': '+1-555-0000', # Phone number (optional)
'hometown': 'Chicago, IL', # Location (optional)
'email': '[email protected]' # Email (optional)
}
Capabilities:
- Searches 10 social media platforms
- Checks 4+ people search databases
- Reverse phone/email lookup
- Cross-platform analysis
- Confidence scoring
python tiktok_activity_scraper.py
Captures:
- All posted videos
- Liked videos (if public)
- Engagement metrics
- Hashtag analysis
- Comment activity
python instagram_scraper.py
Captures:
- Profile information
- Public posts
- Engagement metrics
- Top performing content
Tool | Description | Use Case | Difficulty |
---|---|---|---|
osint_background_checker.py |
Multi-platform OSINT | Background checks, investigations | 🟢 Easy |
tiktok_activity_scraper.py |
Complete TikTok activity | Full user activity analysis | 🟢 Easy |
tiktok_ultimate_scraper.py |
Network interception | Maximum data capture | 🟡 Medium |
tiktok_advanced_scraper.py |
Deep JSON extraction | Comprehensive profiles | 🟡 Medium |
tiktok_scraper.py |
Basic TikTok scraping | Quick profile checks | 🟢 Easy |
instagram_scraper.py |
Instagram profiles | Public post analysis | 🟢 Easy |
tiktok_json_parser.py |
Parse captured JSON | Data analysis | 🟢 Easy |
advanced_social_osint_scraper.py |
Cross-platform framework | Multi-platform tracking | 🟡 Medium |
✅ Social media profiles (10 platforms)
✅ People search database records
✅ Phone number associations
✅ Email account connections
✅ Location-based mentions
✅ Cross-platform verification
✅ Confidence scores
✅ All posted videos (with metadata)
✅ Liked videos (if public)
✅ Follower/following counts
✅ Engagement metrics
✅ Hashtag patterns
✅ Music usage
✅ Comment activity
✅ Profile information
✅ Public posts (~30 without login)
✅ Engagement metrics
✅ Hashtag analysis
❌ Liked posts (PRIVATE - impossible)
Found on 6/10 platforms:
- ✅ Instagram (1,952 followers)
- ✅ GitHub
- ✅ Snapchat
Confidence: 90% username match
Digital Footprint: High visibility
Investigation Time: 3 minutes
Captured:
- 18 videos with full metadata
- 9 liked videos
- Engagement rate: 7.8%
- Top hashtags: #fyp, #butter, #zlam
Captured:
- 27 posts
- 1,952 followers
- Avg 268 likes/post
- 13.7% engagement rate
1. Run OSINT background checker
2. Identify which platforms person uses
3. Get basic statistics
1. Use TikTok activity scraper if found on TikTok
2. Use Instagram scraper if found on Instagram
3. Capture detailed content and engagement
1. Review cross-platform data
2. Identify patterns and connections
3. Verify information across sources
4. Generate confidence scores
1. Compile findings
2. Generate JSON and text reports
3. Document sources
4. Note confidence levels
Total Time: 10-20 minutes for comprehensive investigation
- Checks 10 social media platforms
- Finds matching profiles
- Extracts available data
- Google advanced searches
- People search databases
- Location-based filtering
- Name variation matching
- Reverse phone lookup
- Social media association (Facebook, etc.)
- Carrier information
- Location data
- Account association check
- Social media connections
- Breach database checking
- Domain analysis
- Name + location searches
- Local database queries
- Geographic filtering
- Community mentions
# In osint_background_checker.py
investigation_params = {
'full_name': 'Target Name',
'username': 'target_username',
'birthday': '1990-01-01',
'phone': '+1-555-0000',
'hometown': 'City, State',
'email': '[email protected]'
}
# Check specific platforms only
platforms = ['instagram', 'tiktok', 'linkedin']
# Or check all platforms
platforms = None
# For automated/background operation
checker = OSINTBackgroundChecker(headless=True)
# For watching the process
checker = OSINTBackgroundChecker(headless=False)
- OSINT Background Checker Guide - Complete OSINT documentation
- TikTok Activity Guide - TikTok scraping guide
- Instagram Guide - Instagram limitations & capabilities
- Snapchat Guide - Snapchat scraping (very difficult)
- Example Results - Sample investigation results
✅ Pre-employment screening (with consent)
✅ Investigative journalism
✅ Security research
✅ Law enforcement (with authority)
✅ Fraud investigation
✅ Missing persons cases
❌ Stalking or harassment
❌ Identity theft
❌ Doxxing
❌ Privacy violations
❌ Unauthorized surveillance
❌ Data broker scraping for profit
- GDPR (EU data subjects)
- CCPA (California residents)
- FCRA (employment screening)
- COPPA (minors)
- Platform Terms of Service
You are responsible for ensuring your use complies with all applicable laws.
- Encrypt sensitive reports
- Use secure storage
- Delete when no longer needed
- Don't share unnecessarily
- Follow data retention policies
- Use VPN when appropriate
- Rotate user agents
- Implement rate limiting
- Avoid account bans
- Document methodology
- Username Search: 80-90% accuracy
- Name Search: 50-70% accuracy
- Phone/Email: 60-80% accuracy
- Cross-Platform: 70-90% confidence
- TikTok: ~70-90% of public data
- Instagram: ~60-70% (login wall limits)
- LinkedIn: ~40-50% (requires auth)
- Twitter: ~70-80% of public data
- Overall: ~65-75% comprehensive capture
Contributions welcome! Areas for improvement:
- Additional platform support
- Better captcha handling
- Authentication modules
- Data visualization
- Export formats
- Analysis algorithms
For educational and authorized use only.
Users assume all legal responsibility for their use of these tools.
Respect:
- Privacy laws
- Platform Terms of Service
- Individual privacy rights
- Ethical boundaries
- 5 TikTok scrapers
- 1 Instagram scraper
- 1 OSINT background checker
- 1 Cross-platform OSINT framework
- 3 Utility/analysis tools
- Complete usage documentation
- Platform-specific guides
- Example investigations
- Legal considerations
- TikTok: @.wabby (18 videos, 9 likes)
- Instagram: @abby.barger (27 posts)
- OSINT: Abby Barger (6 platforms found)
For questions or issues:
- Check documentation in
/docs
folder - Review example data files
- Consult guide files (*.md)
Created: October 2025
Repository: github.com/husseytaylor/scrape
Inspired By: OSINT Ambition
Status: ✅ Production Ready