Enterprise Anti-Scam System: Aggregator of 11+ security services and A
Project Description
Main Concept:
Development of a high-load ecosystem to protect users from digital fraud in Ukraine. The system provides cascading real-time verification of objects through integration with leading global cybersecurity services.
Key Functionality:
Multi-API Aggregation: Simultaneous verification through 11+ independent sources (VirusTotal, Google Safe Browsing, AbuseIPDB, PhishTank, and others).
Intelligent Risk Score: Proprietary risk assessment system (0–100 points) based on a combination of reputation databases, technical parameters of domains, and AI analysis.
Comprehensive OSINT Search: Automated verification of Ukrainian phone numbers, SMS messages, email addresses, and websites for phishing and data leaks.
AI Phishing Detector: A machine learning-based module for analyzing message text for signs of social engineering (UA/RU/EN).
Technical Specifications and Architecture:
Backend: Built on an asynchronous Python stack (aiogram 3.x) to ensure instant system response.
Infrastructure: Full containerization using Docker and Docker Compose.
Data Management: Use of PostgreSQL for storing logs and Redis for efficient caching of results, reducing API load by ~70%.
Performance: The full cycle of deep verification of an object is completed in just 5–6 seconds.
Scalability: The architecture is ready for horizontal scaling and processing requests from 1,000,000 users.
Result:
A stable production-ready open-source solution has been created, demonstrating skills in building complex enterprise systems and deep expertise in cybersecurity.
Main Concept:
Development of a high-load ecosystem to protect users from digital fraud in Ukraine. The system provides cascading real-time verification of objects through integration with leading global cybersecurity services.
Key Functionality:
Multi-API Aggregation: Simultaneous verification through 11+ independent sources (VirusTotal, Google Safe Browsing, AbuseIPDB, PhishTank, and others).
Intelligent Risk Score: Proprietary risk assessment system (0–100 points) based on a combination of reputation databases, technical parameters of domains, and AI analysis.
Comprehensive OSINT Search: Automated verification of Ukrainian phone numbers, SMS messages, email addresses, and websites for phishing and data leaks.
AI Phishing Detector: A machine learning-based module for analyzing message text for signs of social engineering (UA/RU/EN).
Technical Specifications and Architecture:
Backend: Built on an asynchronous Python stack (aiogram 3.x) to ensure instant system response.
Infrastructure: Full containerization using Docker and Docker Compose.
Data Management: Use of PostgreSQL for storing logs and Redis for efficient caching of results, reducing API load by ~70%.
Performance: The full cycle of deep verification of an object is completed in just 5–6 seconds.
Scalability: The architecture is ready for horizontal scaling and processing requests from 1,000,000 users.
Result:
A stable production-ready open-source solution has been created, demonstrating skills in building complex enterprise systems and deep expertise in cybersecurity.