ThreatCipher

Advanced Security Intelligence & Threat Detection System

GPUAccelerated Search
Multi-StageDetection Engine
Real-timeProcessing
ACTIVEProject Status

Live System Demo

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Project Overview

ThreatCipher is a security intelligence system designed for real-time threat detection and risk assessment. Built with Flask and powered by GPU acceleration (CuPy, NumPy), the system processes large-scale databases to identify potential security threats using advanced hash-based indexing and multi-stage search algorithms.

It features a multi-threaded architecture that supports both manual queries and bulk file processing. This allows security operations to receive actionable intelligence through advanced analytics, risk scoring, and comprehensive reporting.

Key Features & Capabilities

  • GPU-accelerated search engine with hash-based indexing for rapid lookups.
  • Multi-stage detection: Stage 1 (ID/Contact), Stage 2 (Name Components), Stage 3 (Full Name).
  • Advanced batch processing with concurrent threading for CSV and Excel files.
  • Intelligent keyword filtering with customizable ignore lists for enhanced accuracy.
  • Real-time risk assessment with country-based analytics and threat scoring.
  • Comprehensive reporting with PDF and Excel export, featuring detailed visualizations.
  • RESTful API endpoints for seamless integration with external security systems.

Technical Implementation

The system employs a hash-based indexing architecture that pre-processes database records into optimized hash tables for fast searches. Built on Flask with CuPy for GPU acceleration, it handles whole-value and segmented (comma/space-separated) data parsing for comprehensive threat identification.

Multi-threading via `ThreadPoolExecutor` enables concurrent batch operations, while the analytics engine provides real-time risk scoring based on match patterns, geographical indicators, and threat intelligence data.

System Architecture

A multi-threaded Flask architecture with GPU acceleration, hash-based indexing, and an advanced analytics pipeline.

ThreatCipher System Architecture Diagram A flow diagram showing the data pipeline from input to analytics in the ThreatCipher system. DATA INPUT LAYER Excel DBs XLSX/XLS Upload Files CSV/XLSX Manual Query REST API HASH INDEXING ENGINE Pre-processing & Hash Generation Whole values | Comma-separated | Space-separated Hash Tables Fast Lookup Record Map ID Tracking GPU Acceleration (CuPy + NumPy) MULTI-STAGE DETECTION Stage 1 NIC Passport Phone ID Match Stage 2 First Name OR Last Name Name OR Stage 3 First Name AND Last Name Full Match THREADING ENGINE ThreadPoolExecutor Max 4 Workers | Concurrent Processing Batch Proc 5K chunks Progress TQDM ANALYTICS & REPORTING ENGINE Risk Scoring Match Count Country Analysis Pattern Detection Low|Med|High Statistics Term Frequency Entry Analytics Visualizations Charts & Graphs PDF Reports ReportLab Threat Intel Detailed Analysis Export Ready Excel Export OpenPyXL Multi-sheets Formatted Data Business Ready FLASK API LAYER RESTful API Endpoints JSON API /check endpoint File Upload Multi-format ⚡ Hash-Based Indexing 🔍 3-Stage Detection 🧠 GPU Acceleration 📊 Real-time Analytics 🚀 Multi-threaded

Key Results & Impact

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Precision Detection

Hash-based indexing and multi-stage algorithms ensure accurate threat identification with minimal false positives.

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High Performance

GPU acceleration and concurrent processing deliver sub-second search times across millions of records.

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Actionable Intelligence

Comprehensive reports with risk scoring and country analysis are generated in PDF and Excel formats.

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Scalable Architecture

The multi-threaded Flask framework and RESTful API support large-scale security operations and external integrations.

Explore More

Dive deeper into the implementation and capabilities of the ThreatCipher system.

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