MAYAVIHIN Deepfake Detection System Version 19

Overview

MAYAVIHIN is a web-based deepfake detection and verification system that analyzes uploaded media files (images, videos, audio) to determine their authenticity using multiple AI analysis agents.

Core Features

Media Upload and Analysis

• Users can upload image, video, or audio files for analysis
• Support for common formats (JPG, PNG, MP4, MP3, WAV)
• File size limits and format validation
• Progress tracking during upload and analysis

Multi-Agent Detection System

The system employs five specialized analysis agents that work in parallel:

1. Visual Forensics Agent - Analyzes images and videos for visual manipulation artifacts
2. Audio Analysis Agent - Detects audio deepfakes and voice cloning artifacts
3. Metadata Agent - Examines file metadata and compression signatures
4. Consistency Agent - Cross-validates results from other agents
5. Explainability Agent - Generates human-readable explanations for detection results

Analysis Results Dashboard

• Overall authenticity verdict (Authentic/Fake/Uncertain)
• Confidence score (0-100%)
• Detailed per-agent results display: Each of the five agents shows individual verdicts (“Real”, “Fake”, “Uncertain”) with corresponding confidence percentages
• Rich explainable AI layout: Visual Forensics, Audio Analysis, Metadata, Consistency, and Explainability agents each display detailed sub-results with human-readable reasoning text and percentage confidence bars
• Multi-agent verdict visualization: Clear display of each agent’s analysis outcome with explanatory text and visual confidence indicators
• Visual indicators highlighting suspicious areas (for images/videos)
• Timeline view for video analysis results

Analysis History

• Users can view their previous analysis requests
• Search and filter past analyses by date, file type, or result
• Export analysis reports

System Logs

• Comprehensive activity logging displaying application events
• Log entries for media uploads, analysis actions, deletions, and system errors
• Scrollable card-based or table layout with columns for timestamp, action type, file name/ID, status, and message details
• Filter and search functionality for quickly locating specific log entries
• Real-time log updates and chronological ordering

Backend Data Storage

• Analysis Records: Store analysis results, confidence scores, agent outputs, and explanations with detailed per-agent verdict data including individual agent confidence scores, reasoning text, and sub-analysis results
• File Metadata: Store original filename, file type, size, upload timestamp
• User Sessions: Track user uploads and analysis history (no authentication required)
• System Logs: Store comprehensive activity logs including timestamps, action types, file references, status codes, and detailed messages

Backend Operations

• Process uploaded media files through the five analysis agents using Version 19 stable analysis implementation
• Generate confidence scores and aggregate results using Version 19 logic
• Store detailed multi-agent analysis data: Persist individual agent verdicts, confidence percentages, and explanatory reasoning for each of the five analysis agents using Version 19 data structures
• Provide rich explainable AI data: Ensure backend returns comprehensive analysis results including per-agent sub-results, human-readable explanations, and confidence metrics using Version 19 format
• Create human-readable explanations for detection results
• Store analysis results and metadata with reliable data persistence using Version 19 implementation
• Retrieve analysis history for users
• Handle file upload and analysis execution using Version 19 stable synchronization
• Restore Version 19 blob handling: Implement the stable file upload and analysis processing logic from Version 19 that prevents “Cannot convert undefined to BigInt” errors
• Version 19 analysis execution: Use the exact analysis processing implementation from Version 19 that successfully handles file uploads and generates proper results
• Execute standard API calls to AI analysis services using Version 19 methods
• Implement Version 19 error handling for analysis operations
• Log all system activities including uploads, analysis completions, errors, and deletions with timestamps and detailed context
• Retrieve system logs with filtering and search capabilities
• Store log entries with proper categorization and status tracking

Backend Implementation Requirements

• Revert to Version 19 Backend Logic: Restore the complete backend implementation from Version 19 that successfully processes file uploads and analysis without BigInt conversion errors
• Version 19 Data Handling: Use the exact data structures, type handling, and processing logic from Version 19
• Stable Analysis Processing: Implement the Version 19 analysis execution flow that properly handles file uploads and generates accurate results
• Version 19 API Responses: Ensure all backend API responses follow the Version 19 format and structure
• Reliable File Processing: Use Version 19’s proven file upload and analysis synchronization that prevents undefined value errors
• Numeric Value Validation and Type Safety: Implement comprehensive validation and safe conversion for all numeric values before storage, ensuring fields like confidence, uploadTime, and timestamp are consistently stored as Nat types
• Defensive Type Checking: Add defensive checks and automatic type normalization for all optional numeric results returned from frontend or model APIs before inserting into the analyses map
• BigInt Conversion Error Prevention: Validate all numeric inputs and provide default values for undefined or null numeric fields to prevent “Cannot convert undefined to BigInt” errors
• Safe Numeric Conversion: Implement safe conversion functions that handle undefined, null, or invalid numeric values by providing appropriate default values or error handling
• Maintain consistent and reliable file upload and analysis execution using Version 19 methods
• Provide standardized success/error responses using Version 19 response formats
• Handle analysis completion with explicit success confirmation using Version 19 logic
• Maintain reliable data persistence using Version 19 implementation
• System Activity Logging: Log all backend operations, errors, and state changes using Version 19 logging implementation

API Response Format

• Use Version 19 API response structure and format
• Ensure all backend API responses follow Version 19 JSON response format
• Multi-agent analysis data structure: Return analysis results using Version 19 data structure for all five agents with individual verdicts, confidence scores, and explanatory text
• Validate response body structure using Version 19 validation logic
• Maintain Version 19 error and success response schemas
• Ensure analysis save operations return properly formatted JSON responses using Version 19 format
• Numeric Field Validation: Ensure all numeric fields in API responses are properly validated and converted to appropriate types before transmission

Frontend Requirements

• Maintain all current frontend UI, layout, and design elements without changes
• Preserve existing file upload, display, and history features exactly as they are
• Keep all current branding, aesthetics, and visual design unchanged
• Ensure proper handling of Version 19 backend responses in frontend API calls
• Display user-friendly error messages when backend operations fail
• Add clear success state feedback for completed operations
• Maintain responsive UI during error states with descriptive error display

User Interface

Design Theme and Aesthetics

• Deep space cosmic theme with dark indigo, violet, and cyan highlights
• Soft glowing gradients of blue and purple harmonizing with the MAYAVIHIN logo
• Smooth light/dark mode toggle functionality
• Subtle glows, smooth transitions, and responsive breakpoints
• Professional cosmic design with luminescent effects
• Dynamic “eye” background animation that activates gently when files are uploaded
• Minimalist, subtle, and ambient eye design positioned in the background (non-intrusive)
• Eye animation synchronized with darker hues and soft gradients to match the cosmic atmosphere

Header Design

• CODE BLOODED logo maintained with crimson glow aesthetic (unchanged)
• MAYAVIHIN logo integrated as the primary application logo without glow effects
• Remove any small “MAYAVIHIN” label/typo text near the main MAYAVIHIN logo while keeping the main logo intact
• Navigation links: Home, Features, About, History, System Logs
• Smooth light/dark mode toggle
• Responsive design across all screen sizes

Homepage Layout

• Hero section with MAYAVIHIN logo (no glow effects, no additional text labels)
• Animated text rotation: “Detect”, “Verify”, “Explain”, “Protect”
• Interactive buttons: “Upload Media” and “View History”
• Feature highlights section showcasing AI capabilities
• Dynamic eye background animation that responds to file uploads

Page Structure and Routing

• Home Page: Main hero section with logo, upload modal trigger, feature highlights
• Features Page: Display AI agent capabilities with icons and descriptions for all five analysis agents
• About Page: MAYAVIHIN project description, multi-agent architecture explanation, CODE BLOODED development team information
• History Page: Full-page view displaying all previous analyses using the existing AnalysisHistory component with cosmic theme styling
• System Logs Page: Comprehensive activity log display with filtering and search capabilities, using cosmic blue/purple color palette for consistency
• Upload Modal: Fully styled drag-and-drop interface with progress display and result animations
• All pages feature the unified dynamic eye background animation

Upload Interface

• Drag-and-drop file upload with visual feedback
• Progress indicators during upload and analysis
• Improved result animations and visualizations
• Modal-based upload experience
• Eye background animation activates gently during file upload process
• Proper error handling display for save failures with retry options

Results and History

• Rich Analysis Results Display: AnalysisResults and AnalysisResultsModal components show comprehensive multi-agent analysis with detailed per-agent verdicts using Version 19 display format
• Five-Agent Breakdown: Visual Forensics, Audio Analysis, Metadata, Consistency, and Explainability agents each display individual results with “Real”, “Fake”, or “Uncertain” verdicts and confidence percentages
• Explainable AI Layout: Each agent shows human-readable reasoning text and visual percentage confidence bars using Version 19 layout
• Version 19 Analysis Logic: Use the detailed, rich analysis display format from Version 19 with full explainability features
• Analysis history page with search and filter capabilities
• Export functionality for analysis reports
• Visual indicators for suspicious areas in media files
• “View History” button from homepage and header routes directly to the dedicated History page
• History page includes navigation back to homepage

System Logs Interface

• Scrollable card-based or table layout displaying system activity logs
• Columns for timestamp, action type (Upload, Analysis, Delete, Error), file name/ID, status (Success, Error), and message details
• Filter and search bar for quickly locating specific log entries
• Real-time log updates with chronological ordering
• Responsive design matching the cosmic theme
• Navigation integration with header and smooth transitions back to homepage/dashboard
• Consistent styling with existing UI components using cosmic blue/purple color palette

Footer Design

• Cosmic gold theme matching overall aesthetic
• Centered “CODEX LETHALIS” branding
• Subtext: “Developed by CODE BLOODED | Built with ❤️ (love)”
• Responsive design across all devices

Color Palette and Visual Updates

• Primary colors: Deep indigo (#1a1a2e), violet (#16213e), cyan highlights (#0f3460)
• Gradient tones: Blue to purple soft glowing gradients synchronized with dynamic eye background
• Background gradients, glow effects, borders, and hover states harmonized with the eye animation
• All components (buttons, cards, modals, typography) styled with the updated color palette
• Global CSS and Tailwind configuration updated to reflect the new theme with eye animation integration
• Preserve all existing functionality, layout, and responsiveness
• MAYAVIHIN logo displayed without glow effects and without additional text labels across all pages

Dynamic Background Animation

• Minimalist eye design that opens gently when files are uploaded
• Positioned in the background layer, non-intrusive to UI elements
• Smooth animation synchronized with color accents and transitions
• Consistent across all pages for unified user experience
• Darker hues and soft gradients to match the cosmic atmosphere

Technical Requirements

• Support for multiple file formats and sizes
• Parallel processing of analysis agents using Version 19 stable analysis implementation
• Real-time progress updates during analysis
• Efficient storage and retrieval of analysis results using Version 19 methods
• Multi-agent data mapping: Ensure backend analysis retrieval properly maps detailed verdict data to frontend AnalysisResults and AnalysisResultsModal components using Version 19 data mapping
• Explainable AI integration: Frontend components must display all five agents’ individual results with confidence percentages and reasoning text using Version 19 integration
• Fast response times for result display
• Version 19 File Processing: Use the stable file upload and analysis processing from Version 19 that prevents BigInt conversion errors
• Version 19 Data Handling: Implement Version 19’s proven data structures and type handling that successfully processes analysis results
• Robust Numeric Type Handling: Implement comprehensive validation and safe conversion for all numeric values to prevent BigInt conversion errors
• Type Safety for Optional Values: Add defensive checks for undefined or null numeric values before storage operations
• Reliable data persistence and consistency using Version 19 analysis logic
• Standardized error responses and success validation using Version 19 response handling
• Consistent API response body format using Version 19 API structure
• Proper JSON response handling in frontend API integration using Version 19 methods
• System Logging Integration: Connect system logs page with existing React Query hooks in useQueries.ts for real-time log retrieval
• Fully responsive design across desktop, tablet, and mobile devices
• Smooth animations and transitions throughout the interface including dynamic eye background
• React Router integration for page navigation with dedicated History and System Logs page routes
• Existing React Query hooks maintained for backend connectivity
• Application content language: English

Production Deployment Requirements

• Deploy Version 19 of the MAYAVIHIN application to production environment
• Restore Version 19 Stability: Ensure the stable backend implementation from Version 19 is deployed that prevents “Cannot convert undefined to BigInt” errors
• Version 19 Analysis Processing: Confirm that the Version 19 analysis logic works correctly in production environment
• Stable File Upload: Verify that Version 19’s proven file upload and analysis processing works correctly in production
• Enhanced Numeric Type Safety: Ensure all numeric value validation and safe conversion mechanisms are properly deployed to prevent BigInt conversion errors in production
• Maintain all current frontend UI, layout, and design elements without changes
• Preserve existing functionality including file upload, display, and history features exactly as they are
• Confirm all existing functionality works correctly using Version 19 implementation
• Maintain all current features and capabilities without regression
• System Logs Production: Ensure system logging functionality works correctly in production using Version 19 implementation
• Reliable Analysis Processing: Verify that the Version 19 backend logic processes file uploads and analysis correctly in production environment