33-TruthGuard

Appearance

Step 0 Pre-Check: Project Type Detection & Evidence Audit ​

1. Detected Project Type ​

  • Primary Classification: Multi-Modal Cyber-Defense & AI Forensics Platform (React 18 + TypeScript + Vite + Tailwind CSS + Supabase Edge Functions + Micro-Frontend Federated Hub Architecture).
  • Stack Paradigm: Distributed Frontend-Centric Architecture with Serverless Edge Functions (supabase.functions.invoke), Client-Side Cryptographic & Forensic Analysis Engines (Web Crypto API SHA-256, EXIF parsing via exifr), and State-Driven Real-Time Observability (Zustand, TanStack Query, Framer Motion).
  • Applicable Documentation Track:
    • Track B (Frontend-Centric Forensics & Micro-Frontends): Advanced Component Design, Dynamic Port Probing (mainpage/src/pages/FeatureEmbed.tsx), Canvas/SVG Authenticity Gauges, Client-Side Forensic Parsers, Zustand Persistent Stores.
    • Track A/C Hybrid (Serverless Backend & Edge Gateways): Supabase PostgreSQL profiles schema, Edge Function invocations (analyze-media, analyze-content), OAuth2 / JWT authentication flows (mainpage/src/contexts/AuthContext.tsx).
    • AI Integration Track: Pre-trained multi-modal forensic heuristics, sentiment & emotional manipulation analysis, fact-checking consensus pipelines (PolitiFact, Snopes, FactCheck.org, Reuters integrations), and voice/SMS phishing threat classifiers.

2. Evidence from Codebase ​

Evidence ItemSource Location in WorkspaceArchitectural Role & Justification
Hub Orchestration[mainpage/src/pages/Hub.tsx](file:///Users/avishjain/avishjain9-repos/33-codealchemist/mainpage/src/pages/Hub.tsx#L1-L217)Central access point coordinating 6 specialized forensic sub-modules with NVIDIA-inspired dark styling.
Dynamic Port Prober[mainpage/src/pages/FeatureEmbed.tsx](file:///Users/avishjain/avishjain9-repos/33-codealchemist/mainpage/src/pages/FeatureEmbed.tsx#L59-L76)Implements client-side dynamic port scanning (checkPort starting at port 5176 using no-cors HEAD requests) to detect running micro-frontend instances.
Executive Forensics[mainpage/src/components/VeritAIApp.tsx](file:///Users/avishjain/avishjain9-repos/33-codealchemist/mainpage/src/components/VeritAIApp.tsx#L1-L1685)1,685-line comprehensive forensic dashboard calculating credibility scores (0–100), emotion manipulation indexes, bias indicators, and claim verification.
Cryptographic Provenance[mediavault 2/src/lib/mediavault-store.ts](file:///Users/avishjain/avishjain9-repos/33-codealchemist/mediavault%202/src/lib/mediavault-store.ts#L64-L120)Zustand store with local persistence (STORAGE_KEY_FILES), simulating multi-stage encryption, file integrity verification, and activity logging.
Tamper Analysis & EXIF[camara-temper/src/lib/fileAnalyzer.ts](file:///Users/avishjain/avishjain9-repos/33-codealchemist/camara-temper/src/lib/fileAnalyzer.ts#L66-L179)Forensic file analyzer combining Web Crypto SHA-256 (crypto.subtle.digest) with exifr parsing to detect editing software signatures (photoshop, gimp, lightroom).
Edge Function Invocations[truthlence/src/pages/Index.tsx](file:///Users/avishjain/avishjain9-repos/33-codealchemist/truthlence/src/pages/Index.tsx#L35-L38) & [calldetection-sms-contentdetection/src/pages/CallDetection.tsx](file:///Users/avishjain/avishjain9-repos/33-codealchemist/calldetection-sms-contentdetection/src/pages/CallDetection.tsx#L23-L26)Remote serverless AI invocations via supabase.functions.invoke('analyze-media') and supabase.functions.invoke('analyze-content').
Authentication & RBAC[mainpage/src/contexts/AuthContext.tsx](file:///Users/avishjain/avishjain9-repos/33-codealchemist/mainpage/src/contexts/AuthContext.tsx#L68-L99)Supabase Auth listener (onAuthStateChange) mapped to relational profiles table with role definitions (Journalist, Analyst, Admin).

3. How the Documentation Adapts ​

  1. Micro-Frontend Architecture Focus: Rather than documenting a traditional single-monolith Express backend, we document the real-world micro-frontend federated topology: independent Vite applications communicating over designated local ports (:5173, :5182, :5183, :5184) and unified via the Hub and Edge gateways.
  2. AI Integration Integrity: Real code calls pre-trained AI analysis routines via Supabase Edge Functions (analyze-media and analyze-content) and client-side heuristics. No custom machine learning weights were trained locally; models are accessed as inference services and deterministic algorithmic pipelines.
  3. Database Grounding: Database features reflect the real PostgreSQL / Supabase schema (the profiles table and session storage), while asset metadata caching uses client-side IndexedDB and localStorage persistence in mediavault 2.
  4. Mandatory Artifacts: All diagrams (Mermaid), first-person spoken scripts ("Say It Out Loud"), the 275-item enterprise master checklist, the 19 system design deep dives, and the 150+ project-specific interview Q&As reflect this exact implementation.