An advanced AI-powered credibility engine that fact-checks claims, detects deepfake images, analyzes media bias, and scans full web pages for misinformation — in real-time.
- Overview
- Key Features
- Architecture
- Web Dashboard
- Browser Extension (USP)
- Tech Stack
- Getting Started
- API Reference
- Future Scope
- Contributing
- License
VERIVOX (Verified Voice — Veracity Optimized eXtended) is an end-to-end misinformation detection platform that combines:
- 🧠 LLM-powered claim extraction & fact-checking (GPT-4.1)
- 🤖 HuggingFace ML model for fake news classification
- 🖼️ EfficientNet-B0 deepfake detection for image authenticity
- 📊 Multi-signal credibility scoring (Fact-Check, Source Credibility, Sentiment/Bias)
- 🔌 Browser extension for real-time verification while browsing
VERIVOX doesn't just flag content as fake — it provides a detailed trust score (0-100), explains why content is misleading, and cites reference sources so users can verify independently.
| Feature | Description |
|---|---|
| 📝 Text/Claim Analysis | Paste any claim or article text → get instant credibility assessment |
| 🖼️ Deepfake Detection | Upload images to detect AI-generated/manipulated media |
| 🌐 Full Page Scanning | Enter any URL → CLARIX scrapes and analyzes the entire page |
| 📊 Trust Score (0-100) | Multi-dimensional scoring with Fact-Check, Source Credibility, and Bias breakdown |
| 🧩 Browser Extension | One-click verification directly in your browser — no tab switching needed |
| 📈 Live Dashboard | Real-time stats, analysis history, and activity tracking |
| 🔍 RAG Pipeline | Retrieval-Augmented Generation cross-references claims against trusted sources |
| ⚡ Async Analysis | Queue-based processing for non-blocking URL analysis |
┌───────────────────────────────────────────────────────────────────┐
│ VERIVOX Platform │
├─────────────────┼──────────────────┼────────────────────────────┤
│ │ │ │
│ Next.js │ Express.js │ FastAPI │
│ Frontend │ Backend │ Python Engine │
│ (Port 3001) │ (Port 3000) │ (Port 8000) │
│ │ │ │
│ ┌───────────┐ │ ┌──────────┐ │ ┌──────────────────────┐ │
│ │ Dashboard │──┼─▶│ API Server │──┼─▶│ HuggingFace Model │ │
│ │ Analyzer │ │ │ LLM Svc │ │ │ (Fake News Detector) │ │
│ │ Stats │ │ │ ML Svc │ │ │ │ │
│ └───────────┘ │ │ RAG Svc │ │ │ EfficientNet-B0 │ │
│ │ │ Caching │ │ │ (Deepfake Detector) │ │
│ ┌───────────┐ │ └─────┼──────┘ │ │ │ │
│ │ Extension │──┼──────── │ │ GPT-4.1 Pipeline │ │
│ │ (Popup) │ │ │ │ (Claim Verification) │ │
│ └───────────┘ │ ┌──────────┐ │ └──────────────────────┘ │
│ │ │ Neon DB │ │ │
│ │ │ (Postgres) │ │ │
│ │ └──────────┘ │ │
└─────────────────┴──────────────────┴────────────────────────────┘
The VERIVOX web dashboard provides a premium, dark-themed interface with real-time particle animations and glassmorphism cards.
The VERIVOX Browser Extension is the heart of the platform. While dashboards are useful, the real power lies in verifying content while you browse — without switching tabs, copy-pasting text, or disrupting your workflow.
Most fact-checking tools require you to leave the page, paste content into a separate website, and wait for results. VERIVOX brings the verification engine directly into your browser toolbar, making credibility assessment as natural as clicking a bookmark.
| Feature | How It Works |
|---|---|
| 📋 Text Analysis | Paste or type any claim → instant credibility check |
| ✅ Use Selection | Highlight text on any web page → click "Use Selection" → analyze |
| 🖼️ Image Check | Upload or paste image URL → deepfake detection |
| 🌐 Full Page Scan | Click "Scan Full Page" → CLARIX analyzes the entire page you're on |
| 🔗 Dashboard Link | One-click to open the full web dashboard for deeper analysis |
- Open
chrome://extensions(orbrave://extensions/edge://extensions) - Enable Developer Mode (toggle in top-right)
- Click "Load unpacked"
- Select the
extension/folder from this repository - Pin the Clarix icon in your toolbar
Works with: Chrome, Brave, Edge, and any Chromium-based browser.
| Technology | Purpose |
|---|---|
| Next.js 16 (Turbopack) | React framework with server-side rendering |
| Tailwind CSS | Utility-first styling |
| Radix UI | Accessible component primitives |
| Framer Motion | Scroll-reveal and micro-animations |
| Lucide React | Icon library |
| Technology | Purpose |
|---|---|
| Express.js | REST API server |
| Prisma ORM | Type-safe database queries |
| OpenAI SDK | GPT-4.1 for claim extraction, verification, and summarization |
| Multer | Image file upload handling |
| Bull | Job queue for async analysis (optional, Redis-backed) |
| Joi | Request validation |
| Technology | Purpose |
|---|---|
| FastAPI | High-performance async API |
| Transformers | HuggingFace fake news detection model |
| PyTorch | Deep learning inference |
| EfficientNet-B0 | Deepfake image classification |
| Pydantic | Schema validation |
| Technology | Purpose |
|---|---|
| Neon (PostgreSQL) | Serverless database |
| Supabase | pgvector for RAG embeddings (optional) |
| Redis | Caching & job queues (optional, falls back to in-memory) |
- Node.js ≥ 18
- Python ≥ 3.11
- npm ≥ 9
- An OpenAI API Key (get one here)
git clone https://github.com/Aditya060806/VERIVOX.git
cd VERIVOXServer backend (server/.env):
cp server/.env.example server/.env
# Edit server/.env and add your keys:
# OPENAI_API_KEY="sk-your-key-here"
# DATABASE_URL="your-neon-postgres-url"Python engine (.env in project root):
# Create .env in project root
OPENAI_API_KEY=sk-your-key-here
OPENAI_MODEL=gpt-4.1-mini
LLM_PROVIDER=openai
HOST=0.0.0.0
PORT=8000
LOG_LEVEL=info# Node.js backend
cd server && npm install && npx prisma generate && npx prisma db push && cd ..
# Next.js frontend
cd frontend && npm install && cd ..
# Python engine
pip install -r requirements.txt# Terminal 1 — Backend API (port 3000)
cd server && npm run dev
# Terminal 2 — Frontend dashboard (port 3001)
cd frontend && PORT=3001 npm run dev
# Terminal 3 — Python AI engine (port 8000)
python main.py- Go to
chrome://extensions - Enable Developer Mode
- Click Load unpacked → select the
extension/folder - Pin the Clarix icon 📌
# Health check
curl http://localhost:3000/api/health
# → {"success":true,"status":"healthy"}
# Test analysis
curl -X POST http://localhost:3000/api/analyze \\
-H "Content-Type: application/json" \\
-H "X-API-Key: your-public-api-key" \\
-d '{"type":"text","content":"Scientists confirm chocolate cures cancer"}'
# → {"success":true,"data":{"score":10,"verdict":"Misleading",...}}All endpoints are prefixed with /api and served at http://localhost:3000.
| Method | Endpoint | Description | Auth |
|---|---|---|---|
GET |
/api/health |
Server health check | No |
POST |
/api/analyze |
Unified analysis (text/image/page) | API Key |
POST |
/api/analyze/url |
Analyze a URL | API Key |
POST |
/api/analyze/text |
Analyze raw text | API Key |
POST |
/api/analyze/image |
Deepfake detection (multipart upload) | API Key |
GET |
/api/analyze/history |
Get analysis history | API Key |
GET |
/api/analyze/:resultId |
Get specific result | No |
GET |
/api/stats |
Dashboard statistics | No |
POST |
/api/analyze/async/url |
Queue async URL analysis | API Key |
GET |
/api/analyze/status/:id |
Poll async job status | No |
POST /api/analyze
Content-Type: application/json
X-API-Key: your-api-key
{
"type": "text",
"content": "Breaking: Scientists discover miracle cure for all cancers"
}{
"success": true,
"data": {
"score": 15,
"verdict": "Misleading",
"factCheck": 10,
"sourceCredibility": 20,
"sentimentBias": 5,
"explanation": "The article makes an extraordinary claim...",
"credibility": {
"score": 15,
"confidence": 0.9,
"category": "flagged",
"label": "Flagged as Fake",
"badge": "FAKE"
},
"sources": [
{ "title": "Reuters Fact Check", "url": "https://www.reuters.com/fact-check/" },
{ "title": "AP News Fact Check", "url": "https://apnews.com/hub/ap-fact-check" }
]
}
}VERIVOX is built as a modular, extensible platform. Here's what's coming next:
Currently: VERIVOX can analyze individual URLs and text.
Next: Deep-crawl entire websites, analyzing every page for credibility patterns, identifying systemic misinformation across a domain, and generating a site-wide trust report.
Goal: Real-time tweet and thread analysis.
- Monitor trending topics for misinformation spikes
- Analyze tweets with image/video attachments for deepfakes
- Generate credibility scores for viral threads
- Track misinformation propagation patterns across retweets
Goal: Subreddit and post-level credibility checks.
- Analyze top posts in news subreddits (r/news, r/worldnews, r/politics)
- Cross-reference claims in comments with known facts
- Flag potential astroturfing and coordinated misinformation
- Provide community-level credibility heatmaps
Planned integrations for Instagram, Facebook, Telegram, and YouTube to verify visual and video content at scale.
| Feature | Description |
|---|---|
| Video Deepfake Detection | Extend EfficientNet to analyze video frames for face-swap and lip-sync deepfakes |
| Multi-language Support | Support fact-checking in Hindi, Spanish, French, Arabic, and more |
| Source Network Graph | Visualize how misinformation spreads across sources using graph databases |
| Real-time Alerts | Push notifications for high-confidence misinformation in followed topics |
| Collaborative Fact-Checking | Community-driven verification with upvote/downvote on analyses |
| Custom Watchlists | Monitor specific topics, people, or sources for new misinformation |
- Misinformation Trend Dashboard — Track fake news patterns over time
- Exportable Reports — PDF/CSV exports for journalists and researchers
- API Webhooks — Real-time notifications for enterprise integrations
- Media Literacy Score — Personalized score tracking your fact-checking habits
VERIVOX/
├── frontend/ # Next.js 16 web dashboard
│ ├── src/app/page.tsx # Main dashboard page
│ └── src/components/ # UI components (shadcn/ui)
│
├── server/ # Express.js backend
│ ├── src/
│ │ ├── config/ # Environment config
│ │ ├── controllers/ # Route handlers
│ │ ├── services/ # Business logic
│ │ │ ├── llm.service.js # OpenAI GPT integration
│ │ │ ├── ml.service.js # Python engine bridge
│ │ │ ├── credibility.service.js # Scoring pipeline
│ │ │ └── rag.service.js # RAG retrieval
│ │ ├── routes/ # API routes
│ │ └── middleware/ # Auth, rate-limiting
│ └── prisma/schema.prisma # Database schema
│
├── extension/ # Chrome extension (popup + content scripts)
│ ├── popup.html # Extension popup UI
│ ├── popup.js # Popup logic & API calls
│ ├── popup.css # Extension styles
│ └── manifest.json # Extension manifest (MV3)
│
├── engine/ # Python AI modules
│ ├── pipeline.py # Main verification pipeline
│ ├── claim_extractor.py # Claim extraction
│ ├── claim_verifier.py # Fact verification
│ ├── deepfake_detector.py # EfficientNet-B0 deepfake model
│ ├── bias_analyzer.py # Bias detection
│ └── scorer.py # Credibility scoring
│
├── image_model/ # Pre-trained model weights
│ └── deepfake_model.pth # EfficientNet-B0 weights
│
├── main.py # FastAPI entry point
├── config.py # Python engine config
└── requirements.txt # Python dependencies
Contributions are welcome! Here's how to get started:
- Fork this repository
- Create a feature branch:
git checkout -b feature/your-feature - Commit your changes:
git commit -m "feat: add your feature" - Push to the branch:
git push origin feature/your-feature - Open a Pull Request
Please follow the existing code style and include tests where applicable.
This project is licensed under the MIT License — see the LICENSE file for details.