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🛡️ NoteBoost

Real-Time Social Threat Intelligence & Automated Triage Engine

NoteBoost is a next-generation cybersecurity dashboard that monitors social media signals for coordinated disinformation campaigns, zero-day exploit leaks, and brand reputation threats.

Unlike traditional monitors that rely solely on keywords, Sentinel uses a Hybrid Intelligence Engine:

  1. Speed: A deterministic heuristic formula () filters noise in microseconds.
  2. Intelligence: A Gemini 2.0 Flash agent verifies high-risk threats against ground-truth data (arXiv, CVE databases, internal logs).

🚀 Key Features

  • Live Threat Monitor: Asynchronous ingestion pipeline processing high-velocity social signals.
  • Mathematical Risk Scoring: Custom algorithm to detect viral anomalies instantly.
  • Agentic Triage: "Review & Block" triggers a Gemini Agent that performs deep-dive forensic analysis (Context Check, Source Verification, Cross-Referencing).
  • "Mission Impossible" UI: Dark-mode dashboard with slide-down forensic packets and live ingestion logs.
  • False Positive Protection: Distinguishes between actual threats (e.g., "Zero-Day Exploit") and benign technical jargon (e.g., "Killing a server").

🏗️ Technical Architecture

1. The Ingestion Layer (FastAPI)

  • Built on FastAPI + AsyncIO for non-blocking, high-throughput signal processing.
  • Normalizes unstructured social data into a strict JSON schema.
  • Simulates "Firehose" velocity with background worker tasks.

2. The Detection Layer (Heuristic Engine)

  • TextBlob NLP: Calculates Sentiment Polarity ().
  • Velocity Logic: Tracks interactions per minute ().
  • Evidence Scoring: Regex-based domain verification ().

3. The Verification Layer (Generative AI)

  • Google Gemini 2.0 Flash: Acts as the "Level 2 Analyst."
  • Receives the JSON payload and cross-references claims against trusted datasets.
  • Returns a structured "Triage Packet" with a Verdict (Safe/Malicious) and Confidence Score.

4. The Resolution Layer (Next.js)

  • Next.js 14: Server-side rendering for performance.
  • Tailwind CSS: "Cyber-Sentinel" aesthetic with Framer Motion animations.
  • Polling Architecture: Simulates real-time WebSocket updates.

🧮 The Logic: Formula

Threats are prioritized using our proprietary risk formula:

  • (Sentiment Risk): Derived from NLP polarity. High hostility = High .
  • (Velocity Risk): Rate of spread (Likes/Retweets per minute). Viral = High .
  • (Evidence Credibility): Domain trust score. Unverified links (Pastebin) = Low (which increases Risk).

🛠️ Getting Started

Prerequisites

  • Node.js 18+
  • Python 3.9+
  • Google Gemini API Key

1. Clone the Repository

git clone https://github.com/yourusername/noteboost.git
cd noteboost

2. Backend Setup (FastAPI)

cd backend
# Create virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Start the API Server
uvicorn main:app --reload

The backend will run at http://localhost:8000. API Docs available at /docs.

3. Frontend Setup (Next.js)

# Open a new terminal
cd ..
npm install

# Start the Development Server
npm run dev

The dashboard will launch at http://localhost:3000.


🧪 Usage / Demo Scenarios

The system includes a Simulation Mode to demonstrate detection capabilities:

  1. The Villain (@DeepNet_Ops):
  • Scenario: A tweet claims a "Zero-Day Exploit" with a Pastebin link.
  • Result: Risk Score 0.99.
  • Action: Click "Review". Gemini identifies the CVE pattern and flags as MALICIOUS.
  1. The False Positive (@DevTeam_Lead):
  • Scenario: A dev says, "We are killing the server."
  • Result: Risk Score 0.72 (High Sentiment).
  • Action: Click "Review". Gemini recognizes "DevOps Context" and flags as SAFE.

📜 License

MIT License. Built for the AI Hackathon 2026.

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