Log On The Go

Local-first security log analysis with on-demand intelligence.
Built for developers, sysadmins, and production servers

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🚀 What is LOTG?

Log On The Go (LOTG) is a modern log analysis platform that lets you:

• Analyze security logs on demand
• Upload files or analyze logs by path
• Inspect risk levels, attack patterns, and timelines
• Keep everything local-first and controlled

No background magic.
No forced cloud dependency.
You decide when analysis happens.

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🧩 Modes

🔹 Standard Mode (LOTG)

• Upload log files
• Analyze logs by file path
• View detailed security reports instantly

🔹 Server Mode (LOTG Serv)

• Designed for servers & businesses
• Secure access via credentials
• Analyze pre-configured server log paths
• Same analysis engine, same results, cleaner workflow
• Make a user using python -m app.init_users

LOTG Serv runs locally but is structured for production environments.

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🔍 What Gets Analyzed?

LOTG supports a wide range of logs including:

• Linux auth logs (auth.log, secure)
• SSH authentication events
• Apache access logs
• Syslog-style files
• Mixed or unknown formats (graceful fallback)

Each analysis includes:

• Risk score & level (LOW / MEDIUM / HIGH)
• Suspicious IPs
• Brute-force attempts
• Attack chains & anomalies
• Timeline & narrative summary

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🧠 How It Works

1. Choose a mode (Upload / Path / SERV)
2. Trigger analysis manually
3. Logs are parsed & normalized
4. Security patterns are detected
5. Results are returned as structured JSON
6. Frontend presents expandable, readable reports

Nothing is modified.
Nothing runs in the background without you knowing.

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🖥️ Tech Stack

Backend

• Python
• FastAPI
• Read-only log parsing

Frontend

• React (Vite)
• Modern, dark, security-focused UI
• Expandable analysis views

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▶️ Running the App (Dev)

From the project root:

npm install concurrently --save-dev 
cd frontend && npm install && cd .. 
npm run dev 

Demo

Click to expand demo

📊 Log Analysis Demo

Input

• auth.log
• apache2.log

What LOTG shows

• Risk score: HIGH
• Brute-force detection
• Attack chain correlation
• Timeline of suspicious activity

Screenshot

Sample Output (JSON)

{
  "risk_level": "HIGH",
  "risk_score": 85,
  "attackers": 3
}