IoT_PreTester_Demo/V4.5

IoT PreTester V4.5

Overview

The IoT PreTester V3 project is an integrated platform for analyzing and evaluating IoT devices, firmware files, and network traffic.
It combines a Django backend for data storage, API, and analysis with a Next.js frontend for user management, device administration, and result visualization.

The solution allows administrators to manage manufacturers, device types, and users, analyze firmware uploads (Binwalk, Strings, Hashes, PCAP), and view results via a modern web interface.

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Main Components

Backend – Django

Path: django_project/
Framework: Django + Django REST Framework

Structure and main modules:

• IoTAnalyzer/ – Core application containing models, views, URLs, and analysis functions
  • models.py – Data model (devices, firmware, manufacturers, analysis results)
  • views.py – REST APIs for device management, file uploads, authentication
  • urls.py – API routing and endpoint definition
  • db_create.py, db_read.py, db_update.py, db_delete.py – CRUD logic
  • analyze/ – Modules for firmware, PCAP, URL, and hash analysis
  • management/commands/ – Management commands for automated analysis
• IoTPreTester/ – Django project configuration (settings, middleware, routing)
• templates/ – Classic Django template (e.g., index page)
• static/ – Static assets for legacy UI components
• tests/ – Unit and integration tests

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Frontend – Next.js

Path: Frontend/iot-pre-tester-frontend/
Framework: Next.js + TypeScript + Tailwind CSS + shadcn/ui

Structure and main modules:

• src/app/ – App routes in Next.js App Router style
  • login/, change-password/ – Authentication
  • devices/ – Device management and details view
  • manage-users/, manage-device-types/, manage-manufacturers/ – Admin features
  • scan-results/, analysis/ – Display of analysis results
• src/components/ – UI components, upload modules, authentication, providers
• src/lib/ – API hooks, contexts, utility functions
• src/services/ – HTTP services and file upload handlers
• src/types/ – TypeScript type definitions
• public/ – Static assets, images, and upload directories
• Configuration files: next.config.ts, tailwind.config.ts, tsconfig.json

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Analysis and Data Processing

Path: django_project/IoTAnalyzer/analyze/

Included modules:

• analyze_pcap.py – Evaluation of PCAP files (e.g., hashes, URLs)
• analyze_firmware.py – Extraction of strings and binary data from firmware
• analyze_hashes.py – Hash analysis (including password cracking via rockyou.txt)
• analyze_url.py, analyze_dns.py – DNS/URL validation and network checks

Results are persisted in the RawData, AnalyzedData, Firmware, Device, and related models.

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Docker Commands

Starting the Containers

# 1. Change to this directory
cd V4.5

# 2. Configure environment variables (only the first time)
cp .env.example .env
nano .env # Adjust: SECRET_KEY, DJANGO_SUPERUSER_PASSWORD, etc.

# 3. Build and start the containers
docker compose up -d --build

# 4. Wait until both containers report "healthy"
docker compose ps

The first start takes a few minutes (images are built, the database is created and seeded with default manufacturers/device types). The frontend only starts once the backend healthcheck passes. After the first successful start, set INIT_DATABASE=false in .env to skip re-seeding on later starts.

Then log in at http://localhost:3000 with the superuser from .env (default username admin, password = DJANGO_SUPERUSER_PASSWORD). Demo files for trying out the analysis are in demo_files/.

A full German step-by-step guide (start, usage, shutdown) is in the repository README.

Stopping the Containers

# Stop containers (data is preserved)
docker compose stop

# OR: Stop and remove containers (data is preserved)
docker compose down

# OR: Remove everything including volumes/data (caution!)
docker compose down -v

Quick overview

Action	Command
Start	docker compose up -d
Stop	docker compose stop
Status	docker compose ps
Logs	docker compose logs -f

Access

• Frontend: http://localhost:3000
• Backend API: http://localhost:8000

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License

This project is licensed under an internal research and development license.
Commercial use or distribution requires written permission from the project owner.