Demo Data Generation

This guide explains how to generate demonstration data for testing and development purposes.

Overview

The generate_demo_data.py script creates realistic test data based on a University/Faculty theme, including:

Users: Admin and regular users (Profs, Students, IT Support)
Contact Persons: Departments and individuals with IP and CIDR assignments
Hosts: Servers with rich metadata (OS, Hostnames)
Scans: Vulnerability reports (XML, PDF, HTML) with linked products, locations, and sources.
Linked Reports: Scenarios where XML, PDF, and HTML reports share the same report ID/filename.
Trend Data: Historical scan data generated daily for the last 30 days
Access Logs: Simulated usage history

Prerequisites

The script must be run inside the Docker backend container to access the database.

Running the Script

Basic Usage

docker exec vulnerability-scanner-backend-1 python /app/generate_demo_data.py

First-Time Setup

If the script is not yet in the container (e.g. if you modified it locally), copy it first:

docker cp src/backend/generate_demo_data.py vulnerability-scanner-backend-1:/app/
docker exec vulnerability-scanner-backend-1 python /app/generate_demo_data.py

Generated Data

Users

The script creates the following demo users.

Default Password: DemoPass123!

Username	Full Name	Email	Role
prof_mueller	Prof. Dr. Thomas Müller	thomas.mueller@uni.de	Admin
dr_schmidt	Dr. Anna Schmidt	anna.schmidt@uni.edu	User
stud_weber	Maximilian Weber	max.weber@student.uni.edu	User
admin_fischer	Klaus Fischer	klaus.fischer@rz.uni.edu	Admin
user_bib	Bibliothek EDV	edv@bibliothek.uni.edu	User
user_rz	IT Support RZ	it-support@rz.uni.edu	Admin

Contact Persons

Contact persons are created to demonstrate IP and CIDR ownership:

Prof. Dr. Thomas Müller - IPs: 192.0.2.10, 192.0.2.11, …
IT Rechenzentrum - CIDR: 192.0.2.0/24, 198.51.100.0/24, 203.0.113.0/24 (Network Wide)
Fakultät Informatik - IPs: 203.0.113.1, 203.0.113.2 - CIDR: 203.0.113.0/24
Bibliothek - IPs: 198.51.100.40

Hosts & Metadata

Hosts are enriched with realistic metadata:

Hostname: e.g., webserver01.informatik.uni.edu
OS: e.g., Ubuntu 22.04 LTS, Debian 11, Windows Server 2019

Linked Data: - Products: OpenSSH 8.2p1, Apache/2.4.41, etc. - Locations: tcp/80, tcp/443, etc. - Sources: NVT Feed, CVE Feed

Historical Trend Data

To populate the Vulnerability Trend dashboard, the script generates:

Daily Scans: For the last 30 days
Target: Fakultät für Informatik (webserver01)
Varying Severity: Random mix of High/Medium/Low vulnerabilities to show trend lines.

Scan Scenarios

Specific scenarios are created to test logic:

Unaccessed Report: A report created 1 day ago that has never been opened (testing notifications).
Linked Reports: A full set (XML, PDF, HTML) for Rechenzentrum to test UI grouping.
Orphan Reports: Standalone PDF or HTML files (e.g. Legacy_Scan_2023.pdf) to test individual file handling.
Unknown Owner: A report for an IP (192.0.2.199) not assigned to any contact.
Legacy Scan: Old scan from >30 days ago.

Resetting Demo Data

The script is idempotent for inserts (skips existing IDs/Emails), but for a clean slate:

# Stop containers
docker compose down -v

# Restart
docker compose up -d

# Re-run script
docker exec vulnerability-scanner-backend-1 python /app/generate_demo_data.py

Troubleshooting

UnboundLocalError: If you see an error about vuln_objs, ensure you are using the latest version of the script where vulnerability creation is ordered before the trend data loop.