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Getting Started

This guide walks you through installing the Detectify Internal Scanner using the packaged installer. The entire process takes about 5 minutes.

Make sure you have your four credentials ready before starting: license key, connector API key, registry username, and registry password.

Download the installer

Download the detectify-scanner script to your Linux host and make it executable:

curl -sSL https://github.com/detectify/internal-scanning-installer/releases/latest/download/detectify-scanner -o detectify-scanner chmod +x detectify-scanner

Run the installer

Run the installer with sudo:

sudo ./detectify-scanner install

The installer will:

  1. Run pre-flight checks — verifies system requirements, network connectivity, and dependencies
  2. Prompt for credentials — enter your license key, connector API key, registry username, and registry password
  3. Validate credentials — confirms registry and license credentials are valid before proceeding
  4. Install k3s — provisions a lightweight Kubernetes cluster
  5. Deploy the scanner — installs all scanner components via Helm
  6. Wait for readiness — confirms all pods are healthy

Verify the installation

Once installation completes, you’ll see a success message with the scanner API URL:

Installation complete! Scanner is running. All pods are healthy in the 'scanner' namespace. Configuration saved to /etc/detectify-scanner/scanner.env Scanner API: http://<your-host-ip>:30000 Use this URL to configure your CI/CD pipelines or to start a scan manually.

You can also check the status at any time:

sudo detectify-scanner status

The installer copies itself to /usr/local/bin/detectify-scanner during installation, so you can run commands from anywhere after installing.

What Gets Installed

The installer provisions the following on your host:

ComponentDescription
k3sLightweight Kubernetes distribution (single-node cluster)
scan-schedulerReceives scan requests and queues them in Redis
scan-managerPicks up jobs and creates ephemeral scan worker pods
chrome-controllerManages headless Chrome instances for browser-based scanning
redisIn-cluster data store for job state

All components run in a scanner Kubernetes namespace. For details on how these components interact and scale, see Scaling & Capacity Planning.

Next Steps

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