Installation and Quick Start
System Requirements
DPULSE-CLI is built on Python and designed to run across various environments. To ensure stability and full functionality, your system must meet the following criteria:
| Requirement | Details |
|---|---|
| Operating System | Linux (recommended), macOS, or Windows |
| Python Version | Python 3.11 |
| Network | Stable, high-speed internet connection |
Note: Python versions except 3.11 are not supported. According to this fact, recommended installation methods use virtual environments so you don't worry about dependencies and other projects conflicts.
Required Tools
- Docker — recommended for isolation and ease of use
- uv — recommended for local Python 3.11 and dependencies installation using virtual environment
- Git — required for cloning the repository
Installation Methods
We provide two methods to install DPULSE-CLI. Docker is the recommended method as it eliminates environment conflicts and uses containers for isolation. You can use uv installation method if you want to install DPULSE-CLI locally. This method provides installation with further virtual environment activation when you start DPULSE-CLI, so dependencies and versions conflicts won't appear.
🐳 Method 1: Docker (Recommended)
Using Docker ensures you have all necessary system libraries pre-installed without polluting your host machine.
Step 1: Pull the official image
# If you're using default Docker client
docker pull docker.io/osinttechnologies/dpulse:latest
# In case you are using Podman, which is Docker alternative in some OS:
podman pull docker.io/osinttechnologies/dpulse:latest
Step 2: Run the container
| Platform | Command |
|---|---|
| Linux / macOS | docker run --rm -it -v "$PWD":/data -w /data osinttechnologies/dpulse:latest |
| Windows (PowerShell) | docker run --rm -it -v "${PWD}:/data" -w /data osinttechnologies/dpulse:latest |
| Linux / macOS (Podman) | podman run --rm -it -v "$PWD":/data:Z -w /data osinttechnologies/dpulse:latest |
📦 Method 2: uv
If you prefer running DPULSE-CLI natively, use uv package. It handles virtual environments, correct Python version installation and dependency lock automatically.
# 1. Clone the repository
git clone https://github.com/OSINT-TECHNOLOGIES/dpulse
cd dpulse
# 2.1. Run Linux/macOS installer
chmod +x install.sh
./install.sh
# 2.2. Run Windows installer
powershell -ExecutionPolicy Bypass -File .\install.ps1
These installers will automatically:
- install uv if it is missing
- install Python 3.11 which is strongly required for running DPULSE-CLI
- create a virtual environment
- install all required dependencies
After this procedure you can easily start DPULSE-CLI:
uv run dpulse
Conducting Your First Scan
Once DPULSE-CLI is running, follow this workflow to perform a reconnaissance task.
1️⃣ Main Menu
Upon launch, the CLI interface will appear. To start a standard investigation, select Option 1.
2️⃣ Target Input
DPULSE-CLI operates strictly with domain names, not full URLs.
| Input Type | Example | Valid? |
|---|---|---|
| Domain name | example.com |
✅ Yes |
| Full URL | https://www.example.com/page |
❌ No |
Note: If you accidentally enter a URL, DPULSE-CLI will attempt to extract the domain, but manual input is preferred for accuracy.
3️⃣ Scan Configuration (Modifiers)
You will be asked to configure the scan parameters. Available options:
| Modifier | Description |
|---|---|
| Case Comment | Brief description for internal records (e.g., "Investigation #42") |
| PageSearch | Deep crawling to find sensitive files (PDFs, configs) and exposed secrets |
| Keywords | Custom keywords to search within downloaded documents (requires PageSearch) |
| Dorking Mode | Google Dorking to find admin panels, IoT devices, sensitive directories |
| API Usage | Third-party integrations (VirusTotal, SecurityTrails, HudsonRock) |
| Snapshotting | Capture website's visual state via screenshots, HTML copy, or Wayback Machine |
4️⃣ Results
Once the scan is complete, DPULSE-CLI will:
- Generate a report and put it into a named folder (ex. "report_hackthissiteorg_(19-03-2026, 17h53m16s)"
- Save case metadata to the local database
You can now open the generated report file to view the gathered intelligence.