Argus: The Ultimate Python Toolkit for Information Gathering and Reconnaissance
This repository profile is provided by osrepos.com, an open source repository discovery platform.

Summary
Argus is a powerful, Python-based toolkit designed for comprehensive information gathering and reconnaissance. It features an intuitive command-line interface and over 130 modules for in-depth analysis of networks, web applications, and security configurations. This tool empowers users to efficiently explore target systems, providing valuable insights for educational and ethical security assessments.
Repository Information
Topics
Click on any tag to explore related repositories
Use at your own risk
OSRepos shares public repositories for knowledge and discovery only. Any installation, execution, configuration, or use of code from these repositories is the user's own responsibility. Always review the repository, source code, dependencies, licenses, and security implications before running or installing anything. OSRepos is not responsible for issues, damages, or losses resulting from third-party repositories.
Introduction
Argus, developed by jasonxtn, is a robust and versatile Python-based toolkit engineered for extensive information gathering and reconnaissance. Billed as "The Ultimate Information Gathering Toolkit," Argus provides a user-friendly command-line interface (CLI) and a comprehensive suite of over 130 modules. These modules are designed to streamline the process of exploring networks, analyzing web applications, and assessing security configurations efficiently and effectively.
?? Legal Disclaimer: This tool is intended for educational and ethical use only. The author is not liable for any illegal use or misuse of this tool. Users are solely responsible for their actions and must ensure they have explicit permission to scan the target systems.
Installation
Getting started with Argus is straightforward, offering several flexible installation methods:
Option 1: No Installation (Run Directly)
git clone https://github.com/jasonxtn/argus.git
cd argus
python -m argus
Option 2: Using pip
pip install argus-recon
argus
Option 3: Full Installation
git clone https://github.com/jasonxtn/argus.git
cd argus
chmod +x install.sh && ./install.sh
python -m argus
Option 4: Docker
git clone https://github.com/jasonxtn/argus.git
cd argus
docker build -t argus-recon:latest .
docker run -it --rm -v $(pwd)/results:/app/results argus-recon:latest
Usage Examples
Argus offers an interactive CLI for easy navigation and execution of its modules. Here's a basic workflow and a glimpse into its command structure:
Getting Started Workflow
- Launch Argus:
argus # or if running from folder: python -m argus - Browse available modules:
argus> modules - Select a module:
argus> use 1 - Set target and options:
argus> set target example.com argus> set threads 10 - Run the module:
argus> run
Command Cheatsheet Snippet
| Command | Category | Description | Example |
|---|---|---|---|
modules |
Discovery | List all modules | modules |
use |
Selection | Select module | use 42 |
set target |
Config | Set target | set target example.com |
run |
Execute | Run selected | run |
search |
Discovery | Search by keyword | search ssl |
helpmod |
Help | Module help | helpmod 42 |
Example Session
$ argus
argus> modules
argus> use 1
argus> set target example.com
argus> set threads 10
argus> run
argus> modules -d
argus> use 65
argus> set max_pages 200
argus> run
Why Use Argus?
Argus stands out as a premier tool for reconnaissance due to several key features and advantages:
- Comprehensive Module Set: With 135 specialized modules covering Network & Infrastructure, Web Application Analysis, and Security & Threat Intelligence, Argus offers an unparalleled breadth of capabilities for any assessment.
- Interactive CLI: The newly redesigned command-line interface provides a professional, intuitive, and efficient way to interact with the tool, including module discovery, configuration, and execution.
- Performance Profiles: Tailor your scans with pre-configured profiles like
speed,deep, andsafeto match your specific reconnaissance needs, optimizing for speed, thoroughness, or stealth. - API Integrations: Enhance your data gathering with seamless integrations for services like Shodan, VirusTotal, Censys, and SSL Labs, providing richer and more accurate information.
- Flexible Configuration: Customize default settings, thread limits, export formats (TXT, CSV, JSON), and user agents to fine-tune Argus for your specific environment and requirements.
- Active Development: The recent Version 2.0 refactor brought a complete CLI redesign, module expansion, multi-threading, and improved UI, demonstrating continuous commitment to enhancing the tool.
Links
- GitHub Repository: https://github.com/jasonxtn/Argus
Related repositories
Similar repositories that may be relevant next.

dify-official-plugins: Extending Dify with AI Models, Tools, and Agent Strategies
August 18, 2026
The `dify-official-plugins` repository hosts a collection of official plugins for Dify, an open-source platform for developing LLM-powered AI applications. These plugins, including models, tools, agent strategies, and extensions, enhance Dify's capabilities and are maintained by the official Dify team. They are designed to help developers efficiently build, deploy, and manage AI-driven solutions.

Agent Skills: A Standardized Way to Give AI Agents New Capabilities
August 18, 2026
Agent Skills provides a lightweight, open format for extending AI agent capabilities with specialized knowledge and workflows. It allows packaging procedural knowledge and context into portable, version-controlled folders that agents load on demand. This enables agents to gain domain expertise, follow repeatable workflows, and reuse skills across various compatible AI tools.

A-MEM: Self-Evolving Memory for Coding Agents
August 17, 2026
A-MEM is an innovative self-evolving memory system designed for coding agents, organizing knowledge into a dynamic Zettelkasten-style graph. It allows memories to evolve and connect over time, enhancing an agent's ability to recall and utilize information effectively. This system offers both semantic and structural search capabilities for a richer knowledge base.

Agent Sandbox: Secure Local Development for AI Coding Agents
August 17, 2026
Agent Sandbox provides a robust and secure local development environment specifically designed for collaborating with AI coding agents. It ensures minimal filesystem access, configurable network egress policies, and secure secret injection, protecting your local machine from potentially risky agent operations. This project supports various AI agents and integrates seamlessly with both CLI and popular IDE devcontainer setups.
Source repository
Open the original repository on GitHub.
17 counted GitHub visits