Get Rakshak.

Deploy the autonomous penetration testing platform in your environment to maintain full control over your security workflows.

Docker Container

Recommended for isolated execution and immediate dependency resolution.

docker pull rudrakshai/rakshak:latest
docker run -it --privileged rudrakshai/rakshak
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Local Environment

Native execution for deep infrastructure integration and custom tool chains.

git clone https://github.com/rudrakshai/rakshak
pip install -r requirements.txt
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Seamless Setup.

From downloading the agent to launching your first autonomous assessment takes less than 5 minutes.

01
Choose Environment
Select Docker or Python Local execution based on your OS.
02
Download Core
Pull the core agent architecture and auto-provisioning scripts.
03
Configure Bridge
Set up your Local LLM parameters or standard API keys via MCP.
04
Connect Platform
Authenticate the runner with the Rakshak web interface.
05
Start Assessment
Input a target and let the Swarm take over.
rakshak-runner ~ root
Dashboard
Assessment
Findings
Reports
Settings

Active Assessment: TARGET-ALPHA

Active Agents
3 (Supervisor, Recon, Web)
Vulnerabilities
2 Critical, 4 High
[SYSTEM] Assessment initialized.
[SUPERVISOR] Generating attack plan for target.internal...
[SUPERVISOR] Delegating task to ReconAgent: Find open ports.
[RECON] Executing nmap via profile [stealth_tcp]...
[RECON] Discovered open port 443, 80, 8080.
[SUPERVISOR] Processing findings...
[SUPERVISOR] Delegating task to WebAgent: Fuzz port 8080.

Data Privacy & Bring-Your-Own-LLM

Rakshak AI is built for sensitive environments. Our Model Context Protocol (MCP) Bridge allows you to bypass public cloud APIs entirely. Connect your own local LLMs (like Llama 3) to process vulnerability data locally, ensuring your proprietary infrastructure details never leave your network.

Ready To Start?

Join the next generation of autonomous security testing.

Start Rakshak