Nebula – AI-Powered Penetration Testing Assistant

Nebula is an advanced, AI-powered penetration testing open-source tool that revolutionizes penetration testing by integrating state-of-the-art AI models into your command-line interface. Designed for cybersecurity professionals, ethical hackers, and developers, Nebula automates vulnerability assessments and enhances security workflows with real-time insights and automated note-taking.

Acknowledgement

First i would like to thank the All-Mighty God who is the source of all knowledge, without Him, this would not be possible.

News

Introducing the Deep Application Profiler (DAP). DAP uses neural networks to analyze an executable's internal structure and intent, rather than relying on traditional virus signatures. This approach enables it to detect new, zero-day malware that conventional methods often miss. DAP also provides detailed breakdowns for rapid analyst review and is available as both a web service and an API. Learn More Here

Nebula: AI-Powered Penetration Testing Platform

Nebula is a cutting-edge, AI-powered penetration testing tool designed for cybersecurity professionals and ethical hackers. It integrates both hosted models available through the OpenAI API and open-source models such as Meta's Llama-3.1-8B-Instruct, Mistral AI's Mistral-7B-Instruct-v0.2, and DeepSeek-R1-Distill-Llama-8B directly into the command line interface (CLI). By leveraging these state-of-the-art models, Nebula not only enhances vulnerability assessments and penetration testing workflows but also supports any tool that can be invoked from the CLI.

Installation

System Requirements:

For CPU-Based Inference(Ollama)(Note that Ollama Supports GPU too):

• At least 16GB of RAM
• Python 3.10 – 3.13.9
• Ollama

Installation Command:

python -m pip install nebula-ai --upgrade

Running Nebula

Important:

Ollama Local Model Based Usage

Install Ollama and download your preferred models for example

 ollama pull mistral

Then enter the model's exact name as it appears in Ollama in the engagement settings.

OpenAI Models Usage

To use OpenAI models, add your API keys to your env like so

export OPENAI_API_KEY="sk-blah-blaj"

Then enter the OpenAI model's exact name in the engagement settings.

Run nebula

nebula

Using docker

First allow local connections to your X server:

xhost +local:docker

docker run --rm -it   -e DISPLAY=$DISPLAY   -v /home/YOUR_HOST_NAME/.local/share/nebula/logs:/root/.local/share/nebula/logs -v YOUR_ENGAGEMENT_FOLDER_ON_HOST_MACHINE:/engagements -v /tmp/.X11-unix:/tmp/.X11-unix   berylliumsec/nebula:latest

Interacting with the models.

To interact with the models, begin your input with a ! or use the AI/Terminal button to switch between modes. For example: ! write a python script to scan the ports of a remote system the "!" is not needed if you use the context button

Key Features

• AI-Powered Internet Search via agents:
  Enhance responses by integrating real-time, internet-sourced context to keep you updated on cybersecurity trends. "whats in the news on cybersecurity today"

• AI-Assisted Note-Taking:
  Automatically record and categorize security findings.

• Real-Time AI-Driven Insights:
  Get immediate suggestions for discovering and exploiting vulnerabilities based on terminal tool outputs.

• Enhanced Tool Integration:
  Seamlessly import data from external tools for AI-powered note-taking and advice.

• Integrated Screenshot & Editing:
  Capture and annotate images directly within Nebula for streamlined documentation.

• Manual Note-Taking & Automatic Command Logging:
  Maintain a detailed log of your actions and findings with both automated and manual note-taking features.

• Status feed:
  This panel displays your most recent penetration testing activities, it refreshes every five minutes

Roadmap

• Create custom models that are more useful for penetration testing

Troubleshooting

Logs are located at /home/[your_username]/.local/share/nebula/logs. You would most likely find the reason for the error in one of those logs

Get More Support

• Have questions or need help? Open an Issue on GitHub.