Nebula is an AI-powered command-line assistant for penetration testing, designed to automate reconnaissance, vulnerability analysis, and note-taking for cybersecurity professionals. It integrates various large language models (LLMs) to provide real-time insights and enhance security workflows.

How It Works

Nebula integrates LLMs like Meta's Llama-3.1-8B-Instruct and Mistral-7B-Instruct-v0.2, as well as OpenAI models via API, directly into the CLI. This allows users to leverage AI for tasks such as internet searches, vulnerability suggestions based on tool outputs, and automated note-taking. The tool supports integration with any CLI tool, processing their outputs for AI-driven analysis.

Quick Start & Requirements

• Install: python -m pip install nebula-ai --upgrade
• Prerequisites: Python 3.11+, Ollama (for local models) or OpenAI API key. Minimum 16GB RAM recommended for CPU inference.
• Usage: Run nebula. Interact with AI using ! prefix or AI/Terminal mode.
• 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
• Docs: Video Guide, User Manual

Highlighted Details

• AI-powered internet search via agents for real-time cybersecurity trend updates.
• Automated, categorized security finding note-taking.
• Real-time AI-driven vulnerability discovery and exploitation suggestions.
• Seamless data import from external tools for AI analysis.
• Integrated screenshot capture and annotation.

Maintenance & Community

• Support via GitHub Issues.
• Video guides and user manual available.

Licensing & Compatibility

• License not specified in the README.

Limitations & Caveats

Some features are exclusive to Nebula Pro. The README mentions a "Deep Application Profiler (DAP)" which uses neural networks for malware detection, but its integration status within the core Nebula CLI tool is unclear.