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A localized penetration testing assistant based on large language models, requiring no cloud API keys, integrating multiple security tools to automate reconnaissance, vulnerability discovery, and repair suggestion generation
Section 01
This project is an AI-powered penetration testing assistant based on large language models, designed to run completely locally without cloud API keys. It integrates multiple security tools to automate reconnaissance, vulnerability discovery, and repair suggestion generation. Key features include private deployment, no subscription fees, and support for generating professional reports.
Section 02
Traditional penetration testing relies heavily on tester experience, requiring mastery of many tools and analysis of outputs, which limits accessibility for small teams. Most AI security tools depend on cloud APIs, posing data leakage risks and ongoing costs. DIGILIANS AI addresses these issues with its "fully local" design—no cloud services, no API keys, no subscriptions—enabling private AI-driven security testing.
Section 03
Architecture: Modular design integrating traditional tools and local AI. Components:
Workflow: Input target → run tool chain → AI analysis → generate reports & store history.
Section 04
Modes:
Deployment: Compatible with Kali Linux. Requires Python3.8+, Ollama, Digilians-offensive model, MariaDB, and pre-installed tools (nmap, nikto etc.). Quick start takes ~15 mins.
Section 05
Compliance: Built-in authorization check (user must confirm "I have permission" before scanning)
Value:
Section 06
Limitations:
Future improvements: Community contributions to expand tool coverage, model support, and add enterprise features.
Section 07
DIGILIANS AI shows a practical application of LLMs in security testing, focusing on solving real pain points (tool integration, data privacy, efficiency). It acts as an AI assistant to free experts from repetitive tasks, letting them focus on high-value work. As local LLMs advance, more such tools are expected to drive the industry toward efficiency and inclusivity.
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