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BreachSeek: A Multi-Agent Automated Penetration Tester

Ibrahim Alshehri, Adnan Alshehri, Abdulrahman Almalki, Majed Bamardouf, Alaqsa Akbar

TL;DR

In preliminary evaluations, BreachSeek successfully exploited vulnerabilities in exploitable machines within local networks, demonstrating its practical effectiveness and positioning it as an indispensable tool for cybersecurity professionals.

Abstract

The increasing complexity and scale of modern digital environments have exposed significant gaps in traditional cybersecurity penetration testing methods, which are often time-consuming, labor-intensive, and unable to rapidly adapt to emerging threats. There is a critical need for an automated solution that can efficiently identify and exploit vulnerabilities across diverse systems without extensive human intervention. BreachSeek addresses this challenge by providing an AI-driven multi-agent software platform that leverages Large Language Models (LLMs) integrated through LangChain and LangGraph in Python. This system enables autonomous agents to conduct thorough penetration testing by identifying vulnerabilities, simulating a variety of cyberattacks, executing exploits, and generating comprehensive security reports. In preliminary evaluations, BreachSeek successfully exploited vulnerabilities in exploitable machines within local networks, demonstrating its practical effectiveness. Future developments aim to expand its capabilities, positioning it as an indispensable tool for cybersecurity professionals.

BreachSeek: A Multi-Agent Automated Penetration Tester

TL;DR

In preliminary evaluations, BreachSeek successfully exploited vulnerabilities in exploitable machines within local networks, demonstrating its practical effectiveness and positioning it as an indispensable tool for cybersecurity professionals.

Abstract

The increasing complexity and scale of modern digital environments have exposed significant gaps in traditional cybersecurity penetration testing methods, which are often time-consuming, labor-intensive, and unable to rapidly adapt to emerging threats. There is a critical need for an automated solution that can efficiently identify and exploit vulnerabilities across diverse systems without extensive human intervention. BreachSeek addresses this challenge by providing an AI-driven multi-agent software platform that leverages Large Language Models (LLMs) integrated through LangChain and LangGraph in Python. This system enables autonomous agents to conduct thorough penetration testing by identifying vulnerabilities, simulating a variety of cyberattacks, executing exploits, and generating comprehensive security reports. In preliminary evaluations, BreachSeek successfully exploited vulnerabilities in exploitable machines within local networks, demonstrating its practical effectiveness. Future developments aim to expand its capabilities, positioning it as an indispensable tool for cybersecurity professionals.
Paper Structure (18 sections, 6 figures)

This paper contains 18 sections, 6 figures.

Table of Contents

  1. Introduction
  2. Literature Review
  3. Model Architecture and Implementation
  4. Graph-Based Approach Using LangGraph
  5. General Model Workflow
  6. Specific Architecture for Penetration Testing
  7. Implementation Environment
  8. Testing Methodology
  9. Web UI
  10. Results
  11. Future Work
  12. Human Intervention
  13. Fine Tuning
  14. Retrieval-Augmented Generation (RAG)
  15. Dynamic and Engaging Responses for Enhanced Interaction
  16. ...and 3 more sections

Figures (6)

  • Figure 1: The general workflow of such models
  • Figure 2: The specific workflow used by our model
  • Figure 3: The clean web UI when you start chatting with model
  • Figure 4: The AI agents performing a task
  • Figure 5: The web UI when the task is done
  • ...and 1 more figures