Deadend: An Agentic Pentest Tooling

Table of Contents

1. Introduction and Results
2. Failure Analysis
3. Demo
4. Next Improvements and Research
5. Contribute

Introduction and Results

Deadend represents a revolutionary approach to offensive security testing by leveraging AI agents to automate and enhance penetration testing workflows. Our agentic architecture enables intelligent automation of security assessments, allowing security teams to conduct comprehensive pentests faster and more efficiently than traditional methods.

The initial results demonstrate significant improvements in both speed and coverage. Our AI agents can autonomously navigate complex attack surfaces, identify vulnerabilities, and generate detailed security reports with minimal human intervention.

Failure Analysis

Understanding failure modes is crucial for improving our agentic pentest tooling. Through extensive testing and evaluation, we’ve identified several key areas where our agents encounter challenges:

• Complex multi-step attacks: Agents sometimes struggle with attacks requiring multiple interdependent steps
• Context preservation: Maintaining context across long-running security assessments remains a challenge
• False positive management: Distinguishing between actual vulnerabilities and false positives requires refinement

These insights drive our continuous improvement efforts and help us build more robust and reliable security testing agents.

Demo

Experience Deadend in action through our interactive demo. The tool demonstrates how AI agents can:

• Automatically discover and enumerate attack surfaces
• Execute sophisticated penetration testing techniques
• Generate comprehensive security assessment reports
• Adapt to different target environments and configurations

Try the demo to see how agentic pentest tooling can transform your security testing workflow.

Next Improvements and Research

Our roadmap includes several exciting developments:

• Enhanced agent coordination: Improving multi-agent collaboration for complex security assessments
• Advanced vulnerability detection: Integrating cutting-edge AI models for better threat identification
• Real-time adaptation: Developing agents that can adapt their strategies in real-time based on target responses
• Integration capabilities: Expanding support for popular security tools and frameworks

We’re actively researching new approaches to make agentic security testing more effective, reliable, and accessible.

Contribute

We welcome contributions from the security and AI communities! Whether you’re interested in:

• Improving agent capabilities
• Adding new attack modules
• Enhancing documentation
• Reporting bugs or suggesting features

Your contributions help make Deadend better for everyone. Check out our GitHub repository to get started, or join our Discord community to connect with other contributors.