Dreadnode provides the infrastructure necessary to operationalize and scale agentic cyber capabilities. It allows security teams to deploy, evaluate, and monitor autonomous agents while maintaining complete control over data and models through self-hosting and local inference support.
Key Features
- AI Red Teaming: Specialized platform for testing machine learning models and multi-agent systems for safety and security risks.
- Attack Playbooks: Includes 83 automated web application penetration testing playbooks and Active Directory assessment agents.
- DreadIndex: A performance benchmark of large language models (LLMs) against real-world offensive cybersecurity tasks.
- Sovereignty & Control: Support for on-premises deployment and self-hosted model inference to ensure operational data remains internal.
- Observability & Traceability: Full execution traces to investigate agent behavior and map findings back to specific tool calls.
- Agent Evaluation: Integrated framework for testing agent performance using LLM judges and task-specific success criteria.
Use Cases
- Scaling Red Team Operations: Automating repetitive scanning and exploitation tasks through specialized cyber agents.
- AI Safety Testing: Probing LLM-based applications for jailbreaks, prompt injections, and logic failures.
- Continuous Vulnerability Assessment: Running automated web and network discovery agents connected to existing C2 tools.
- Benchmarking LLMs: Using DreadIndex to select the most cost-effective and capable models for specific offensive workflows.
