Dreadnode Offensive Security Agents is a platform for deploying, building, evaluating, and improving AI-driven agents designed for offensive security operations. The platform ships with a library of pre-built agents ("Strikes") that can be deployed directly into existing environments, as well as tooling for users to bring and customize their own agent code. Core operational use cases supported include: - Vulnerability research: reverse engineering binaries, source code analysis, fuzzing support, and exploit creation - Network operations: integration with command-and-control (C2) frameworks to support red-team engagements beyond basic shell access - Web application testing: browser automation, tool automation, and follow-up attack chaining for bug bounties and SAST workflows - Threat intelligence gathering: ingesting raw data from multiple sources and pivoting between relational datasets The platform includes an agent evaluation and observability layer ("cyber evals") that provides: - Full agent tracing across inference calls, tool executions, and task workflows - Metric-based evaluation frameworks for comparing agent architectures and model configurations - Task-specific custom scoring attached to individual tasks and tools within a workflow - Synthetic data generation for scaling evaluations and producing fine-tuning datasets Agents and models can be iteratively trained and tuned through tight feedback loops, and then deployed into operational workflows. The platform targets security teams looking to augment offensive operations with AI-assisted automation.