{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/9"}],"enrichment":{"capability":"Dreadnode is an SDK for building, testing, and evaluating AI security agents with built-in tools for red teaming, observability, and systematic evaluation against datasets.","skillfed_tags":["ai-security","red-teaming","agent-framework"],"use_cases":["Build a multi-step security analysis agent that searches vulnerability databases and reports findings with automatic tracing.","Run systematic red teaming attacks against an LLM to find jailbreaks or unsafe outputs using TAP or Crescendo.","Evaluate a penetration-testing agent against a dataset of web applications with custom scorers measuring thoroughness and safety.","Deploy an AI agent as a FastAPI service with built-in observability and real-time scoring hooks.","Experiment with language-adapted red teaming by translating attack prompts or framing them in benign contexts."],"what_it_does":"Dreadnode is a Python SDK for building and testing AI security agents\u2014systems that reason over multiple steps, call tools, and produce observable traces of their execution. It provides decorators to define agents with tools and hooks, run them against datasets with composable scorers, and trace all steps via OpenTelemetry. The package also includes a suite of AI red teaming attacks (TAP, GOAT, Crescendo, AutoDAN-Turbo, ReNeLLM) designed to probe LLMs for safety and security failure modes by systematically generating adversarial prompts.\n\nThe SDK integrates with HuggingFace for dataset loading, supports deployment via FastAPI or Ray, and includes a TUI for interactive development and platform sync. It depends on a large ecosystem: boto3 and AWS SDKs for cloud services, litellm for LLM routing, fastapi for serving, optuna for hyperparameter tuning, and data libraries like pandas and numpy. Most workflows require external LLM API keys (OpenAI, Anthropic, AWS Bedrock) and will incur costs proportional to token usage.","worth_installing":"Yes, with conditions. Install if you are building or testing AI security agents and need a unified framework for agent definition, evaluation, and red teaming. The active maintenance, low install friction, and comprehensive feature set (agents, evaluations, red teaming, tracing) make it a solid choice for security-focused AI workflows. However, verify the license before use in proprietary projects, budget for LLM API costs, and confirm that the red teaming attacks meet your research or production requirements. The large dependency footprint may be a concern in resource-constrained deployments."},"id":"dreadnode","links":{"html":"https://skillfed.io/packages/dreadnode","md":"https://skillfed.io/packages/dreadnode.md","pypi":"https://pypi.org/project/dreadnode/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-23","license_spdx":null,"license_treatment":"unclear","name":"dreadnode","python_support":"supports_current","summary":"Dreadnode SDK"},"popularity":{"monthly_downloads":142431,"position":11209,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.0.38"}