Humanbound

Overview

Humanbound is an open-source adversarial testing engine, software development kit (SDK), and command-line interface (CLI) designed specifically for testing AI agents. It empowers developers to simulate realistic adversarial scenarios against their AI agents through multi-turn conversations, tool abuse, and live endpoints. This comprehensive testing framework allows for identifying vulnerabilities and turning each failure into actionable firewall rules, ensuring robust defenses for your AI systems.

Key Features

• Realistic Testing: Unlike traditional testing tools that focus solely on prompts, Humanbound tests the agents themselves, effectively probing tool usage and defining operational boundaries.
• Dynamic Defense Mechanism: The innovative hb guardrails feature automatically converts test failures into deployable firewall rules, enabling the creation of responsive security measures.
• Local and Cloud Compatibility: Humanbound runs seamlessly on local machines or can interact with the Humanbound Platform without the need for user authentication to initiate testing.

Getting Started with Humanbound

This project is structured to facilitate a swift onboarding process:

• A Quick Start guide is available to help users install the CLI and the SDK, including options for OpenAI, Anthropic, and other providers.
• Run tests against your AI agents using simple CLI commands:

  hb test --endpoint ./bot-config.json --repo . --wait
  

  This command initiates adversarial testing against your agent, storing results and insights in easy-to-understand formats.

Adversarial Testing Framework

Humanbound provides a powerful framework for adversarial testing, allowing you to:

• Identify vulnerabilities through live endpoints and interactive testing scenarios.
• Utilize the arena command to practice on intentionally vulnerable agent configurations, ensuring safe experimentation environments.

  hb arena run <agent>
  

Example Configuration

Configuring Humanbound for your agent involves defining endpoints for chat completions and session initiation in a bot-config.json file. Here's a sample structure:

{
  "chat_completion": {
    "endpoint": "https://your-bot.com/chat",
    "headers": {"Authorization": "Bearer <token>"},
    "payload": {"message": "$PROMPT"}
  },
  "thread_init": {
    "endpoint": "https://your-bot.com/sessions",
    "headers": {"Authorization": "Bearer <token>"},
    "payload": {}
  }
}

Continuous Improvement

Each testing run generates valuable training data that can be fed back into the system to enhance agent defenses, ensuring a proactive approach to security.

• Convert test findings into rules:

  hb guardrails -o rules.json
  

• Train classifiers using identified vulnerabilities to construct a protective barrier against potential exploits.

Extensive Documentation

Humanbound's comprehensive documentation is available at docs.humanbound.ai, providing in-depth guidance on all features, configuration options, and advanced usage.

Humanbound is a pioneering tool in adversarial testing for AI systems, merging offensive security practices with adaptive defensive mechanisms. It stands out as a unique open-source solution aimed at enhancing the robustness of AI agents in a rapidly evolving technological landscape.