GeezerVison

Open-source adversarial testing engine, SDK, and CLI for AI agents.
Most testing tools test prompts. Humanbound tests agents.

Repositories · Quick Start · Usage · Documentation · Contributing

📖 Full documentation lives at docs.humanbound.ai — this README covers the essentials; the docs have the depth.

• Tests agents, not prompts. Drives real multi-turn conversations against your live endpoint instead of scoring one-shot completions.
• Probes tool use and scope. Attempts the actions your agent shouldn't take — over-scoped tool calls, boundary violations — not just unsafe text generation.
• Scores against your policy. Findings are evaluated against a security policy you define, not a generic safety rubric.
• Closes what it finds. hb guardrails turns failing test cases directly into deployable guardrail rules, so a single run both surfaces and fixes the gap.
• Local-first. Runs entirely on your machine with no account required; connect to the Humanbound Platform only if you want managed runs, history, and team dashboards.

Humanbound is split across a few focused repos rather than one monolith:

Repo	Description	Stars
humanbound	Open-source adversarial testing engine, SDK, and CLI for AI agents. Runs locally or against the Humanbound Platform.
humanbound-firewall	Multi-tier firewall for AI agents — blocks prompt injections, jailbreaks, and scope violations. Local tiers first; LLM judge only when uncertain.
plugins	Humanbound plugin marketplace for Claude Code and Cursor — adversarial security testing for local AI agents.
actions	Official GitHub Actions for Humanbound — adversarial security testing for AI agents in CI.

See all repositories → github.com/humanbound

pip install humanbound                       # CLI + SDK, core deps
pip install humanbound[engine]               # + OpenAI / Anthropic / Gemini / Ollama providers
pip install humanbound[firewall]             # + humanbound-firewall runtime
pip install humanbound[engine,firewall]      # everything

The commands below illustrate the shape of a typical run — check docs.humanbound.ai for the current, complete CLI reference before relying on exact flags.

Run an adversarial test suite against your endpoint:

hb run --endpoint https://api.yourapp.com/agent --policy policy.yaml

Convert failing tests into deployable guardrail rules:

hb guardrails --from-run last --out guardrails.yaml

Or drive it from the SDK:

from humanbound import Engine

engine = Engine(endpoint="https://api.yourapp.com/agent", policy="policy.yaml")
results = engine.run()

if results.failures:
    engine.guardrails.generate(results, out="guardrails.yaml")

Contributions welcome. See CONTRIBUTING.md for the dev loop, release process, and DCO sign-off requirement (see DCO.md).

• 🐛 Report a bug
• 💡 Request a feature
• 🔒 Report a security issue — not via public Issues
• 💬 Join Discord

Humanbound is licensed under the Apache License 2.0.