GraphCanon updated Sep 13, 2026 · GitHub synced Sep 13, 2026
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Decision brief
humanbound is an adversarial testing engine and SDK in Python designed specifically for evaluating the robustness of AI agents against various security threats.
Good fit when
- When you need to test your AI agent's resilience against prompt injection attacks, utilize humanbound’s specialized features tailored for this purpose
- For scenarios that require comprehensive multimodal security testing, including text, image and other modalities, humanbound offers detailed adversarial testing capabilities
Avoid when
- Avoid using humanbound if your project does not involve AI agents or is not concerned about adversarial robustness since the tool's functionality might be overly specific
- Do not use humanbound in environments where an open-source solution is restricted, particularly considering its licensing and trademark policies
Observed Jul 16, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (3d since push)
- As of Sep 13, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 13, 2026
- Security (OSV)
- No lockfile
- As of Jul 15, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install humanboundSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
An open-source adversarial testing engine that provides an SDK and CLI to test the robustness of AI agents locally or via the Humanbound Platform.
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Sep 13, 2026
- Languages
- python
Source: github.language+pyproject.toml · Sep 13, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 13, 2026)
pip install humanbound # CLI + SDK, core depsSource link
Tags
README
Install Docker Run the CLI from the official image (docs): License Apache 2.0. Free to use in any context — commercial or open source — with attribution. See TRADEMARK.md for the trademark policy. The code is open; the name is not. The sibling project is also Apache 2.0 — same li...
For agents
This page has a .md twin and JSON over the API.