IronClaw

Open source alternative to Grok Bot, Google Vertex AI Agent Builder, Amazon Bedrock Agents and Microsoft Copilot Studio

12.7K stars
Apache-2.0
Active this week
Last commit 2 days ago

Last verified Oct 20, 2026

Secure tool-using AI agents with an Apache-2.0 runtime for encrypted execution, vault-backed secrets, and NEAR AI Cloud deployment.

Visit website GitHub12.7K

Read the full breakdownWho it is for, how it works, trade-offs and the FAQ

who it's for

Who IronClaw is for#

AI teams testing tool-using agents

IronClaw fits teams that need repeatable checks before agents call internal tools, write data, or trigger workflows.

Skip if:

Skip it if your LLM use case is read-only summarization with no tool access.

Security reviewers building agent test cases

Reviewers can encode expected failures and unsafe-action scenarios in a project-specific evaluation suite.

Skip if:

Use a broader AI governance platform if you need policy management, audit workflows, and enterprise reporting.

the problem

The problem it solves#

Agentic applications can take actions, call tools, and move data across systems, which makes casual prompt testing too weak. A demo that works once does not prove the agent behaves safely under adversarial or unexpected instructions.

AI teams need repeatable tests for unsafe behavior before agents reach real credentials, money movement, customer systems, or production automation.

how IronClaw solves it

How it solves it#

Agent security focus

IronClaw centers on testing agent behavior rather than generic model chat quality. That focus fits teams adding tool access or automation to LLM applications.

Evaluation workflow

The project provides a public codebase for building and running agent evaluations, giving teams a concrete place to encode unsafe-action scenarios.

Apache-2.0 project code

Apache-2.0 licensing supports internal evaluation programs and commercial AI product teams that need to adapt the toolkit.

strengths · trade-offs

Strengths and trade-offs#

Strengths

Tests the action layerIronClaw is useful because agent risk often lives in tool calls and decision loops, not only in text output. That makes it relevant before connecting agents to sensitive systems.
Useful for early safety gatesTeams can use IronClaw-style evaluations while designs are still changing, instead of waiting for a formal security review at launch.

Trade-offs

-Needs team-specific scenariosAgent risk depends on the tools, permissions, and data an application exposes. IronClaw still requires teams to write evaluations that match their product.
-Not a full governance platformTeams still need access control, logging, incident response, and human review around agent deployments.

tech stack · detected from GitHub

What it's built on#

Languages: PythonRustTypeScript
Frameworks: React
Runtimes: WebAssembly

frequently asked

FAQ#

What is IronClaw for?

IronClaw is for evaluating and securing AI agents, especially agents that can take actions through tools.

What license does IronClaw use?

IronClaw is Apache-2.0 licensed.

Does IronClaw replace a security review?

No. It can support security testing, but teams still need threat modeling, access controls, and operational review.

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Who IronClaw is for#