ironcurtain: A secure runtime for autonomous AI agents. Policy from plain-English constitutions. (

by provos · MCP Server · ★ 615

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install ironcurtain

npm install -g @provos/ironcurtain
git clone https://github.com/provos/ironcurtain.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 74/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentmcpmodel-context-protocolpolicysandboxsecuritytrusted-process

Quick Facts

Stars615
Forks82
LanguageTypeScript
CategoryMCP Server
LicenseApache-2.0
Quality Score74/100
Open Issues24
Last Updated2026-10-30
Created2026-02-21
Platformsmcp, node
Est. Tokens~20k

About ironcurtain

IronCurtain A secure\ runtime for autonomous AI agents, where security policy is derived from a human-readable constitution. \When someone writes "secure," you should immediately be skeptical. What do we mean by secure? [!WARNING] Research Prototype. IronCurtain is an early-stage research project exploring how to make AI agents safe enough to be genuinely useful.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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