securing-mas

A security review method for multi-agent systems, where multiple software agents cooperate on tasks. It combines four established security and risk frameworks to examine threats, controls, governance, and certification needs.

In plain words
What is it for?
Use it to threat-model agent systems, review plugin security, design controls for agent pipelines, and assess systems against OWASP MAESTRO, MITRE ATLAS, NIST AI RMF, and ISO standards.
Why use it?
It gives teams a structured way to identify attacks and risks that can arise when agents, tools, and workflows interact.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/qte77/claude-code-plugins/securing-mas
Any agent
npx skills add qte77/claude-code-plugins --skill securing-mas
Clone the repo
git clone --depth 1 https://github.com/qte77/claude-code-plugins

Made for: Claude Code, Codex.

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 866 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00037 $0.00866
Opus 5 $0.00018 $0.00433
Sonnet 5 $0.00007 $0.00173
Haiku 4.5 $0.00004 $0.00087

Measured yesterday against content hash 8fd12d806ed9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

securing-mas scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/mas-design/skills/securing-mas/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Securing Multi-Agent Systems

Target: $ARGUMENTS

When to Use

Trigger this skill when:

  • Conducting security reviews of agent systems
  • Threat modeling for multi-agent architectures
  • Reviewing plugin implementations for security
  • Designing security controls for pipelines

Framework Stack

MITRE ATLAS (attack taxonomy — what adversaries do)
      |  informs threat identification
      v
OWASP MAESTRO (threat model — what to defend against in MAS)
      |  maps threats to controls
      v
NIST AI RMF (risk framework — how to govern/map/measure/manage)
      |  operationalized by
      v
ISO 42001 + 23894 (certifiable management system + risk methodology)

Use all four layers together: ATLAS enumerates attack vectors, MAESTRO maps them to MAS-specific controls, NIST AI RMF structures governance, and ISO provides the certifiable management system.

Workflow

  1. Review the framework stackreferences/mas-security.md for the conceptual overview of MAESTRO, ATLAS, NIST AI RMF, and ISO 42001/23894 layers working together.

  2. Apply the 7-layer security check — for each new component, walk through every MAESTRO layer. See references/maestro-7-layer-checklist.md for the actionable per-layer checklist (Model → Orchestration).

  3. Run the plugin security checklist — before marking an implementation complete, verify input validation, output safety, resource management, observability, and external dependencies. See references/plugin-security-checklist.md.

  4. Document threats in the cross-framework matrix — for each feature, map concerns to ATLAS techniques, MAESTRO layers, NIST functions, and ISO controls. Start from references/threat-matrix-template.md and add feature-specific rows.

  5. Avoid common vulnerability patterns — consult references/common-vulnerabilities.md for vulnerable/secure code examples: prompt injection (L1), type confusion (L2), resource exhaustion (L5), secret leakage (L6).

  6. Test security controls explicitly — write tests that exercise each MAESTRO layer's controls. See references/security-testing-patterns.md for pytest examples (input validation, timeout enforcement, error message safety).

Read the full file on GitHub · 69 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 69 lines · 37 tokens per session scan A 8fd12d806ed9

Subscribe to this mod's changes

securing-mas is a skill published in the GitHub repository qte77/claude-code-plugins (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 37 tokens to every session and 866 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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