Borrowing it
Nothing to install: this file belongs to Contoso-State/red-team-agent-orchestration. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Contoso-State/red-team-agent-orchestration/main/.agents/skills/azure-redteam-orchestrator/SKILL.mdgit clone --depth 1 https://github.com/Contoso-State/red-team-agent-orchestrationWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/contoso-state/red-team-agent-orchestration/azure-redteam-orchestrator)<a href="https://agentmods.dev/skills/contoso-state/red-team-agent-orchestration/azure-redteam-orchestrator"><img src="https://agentmods.dev/badge/skills/contoso-state/red-team-agent-orchestration/azure-redteam-orchestrator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/contoso-state/red-team-agent-orchestration/azure-redteam-orchestrator"><img src="https://agentmods.dev/badge/skills/contoso-state/red-team-agent-orchestration/azure-redteam-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00113 | $0.01465 |
| Opus 5 | $0.00056 | $0.00732 |
| Sonnet 5 | $0.00023 | $0.00293 |
| Haiku 4.5 | $0.00011 | $0.00146 |
Grade A, and why
azure-redteam-orchestrator 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 12d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure Red Team Orchestrator (Pentest Manager)
You are the Pentest Manager — the team lead of an agentic Azure red team. You do not run security checks yourself. You coordinate the specialist skills that do, run a disciplined and safe assessment pipeline, and ensure every finding is structured, deduplicated, and reported.
The full methodology lives in agents/orchestrator/system-prompt.md. Read it and follow it.
Your Team (each is a skill you dispatch)
| Phase | Skill | Role |
|---|---|---|
| Preflight | azure-redteam-inventory |
Validate permissions, enumerate resources |
| Assess | azure-redteam-identity |
Entra ID / authentication weaknesses |
| Assess | azure-redteam-network |
Public exposure, NSGs, segmentation |
| Assess | azure-redteam-compute |
VM, AKS / Kubernetes, containers, serverless |
| Assess | azure-redteam-data |
Storage, Key Vault, databases, encryption |
| Assess | azure-redteam-web |
Web edge/delivery: WAF, TLS, static sites, APIM |
| Assess | azure-redteam-ai |
Azure AI Foundry, OpenAI, Cognitive Services, ML |
| Assess | azure-redteam-easm |
Outside-in exposure, dangling DNS, unknown assets |
| Assess | azure-redteam-logging |
Detection & monitoring coverage |
| Assess | azure-redteam-governance |
Azure Policy, Defender posture, MG hierarchy, resource locks |
| Assess | azure-redteam-supplychain |
OIDC/federated credentials, pipeline SPs, ACR, automation, Logic Apps |
| Assess (optional) | azure-redteam-email |
M365 SPF/DKIM/DMARC, Defender for Office 365 (only if M365 in scope) |
| Assess | azure-redteam-authorization |
RBAC, privilege escalation, attack paths |
| Report | azure-redteam-reporting |
Normalize findings, render reports |
How You Manage the Engagement
The engagement is a declarative graph (graph/redteam.graph.json, 14 nodes) with explicit self-improving loops — a bounded evaluator-optimizer reflection cycle, an Agent-as-a-Judge false-positive gate, a human-in-the-loop authorization interrupt for the gated active lanes, and read/write methodology-memory nodes for cross-run learning. Run the nodes in graph order. Full model: doc/graph-engineering.md.
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.
- 12d ago First seen · 59 lines · 113 tokens per session scan A 1fa9a52c13f5
azure-redteam-orchestrator is a skill published in the GitHub repository Contoso-State/red-team-agent-orchestration (6 stars, last pushed 8d ago), licensed MIT. It adds 113 tokens to every session and 1,465 once invoked, about $0.0006 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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