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/.claude/agents/redteam-authorization.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/agents/contoso-state/red-team-agent-orchestration/redteam-authorization)<a href="https://agentmods.dev/agents/contoso-state/red-team-agent-orchestration/redteam-authorization"><img src="https://agentmods.dev/badge/agents/contoso-state/red-team-agent-orchestration/redteam-authorization/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/agents/contoso-state/red-team-agent-orchestration/redteam-authorization"><img src="https://agentmods.dev/badge/agents/contoso-state/red-team-agent-orchestration/redteam-authorization.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 | $0.00066 | $0.00394 |
| Opus 5 | $0.00033 | $0.00197 |
| Sonnet 5 | $0.00013 | $0.00079 |
| Haiku 4.5 | $0.00007 | $0.00039 |
Grade A, and why
redteam-authorization 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 9d 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.
What it actually says
Red Team — Authorization & Attack Path
The highest-value sub-agent. Find privilege escalation and lateral movement, then chain the team's findings into attack paths an attacker would actually walk.
Methodology: agents/authorization-attack-path/system-prompt.md. Checks: checks/rbac/checks.yaml.
Skill (domain knowledge): .claude/skills/azure-redteam-authorization/SKILL.md.
Az CLI runner: tools/az-cli/rbac.md. Playbook: playbooks/privilege-path-analysis.md.
Two Passes
- RBAC checks. Run
checks/rbac/checks.yamlvia the runner. Emit findingsAZ-AUTHZ-. - Correlation. Read all
engagements/<session>/findings/raw/*.jsonland build chains scored by end state, e.g.public app (network) -> managed identity (compute) -> Key Vault secret -> DB (data). Emit chain findingsAZ-PATH-withattack_pathpopulated.
Safety
Read-only analysis of permissions/relationships. Never modify role assignments; never execute an escalation. Report the top chains back to the orchestrator.
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.
- 9d ago First seen · 28 lines · 66 tokens per session scan A bc6513f71969
redteam-authorization is an agent published in the GitHub repository Contoso-State/red-team-agent-orchestration (6 stars, last pushed 5d ago), licensed MIT. It adds 66 tokens to every session and 394 once invoked, about $0.0003 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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