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.
npx skills add iamsecure1920/Cordon-AI --skill cordon-cloudgit clone --depth 1 https://github.com/iamsecure1920/Cordon-AIWrote 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/iamsecure1920/cordon-ai/cordon-cloud)<a href="https://agentmods.dev/skills/iamsecure1920/cordon-ai/cordon-cloud"><img src="https://agentmods.dev/badge/skills/iamsecure1920/cordon-ai/cordon-cloud/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/iamsecure1920/cordon-ai/cordon-cloud"><img src="https://agentmods.dev/badge/skills/iamsecure1920/cordon-ai/cordon-cloud.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 | $0.00064 | $0.00639 |
| Opus 5.5 | $0.00026 | $0.00256 |
| Sonnet 5.5 | $0.00013 | $0.00128 |
| Haiku 4.5 | $0.00006 | $0.00064 |
Grade A, and why
cordon-cloud 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 1mo 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cordon cloud
Two very different positions. Conflating them is how people end up testing infrastructure they were never authorized for.
Outside, without credentials
cloud_asset_discovery(keyword="acme")
Guesses storage names against provider endpoints. Read the result carefully:
in_scope— covered by your scope artifact. Safe to look at.found_but_unverified— a matching name is not ownership. A bucket calledacme-backupsmay belong to a completely different Acme. Do not touch these, do not report them as the program's, and do not "just check if it's public".
A publicly readable bucket that is in scope is a real finding. Prove it by listing it once and stopping — do not download the contents. The report needs "this was world-readable", not a copy of the data.
Inside, with credentials the program gave you
cloud_permissions(profile, provider) # CloudFox: principals, permissions, privesc
cloud_audit(provider, severity="high,critical") # Prowler: posture checks
cloud_attack_paths(provider) # graph: what reaches what
k8s_posture(framework="nsa") # Kubescape
All read-only, all logged in the account's audit trail. That is fine and expected — but tell the client, because a sudden burst of enumeration API calls looks exactly like an intrusion to their detection team.
What actually makes a cloud finding
A list of failed benchmark checks is a checklist, not a report. What earns a severity rating is reachability: an internet-facing function that can assume a role that can read the production database, in two hops.
Prioritize in this order:
- Findings that sit on an attack path from an unauthenticated entry point.
- Validated credentials with real blast radius (see
cordon-validate). - Public data exposure.
- Everything else — posture observations, reported as such.
Full attack-path graphs need Cartography with a Neo4j backend; without it,
cloud_attack_paths returns Prowler's own path data only and says so.
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.
- 1mo ago First seen · 69 lines · 64 tokens per session scan A f21fd5eed3d6
cordon-cloud is a skill published in the GitHub repository iamsecure1920/Cordon-AI (0 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 639 once invoked, about $0.0003 per session on Opus 5.5. 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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