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 MingyiSecLab/Mingyi-Atlas --skill cloud-recongit clone --depth 1 https://github.com/MingyiSecLab/Mingyi-AtlasWrote 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/mingyiseclab/mingyi-atlas/cloud-recon)<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/cloud-recon"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/cloud-recon/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/mingyiseclab/mingyi-atlas/cloud-recon"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/cloud-recon.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 | $0.00034 | $0.02300 |
| Opus 5 | $0.00017 | $0.01150 |
| Sonnet 5 | $0.00007 | $0.00460 |
| Haiku 4.5 | $0.00003 | $0.00230 |
Grade C, and why
cloud-recon scanned grade C with 2 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 7d 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.
Cloud metadata endpointhighServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
# Internal: http://169.254.169.254/latest/meta-data/ Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s https://ip-ranges.amazonaws.com/ip-ranges.json | python3 -c " How it starts
The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cloud Infrastructure Reconnaissance Knowledge Base
Cloud reconnaissance identifies cloud-hosted assets, misconfigured storage, exposed services, and cloud-specific attack surfaces. Modern organizations run hybrid infrastructure — cloud recon is essential for complete attack surface mapping.
1. Cloud Provider Detection
Fingerprinting via DNS/Headers
See references/cloud-ip-ranges.md for the full CNAME → provider mapping table and response header fingerprinting. See references/cloud-naming-patterns.md for bucket/resource naming dictionaries.
# Check CNAME records for cloud indicators
dig <target> CNAME +short
# Common cloud CNAME patterns:
# AWS: *.amazonaws.com, *.cloudfront.net, *.elasticbeanstalk.com
# Azure: *.azurewebsites.net, *.blob.core.windows.net, *.azure-api.net
# GCP: *.googleapis.com, *.appspot.com, *.run.app, *.cloudfunctions.net
# Cloudflare: *.cdn.cloudflare.net
# Check IP ranges (AWS)
curl -s https://ip-ranges.amazonaws.com/ip-ranges.json | python3 -c "
import sys, json, ipaddress
data = json.load(sys.stdin)
target = ipaddress.ip_address('<TARGET_IP>')
for prefix in data['prefixes']:
if target in ipaddress.ip_network(prefix['ip_prefix']):
print(f\"AWS Region: {prefix['region']}, Service: {prefix['service']}\")
"
Cloud Service Indicators
| Indicator | Provider | Service |
|---|---|---|
s3.amazonaws.com CNAME |
AWS | S3 Storage |
X-Amz-* headers |
AWS | Various |
X-Ms-* headers |
Azure | Various |
X-Cloud-Trace-Context header |
GCP | Cloud Run/Functions |
*.elasticbeanstalk.com CNAME |
AWS | Elastic Beanstalk |
*.azurewebsites.net CNAME |
Azure | App Service |
*.appspot.com CNAME |
GCP | App Engine |
2. AWS Enumeration
S3 Bucket Discovery
# Common naming patterns
for prefix in <target> <target>-backup <target>-dev <target>-staging \
<target>-prod <target>-assets <target>-uploads <target>-logs \
<target>-data <target>-media www.<target> cdn.<target>; do
# Check if bucket exists
code=$(curl -s -o /dev/null -w "%{http_code}" "https://$prefix.s3.amazonaws.com/")
echo "$code $prefix.s3.amazonaws.com"
done
# Check bucket ACL (if accessible)
curl -s "https://<bucket>.s3.amazonaws.com/?acl"
# List bucket contents (if public)
curl -s "https://<bucket>.s3.amazonaws.com/?list-type=2&max-keys=20"
What ships with it
2 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.
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.
- 7d ago First seen · 265 lines · 34 tokens per session scan E ded1e703978c
cloud-recon is a skill published in the GitHub repository MingyiSecLab/Mingyi-Atlas (11 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 34 tokens to every session and 2,300 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (cloud metadata endpoint, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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cis-aws-foundations-2.2
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cis-aws-foundations-2.4
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cis-aws-foundations-2.5
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cis-aws-foundations-2.7
Eliminate use of the 'root' user for administrative and daily tasks.