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 agentmods add skills/woohyun212/security-skill/cloud-pentestnpx skills add woohyun212/security-skill --skill cloud-pentestgit clone --depth 1 https://github.com/woohyun212/security-skillWrote 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/woohyun212/security-skill/cloud-pentest)<a href="https://agentmods.dev/skills/woohyun212/security-skill/cloud-pentest"><img src="https://agentmods.dev/badge/skills/woohyun212/security-skill/cloud-pentest.svg" alt="Measured on agentmods" 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 | $0.00032 | $0.02344 |
| Opus 5 | $0.00016 | $0.01172 |
| Sonnet 5 | $0.00006 | $0.00469 |
| Haiku 4.5 | $0.00003 | $0.00234 |
Grade A, and why
cloud-pentest 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 6d 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 — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
What this skill does
Performs a structured cloud security assessment across AWS, Azure, and GCP. Runs automated multi-cloud audits with ScoutSuite and Prowler, then performs deep manual analysis of IAM privilege escalation paths, storage exposure, network posture, and serverless configurations. Produces a findings report with CIS benchmark violations, attack narratives, and IaC remediation examples.
When to use
- When performing a cloud security posture assessment (CSPM) against an authorized environment
- When auditing IAM roles and policies for overpermissive grants or privilege escalation paths
- When checking storage buckets/blobs for public exposure or weak access controls
- When reviewing network security groups, NACLs, and VPC endpoint configurations
- When mapping serverless function attack surfaces (Lambda, Azure Functions, Cloud Functions)
Prerequisites
pip install scoutsuite prowler-cloud pacu
# ScoutSuite also requires cloud provider CLIs:
# AWS CLI: pip install awscli
# Azure CLI: https://learn.microsoft.com/cli/azure/install-azure-cli
# gcloud: https://cloud.google.com/sdk/docs/install
Inputs
| Variable | Required | Description |
|---|---|---|
SECSKILL_CLOUD_PROVIDER |
required | Target provider: aws, azure, or gcp |
AWS_PROFILE |
AWS | Named AWS CLI profile to use |
AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY |
AWS (alt) | Static AWS credentials |
AZURE_SUBSCRIPTION_ID |
Azure | Target Azure subscription ID |
GCP_PROJECT_ID |
GCP | Target GCP project ID |
SECSKILL_OUTPUT_DIR |
optional | Directory for results (default: ./output) |
SECSKILL_SCOPE |
optional | Comma-separated services to limit scan scope |
Workflow
Step 1: Identify cloud provider and validate credentials
export PROVIDER="${SECSKILL_CLOUD_PROVIDER:?Set SECSKILL_CLOUD_PROVIDER to aws, azure, or gcp}"
export OUTDIR="${SECSKILL_OUTPUT_DIR:-./output}"
TIMESTAMP=$(date -u '+%Y%m%dT%H%M%SZ')
mkdir -p "$OUTDIR"
case "$PROVIDER" in
aws)
echo "[*] Validating AWS credentials..."
aws sts get-caller-identity || { echo "[-] AWS credentials invalid"; exit 1; }
ACCOUNT_ID=$(aws sts get-caller-identity --query Account --output text)
echo "[+] AWS account: $ACCOUNT_ID"
;;
azure)
echo "[*] Validating Azure credentials..."
az account show --subscription "${AZURE_SUBSCRIPTION_ID:?Set AZURE_SUBSCRIPTION_ID}" \
|| { echo "[-] Azure credentials invalid"; exit 1; }
echo "[+] Azure subscription: $AZURE_SUBSCRIPTION_ID"
;;
gcp)
echo "[*] Validating GCP credentials..."
gcloud config set project "${GCP_PROJECT_ID:?Set GCP_PROJECT_ID}"
gcloud auth application-default print-access-token > /dev/null \
|| { echo "[-] GCP credentials invalid"; exit 1; }
echo "[+] GCP project: $GCP_PROJECT_ID"
;;
*)
echo "[-] Unknown provider: $PROVIDER (use aws, azure, or gcp)"
exit 1
;;
esac
echo "[+] Credential validation passed"
What ships with it
1 file 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.
- 6d ago First seen · 239 lines · 32 tokens per session scan A f00ea930f087
cloud-pentest is a skill published in the GitHub repository woohyun212/security-skill (21 stars, last pushed 4mo ago), licensed MIT. It adds 32 tokens to every session and 2,344 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 2026-08-30.
Other skills, from other repositories
gke-compute-classes
Configures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto…
gke-reliability
Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for disaster recovery setup or full cluster backups (use gke-backup-dr instead).
gke-workload-security
Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running cluster security audits (auditcluster.sh), configuring Workload Identity Federation (impersonation, KSA/GSA binding, and pod setup), enforcing Network Policies (default-deny…
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.
azure-mgmt-botservice-dotnet
Azure Resource Manager SDK for Bot Service in .NET. Management plane operations for creating and managing Azure Bot resources, channels (Teams, DirectLine, Slack), and connection settings. Triggers: "Bot Service", "BotResource", "Azure Bot", "DirectLine channel", "Teams channel", "bot management .NET", "create bot".
cloud-architect
Designs cloud architectures, creates migration plans, generates cost optimization recommendations, and produces disaster recovery strategies across AWS, Azure, and GCP. Use when designing cloud architectures, planning migrations, or optimizing multi-cloud deployments. Invoke for Well-Architected Framework, cost…