cloud-security

cloud-security is a skill for Claude Code from hypnguyen1209/offensive-claude. It costs 52 tokens per session (2,513 once invoked), scanned B, original, MIT.

A guide to assessing security in AWS, Azure and Google Cloud environments. It covers cloud identities, virtual machines, containers, Kubernetes, deployment pipelines and infrastructure configuration.

In plain words
What is it for?
Testing identity-permission escalation, metadata-service attacks, cross-account access, Kubernetes breakouts, CI/CD secrets, infrastructure-as-code settings and cloud persistence.
Why use it?
Cloud systems connect permissions, accounts and services in complex ways, making it easy for one weakness to lead to broader access.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the offensive-claude plugin — 30 skills, 18 commands, 8 agents, 1 hook shipped together

Good fit Testing identity-permission escalation, metadata-service attacks, cross-account access, Kubernetes breakouts, CI/CD secrets, infrastructure-as-code settings and cloud persistence.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hypnguyen1209/offensive-claude/cloud-security
Install

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.

Any agent
npx skills add hypnguyen1209/offensive-claude --skill cloud-security
Clone the repo
git clone --depth 1 https://github.com/hypnguyen1209/offensive-claude

Made for: Claude Code.

Or install offensive-claude, the plugin that ships this one along with the rest of its 30 skills, 18 commands, 8 agents, 1 hook.

Wrote 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.

agentmods badge for cloud-security

README.md
[![agentmods](https://agentmods.dev/badge/skills/hypnguyen1209/offensive-claude/cloud-security.svg)](https://agentmods.dev/skills/hypnguyen1209/offensive-claude/cloud-security)
Your own site
<a href="https://agentmods.dev/skills/hypnguyen1209/offensive-claude/cloud-security"><img src="https://agentmods.dev/badge/skills/hypnguyen1209/offensive-claude/cloud-security.svg" alt="Measured on agentmods" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,513 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 5 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 16
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 91
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Server-Side Request Forgery · line 105
    Code accesses a cloud instance metadata endpoint (e.g. 169.254.169.254). A single request can return temporary IAM credentials, making this a high-value SSRF target for credential theft.
    Fix: Remove access to cloud metadata endpoints unless strictly required. If metadata is needed, restrict it (e.g. IMDSv2 with hop limit) and never expose returned credentials.
  • high Privilege Escalation · line 108
    Potential security issue detected. Manual review is recommended.
    Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
  • medium Data Exfiltration · line 96
    Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.
    Fix: Verify the destination bucket is trusted and owned by you. Never upload credentials, secrets, or workspace contents to external or unverified cloud storage.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.02513
Opus 5 $0.00026 $0.01256
Sonnet 5 $0.00010 $0.00503
Haiku 4.5 $0.00005 $0.00251

Measured 8d ago against content hash 6a04310a29c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade B, and why

cloud-security scanned grade B with 1 finding 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 8d ago.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/aws_privesc_enum.py, scripts/entra_device_code_phish.py, scripts/gcp_impersonation_mapper.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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 endpointmediumServer-side request forgery

One request to 169.254.169.254 can return temporary IAM credentials.

| IMDS SSRF | VPC flow to 169.254.169.254 from web tier; STS use from new ASN | GuardDuty `UnauthorizedAccess:IAMUser/InstanceCredentialExfiltration*` (creds used off-instance) | Use creds from same egress IP where possi

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

skills/cloud-security/SKILL.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cloud Security & Attack

When to Activate

  • Cloud penetration test / red team against AWS, Azure (Entra ID), or GCP
  • IAM / identity privilege escalation and cross-account or cross-tenant pivoting
  • Compromised web app or SSRF reachable from cloud compute — harvest metadata credentials
  • Kubernetes / container assessment, node breakout, cluster takeover
  • CI/CD and IaC review: Terraform state, OIDC federation trust policies, pipeline secrets
  • Post-exploitation: secret extraction, lateral movement, persistence in cloud control plane

Technique Map

Technique ATT&CK CWE Reference Script
AWS IAM privesc (CreatePolicyVersion, PassRole, AttachPolicy) T1098.001 CWE-269 references/aws-iam-privesc.md scripts/aws_privesc_enum.py
AWS sts:AssumeRoot member-account escalation T1078.004 CWE-269 references/aws-iam-privesc.md scripts/aws_privesc_enum.py
Cross-account confused deputy / missing ExternalId T1078.004 CWE-441 references/aws-iam-privesc.md scripts/oidc_trust_auditor.py
IMDS / metadata SSRF credential theft (AWS/Azure/GCP) T1552.005 CWE-918 references/imds-metadata-ssrf.md scripts/imds_harvester.py
EKS node creds → IRSA / Pod Identity pivot T1552.007 CWE-668 references/imds-metadata-ssrf.md scripts/imds_harvester.py
Entra device-code phishing → PRT / device join T1528 CWE-287 references/azure-entra-attacks.md scripts/entra_device_code_phish.py
FOCI refresh-token family abuse T1550.001 CWE-613 references/azure-entra-attacks.md scripts/entra_device_code_phish.py
Azure Managed Identity / App-Admin → SP escalation T1098.001 CWE-269 references/azure-entra-attacks.md scripts/imds_harvester.py
GCP actAs + resource create impersonation chain T1078.004 CWE-269 references/gcp-attacks.md scripts/gcp_impersonation_mapper.py
GCP serviceAccountTokenCreator token chains T1528 CWE-269 references/gcp-attacks.md scripts/gcp_impersonation_mapper.py
Vertex AI P4SA / Ray head-node escalation T1078.004 CWE-732 references/gcp-attacks.md scripts/gcp_impersonation_mapper.py
Container escape (runc Leaky Vessels CVE-2024-21626) T1611 CWE-668 references/kubernetes-container-escape.md -
IngressNightmare (CVE-2025-1974) cluster takeover T1190 CWE-94 references/kubernetes-container-escape.md scripts/k8s_can_i_abuse.py
K8s RBAC privesc (pods/exec, token mount, node proxy) T1078 CWE-269 references/kubernetes-container-escape.md scripts/k8s_can_i_abuse.py
Terraform state secret extraction T1552.001 CWE-312 references/iac-secrets-ci-cd.md scripts/oidc_trust_auditor.py
OIDC federation trust-policy abuse (GitHub/TF Cloud) T1199 CWE-441 references/iac-secrets-ci-cd.md scripts/oidc_trust_auditor.py

Read the full file on GitHub · 120 lines

Changes

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.

  1. 8d ago First seen · 120 lines · 52 tokens per session scan B 6a04310a29c0

Subscribe to this mod's changes

cloud-security is a skill published in the GitHub repository hypnguyen1209/offensive-claude (357 stars, last pushed 21d ago), licensed MIT. It adds 52 tokens to every session and 2,513 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (cloud metadata endpoint). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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