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s0ld13rrs0ld13rr/pentestcode/skills/playbooks/cloud/SKILL.md

playbook-cloud

Skill884 starsChanged 4 months agoMITView on GitHub

Cloud IAM privesc paths and metadata endpoints per provider. Load when the target is cloud or you obtain cloud creds/metadata. Triggers - AWS/GCP/Azure, IAM, S3/blob, 169.254.169.254, access key.

  • Sends data out

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Default compute SA often has editor (overprivileged)

    line 29
  2. Very specific:

    Check for allUsers/allAuthenticatedUsers bindings (public access)

    line 32
  3. Distinctive:

    Run posture scan FIRST after getting creds — misconfig findings often beat privesc chains.

    line 50

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Cloud — Privesc Paths & Metadata

Metadata endpoints (different per cloud!)

AWS IMDSv1 (no header): curl http://169.254.169.254/latest/meta-data/iam/security-credentials/ AWS IMDSv2 (requires token):

TOKEN=$(curl -X PUT -H "X-aws-ec2-metadata-token-ttl-seconds: 21600" http://169.254.169.254/latest/api/token)
curl -H "X-aws-ec2-metadata-token: $TOKEN" http://169.254.169.254/latest/meta-data/

GCP (requires header): curl -H "Metadata-Flavor: Google" http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/token Azure (requires header): curl -H "Metadata: true" "http://169.254.169.254/metadata/identity/oauth2/token?api-version=2018-02-01&resource=https://management.azure.com/"

IMDSv1 vs v2 matters: v1 = any SSRF gives cloud creds. v2 requires PUT first (harder via SSRF).

AWS IAM privesc — dangerous permission combos

  • iam:CreatePolicyVersion → attach admin policy to self
  • iam:AttachUserPolicy → attach AdministratorAccess
  • lambda:CreateFunction + iam:PassRole → execute as privileged role
  • sts:AssumeRole → pivot to cross-account roles
  • ec2:RunInstances + iam:PassRole → launch instance with admin role Tools: pacu (automated), pmapper (permission graph)

GCP privesc

  • Default compute SA often has editor (overprivileged)
  • iam.serviceAccountKeys.create → generate key for any SA
  • cloudfunctions.functions.create + iam.serviceAccounts.actAs → RCE as SA
  • Check for allUsers/allAuthenticatedUsers bindings (public access)

Azure privesc

  • Managed Identity with broad role assignments
  • Contributor → deploy resources, potentially read Key Vault
  • App Registration with high API permissions + admin consent
  • Automation account runbooks → execute as automation identity

What to check everywhere

  • Public storage (S3/GCS/Blob) — --no-sign-request / anonymous
  • Secrets in repos / CI variables / build logs
  • User-data scripts (bootstrap credentials)
  • MFA not enforced on admin accounts
  • Audit logging disabled or misconfigured

Post-creds audit tools

  • AWS: pacu (exploitation framework, modular), pmapper (privesc graph)
  • Multi-cloud posture: scoutsuite (inventory + misconfig report per provider), prowler (AWS/GCP/Azure compliance checks, CIS benchmarks)
  • Run posture scan FIRST after getting creds — misconfig findings often beat privesc chains.

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