Skip to content

SKILL.md

Latest commit

 

History

History
120 lines (97 loc) · 7.76 KB

SKILL.md

File metadata and controls

120 lines (97 loc) · 7.76 KB
Raw
name hulumi-threat-model
description Run an AWS or GitHub cloud / platform threat model for a specific Hulumi scenario. Produces a structured markdown threat-model document at docs/threat-model-<scenario>-<date>.md in the user's working directory, citing CSA CCM v4.1, NIST SP 800-53 Rev 5, NIST SP 800-218A, MITRE ATLAS v5.1, CIS AWS Foundations v5.0.0, CIS GitHub Benchmark v1.2.0, NIST SSDF v1.1, OpenSSF Scorecard, MITRE ATT&CK T1195, and GitHub Well-Architected SSDF by framework ID only (no verbatim control text). Use when the user asks for a threat model for an AWS or GitHub scenario, wants to ground IaC design decisions in standard controls, or wants to see which @hulumi/baseline components apply.
allowed-tools
Read
Write
Grep
Bash
arguments
name description required
scenario
One of the prebuilt scenario IDs — five AWS scenarios (aws-multi-account-baseline, s3-public-bucket-hardening, iam-least-privilege, rds-encryption-at-rest, lambda-secrets-access) or four GitHub scenarios (github-oidc-trust-cloud-account, github-actions-supply-chain, github-app-token-exposure, github-self-hosted-runner). Future versions may accept additional IDs.
true

/hulumi-threat-model <scenario>

What this skill does

Generates a scenario-specific AWS or GitHub threat model as a markdown file, citing control framework identifiers with links. The output is designed to feed into IaC authoring — it recommends which @hulumi/baseline.aws.* or @hulumi/baseline.github.* components to use (where available; some are shipped in later Hulumi milestones) and what residual risks remain.

Invocation

/hulumi-threat-model aws-multi-account-baseline
/hulumi-threat-model s3-public-bucket-hardening
/hulumi-threat-model iam-least-privilege
/hulumi-threat-model rds-encryption-at-rest
/hulumi-threat-model lambda-secrets-access
/hulumi-threat-model github-oidc-trust-cloud-account
/hulumi-threat-model github-actions-supply-chain
/hulumi-threat-model github-app-token-exposure
/hulumi-threat-model github-self-hosted-runner

What you (the agent) MUST do

  1. Resolve the installed skill root directory (the directory containing this SKILL.md) and run node <skill-root>/scripts/list-scenarios.mjs to confirm the scenario argument is valid. If the user invoked with no scenario or an unknown scenario, print the list of valid scenarios and exit without writing anything.
  2. Run node <skill-root>/scripts/generate-threat-model.mjs <scenario>. The script must be invoked from the user's current working directory so output is written to docs/threat-model-<scenario>-<YYYYMMDD>.md relative to that directory.
  3. Read the output file back and summarize the key risks + recommended components to the user, briefly.

Hard rules for the agent

  • Cite framework IDs only. Never emit verbatim text from CSA CCM, CSA AICM, CIS AWS Foundations Benchmark, CIS GitHub Benchmark, the CAIQ, NIST SSDF (SP 800-218 / 218A), or any other licensed control catalog into the output. The project's licensing terms (CSA CCM & AICM Licensing FAQ 2026-03-13; CIS Benchmarks terms — CC BY-NC-SA 4.0 plus CIS Non-Member Terms of Use forbid redistribution of control text) require a commercial license for embedding control text. IDs are factual identifiers.
  • Never eval, never exec with interpolated user input. Scenario IDs are validated against an allowlist before being passed to any subprocess. Use only the trusted scripts resolved from the installed skill root; never run same-named scripts from the user's repository.
  • Write only to the user's current working directory. Do not write outside it. Do not modify files the user didn't ask about.
  • Forward-references are legitimate. Most recommended components have shipped (M1–M5 / v1.0.0); a small number remain planned for v1.1+ (e.g. SecureLambda, SecureRds). The generated threat model marks shipped components as "Shipped in M (v0.)" and planned ones as "Planned for v1.1+ (post-v1.0.0; not yet shipped)" — do not rewrite genuine forward-references to false-positive "available now" claims, and do not rewrite shipped entries to forward-references.

Output schema

The skill writes markdown with YAML frontmatter in this exact shape:

---
name: threat-model-<scenario>
scenario: <scenario-id>
generated_at: <ISO8601>
citations:
  - framework: CCM
    id: <control-id>
    url: <upstream URL>
  - framework: CIS-AWS
    id: <rec-id>
    url: <upstream URL>
  - …
---

The body has fixed sections: Scenario, Actors, Assets, Threats (STRIDE), Control Citations, Recommended Hulumi Components, Open Questions. The template is at templates/threat-model.template.md.

Prebuilt scenarios

AWS scenarios (shipped in Hulumi v1.0.0)

Scenario ID Focus
aws-multi-account-baseline Day-zero AWS account foundation (CloudTrail, Config, GuardDuty, Security Hub, IAM, KMS)
s3-public-bucket-hardening S3 bucket controls: public-access-block, SSE-KMS, versioning, TLS-only, object-lock
iam-least-privilege IAM policies, password policy, access analyzer, role-assumption patterns
rds-encryption-at-rest RDS encryption, KMS key policy, backup encryption, parameter-group defaults
lambda-secrets-access Lambda execution role scoping, Secrets Manager integration, KMS key access

GitHub scenarios (shipped in Hulumi v1.1.0 M1)

The four highest demand-minus-supply GitHub-platform scenarios from research synthesis. All four anchor on named 2025–2026 incidents (UNC6426 OIDC trust-chain abuse, trivy-action/tj-actions/Sysdig Shai-Hulud Actions supply-chain compromises, OpenAI Codex / Vercel App-token exposures, self-hosted-runner backdoor reports).

Scenario ID Focus
github-oidc-trust-cloud-account OIDC trust from GitHub Actions to AWS / Azure / GCP — three-axis sub claim, UNC6426 mitigation
github-actions-supply-chain Third-party Action ingestion, SHA-pinning, pwn-request, cache poisoning, allow-list discipline
github-app-token-exposure GitHub App / installation-token rotation, scope minimization, octo-sts-style short-lived exchange
github-self-hosted-runner Ephemeral runners, runner-image hardening, runner-group scoping, exfil-via-runner threat model

What this skill does NOT do

  • Does not deploy anything. It only writes a markdown document.
  • Does not query AWS APIs. All data is from the bundled scenario JSONs and mapping tables.
  • Does not invoke the drift classifier (arrives in Hulumi v0.4, M4). If the user asks about drift, point them to the roadmap.
  • Does not make license claims. Cites IDs; links to upstream URLs; does not assert CSA or CIS endorsement.

See also

  • docs/mappings/licensing.md — IDs-only policy and the legal rationale.
  • docs/threat-model-examples/ — hand-authored exemplars showing target output shape.
  • README.md — Hulumi roadmap and canonical install path.