What this template does
Transforms provider documentation (URLs) into an auditable security baseline. It:
- Fetches and sanitizes HTML
- Uses AI to extract security requirements (strict 3-line TXT blocks)
-
Composes enforceable controls (strict 7-line TXT blocks with true-equivalence consolidation)
-
Builds a final baseline (TXT) with a
Technology: header
- Returns a downloadable
.txt via webhook and can append/create the file in Google Drive
Why it’s useful
Eliminates manual copy-paste from docs and produces a consistent, portable baseline ready for review, audit, or enforcement tooling. Ideal for rapidly generating or refreshing baselines across cloud providers or services.
Multicloud support
The workflow is multicloud by design. Pass the target cloud in the request and route the same pipeline for:
-
AWS, Azure, GCP (out of the box)
- Extensible to other providers/services by adjusting prompts and routing logic
How it works (high level)
-
POST /create (Basic Auth) with { cloudProvider, technology, urls[] }
- Resolve Google Drive folder (search-or-create) and generate a per-run
uuid
- Download & sanitize each URL
- AI pipeline: Extractor → Composer → Baseline Builder (TXT-only contracts)
- Append or create file in Drive and return a downloadable .txt
Inputs
{
"cloudProvider": "AWS",
"technology": "Amazon S3",
"urls": [
"https://docs.aws.amazon.com/AmazonS3/latest/userguide/security-best-practices.html"
]
}
Outputs
-
File:
controls_<technology>_<timestamp>.txt (downloaded from the webhook)
-
If nothing valid: JSON with
NO_CONTROLS_FOUND and troubleshooting hints
Credentials
-
OpenAI (kept in n8n’s Credential Manager; no API keys in HTTP headers)
-
Google Drive OAuth2 (optional file operations)
-
Basic Auth (protects the webhook endpoint)
Customization & extensions
This template is intentionally modular and can be extended to match your governance model:
-
Prompt-reflective techniques: add reflection/revision passes to increase precision, reduce hallucination, and enforce stricter formats.
-
Compliance assistants: plug additional assistants to analyze/label controls against frameworks like HIPAA, PCI DSS, SOX (and others), emitting mappings, gaps, and remediation notes.
-
Implementation context: feed internal implementation docs, runbooks, design records, or Architecture Decision Records (ADRs); have the pipeline extract requirements from these sources and use them as grounding for new/updated controls.
-
Local/self-hosted LLMs: swap the OpenAI nodes for a local LLM endpoint (self-hosted) to keep data on-prem while preserving the pipeline.
-
Provider-specific outputs: extend the final stage to export Policy-as-Code or IaC snippets (e.g., Rego/Sentinel rules, CloudFormation Guard, ARM/Bicep, Terraform validations).
-
Threat-model tags: include STRIDE/mitigation tags or risk scoring fields in the 7-line control blocks if your process requires it.
Security & privacy
- No hardcoded secrets in HTTP nodes; use n8n’s Credential Manager.
- Drive operations are optional and folder-scoped.
- For sensitive environments, switch to a local LLM and provide only sanitized/approved inputs.
Notes
- Sticky Notes on the canvas summarize Overview, Setup & Credentials, and Run & Troubleshooting.
- Works best with documentation pages that return clean HTML; large/JS-heavy pages may require longer HTTP timeouts.
