Transform Cloud Documentation into Security Control Baselines with OpenAI and Google Drive

What this template does

Transforms provider documentation (URLs) into an auditable security baseline . En:

• 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)

1. POST /create (Basic Auth) with { cloudProvider, technology, urls[] }
2. Resolve Google Drive folder (search-or-create) and generate a per-run uuid
3. Download & sanitize each URL
4. AI pipeline: Extractor → Composer → Baseline Builder (TXT-only contracts)
5. 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 (eg, 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.