security-adventure

1. High-Volume Batch Processing

N8n workflows configured with internal looping and queue management to digest thousands of records over time without hitting API timeouts.

2. "Sliding Window" Context Management

A Python-based chunking_utility.py securely structures long PDF/Word documents into overlapping RAG-optimized pieces while perfectly preserving root ECCC metadata (consultation ID, entry ID).

3. Automated Metadata Validator

An integrated pre-processor (metadata_validator.py) verifies incoming data against standard ECCC Controlled Vocabularies (e.g., verified Regions and Themes) before executing expensive GenAI operations.

4. Bilingual Parity Auditor

1. Mandatory Translation Parity:
   Triggers parallel analysis for French and English sources using Azure OpenAI endpoints based strictly in Canada East.
2. Mathematical Drift Detection:
   Analyzes sentiment outputs from both streams, calculating divergence. If the 'linguistic drift' exceeds the tolerance threshold, it flags the entry for human CDPS review via a Teams bot webhook.

1. Author scenarios
   Write each decision point as a node with: id, prompt, choices[], and optional effects (score, flags, inventory, time, detection risk).
2. Compile to a normalized graph
   Convert markdown / JSON / YAML into a single canonical graph model (nodes + edges + metadata).
3. Validate
   Fail fast on broken content: missing node ids, dead links, unreachable endings, cycles (if disallowed), and invalid effects.
4. Instrument & balance
   Compute helpful analytics: path lengths, expected risk, “dominant choice” detection, and story coverage.
5. Render a playable experience
   Use the normalized graph to drive a UI: show prompt, show choices, apply effects, track state, and record a run log.
6. Export outcomes
   Output the run transcript (JSON + human summary) for learning, audits, or classroom review.

{
  "id": "start",
  "prompt": "You receive an email claiming to be from IT...",
  "choices": [
    {"label": "Click the link", "to": "phished", "effects": {"risk": "+=20"}},
    {"label": "Report to security", "to": "good_call", "effects": {"risk": "-=5", "badge": "reporter"}}
  ]
}