n8n workflow · multi-vector generator + deterministic gate
Phishing Sim Production Line
Calibrated multi-vector phishing training, produced at volume.
status running · private n8nrole designed + built end to end
The reviewer surface: four tiers, every planted red flag highlighted and named, 0 / 2 / 4 / 6 by design.
What it solves
Training sims need exact calibration. An Advanced tier hides one or two tells, Beginner plants five or six, and every flag has to be a real named indicator or the training data is worthless. The design decision that made this reliable: the model returns one clean original plus a per-tier injection plan, and deterministic code materializes all tiers and counts the spans, so token limits and JSON escaping can never corrupt a tier.
Who it serves
Security-awareness teams and MSPs running phishing training across clients and languages.
Who it is for
The content engineer who used to hand-author every sim.
How it works
- Brief inA brand, a scenario, and a target tier spread arrive on the webhook.
- Claude writes the originalOne clean phishing email, plus a per-tier injection plan that says which tells to add where.
- Code materializes every tierA deterministic node builds the four email tiers, SMS, and WhatsApp, wrapping each planted flag in a named span.
- The gate counts flagsIt re-checks span counts against the platform rules: 0 / 2 / 4 / 6, correct indicator names only. Wrong count or a blocked indicator is rejected.
- Human approvesA reviewer sees a tabbed preview of every vector with flags highlighted, and approves or sends back.
- Package outApproved sims export as upload-ready HTML, a landing page, an indicators sheet, and per-vector ZIPs.
Built with
n8n Claude (Sonnet) HTML sim builder span-count validator ZIP packager