Cloud should be a choice
Adopt cloud services because they suit your needs, not because they're your only option.
Welcome
Hi, I'm Michael.
Cybersecurity shouldn't be exclusive. I believe everyone deserves access to practical, professional grade cybersecurity tools, training, and services, without prohibitive costs or the need for years of technical expertise. My goal is to bridge the gap between complex security practices and real-world usability, making cybersecurity accessible, understandable, and achievable for individuals and businesses alike.
Ethos
What I Believe In
Knowledge should be within reach
Practical cybersecurity expertise should be accessible, understandable, and available to everyone.
Security is attainable
Effective cybersecurity is built through practical, achievable steps, not unlimited budgets or specialist teams.
Capability over complexity
The best security solutions are the ones people can confidently use.
Local-First Software
Everything runs on your machine: one executable, one database file you own. No cloud, no accounts, no telemetry.
Open Source
Published in the open on GitHub: free to inspect, verify, and extend. Trust should never require faith.
Portfolio
Tools built to be trusted
Software for people who have to defend a number in front of a board. Free and open during beta; commercial editions will land here when they're ready.
FORLAS CRQ
Flagship
Beta
A local-first quantitative cyber risk platform built on the FAIR methodology. Model loss scenarios, run Monte Carlo simulations, aggregate a whole portfolio, and produce boardroom-ready reports, all from a single desktop application with one database file that you own.
- FAIR-based scenario modelling with Monte Carlo simulation
- Portfolio aggregation and loss exceedance curves
- PDF and Word reporting, ready for executives and auditors
- Fully offline: one executable, one SQLite file, zero external services
View on GitHub
Free during beta
Calibration Trainer
Open source
Self-contained, offline HTML tools that train subject matter experts to give calibrated probability estimates before their inputs reach a quantitative risk model. Based on the estimation training method popularised by Douglas Hubbard: repeated testing with immediate feedback until stated confidence matches actual accuracy.
- 240-question bank across interval and binary rounds
- Brier scoring, hit rates, and a live calibration curve
- Nine-module self-paced course with a printable completion certificate
- Single HTML files: no build step, no network calls, runs from disk
View on GitHub
Free and open source
Contact
Get in touch
Questions about the tools, beta feedback, or commercial interest: all welcome.