risk-quantification

A collection of awesome projects, blog posts, books, and talks on quantifying risk

Interactive CRQ Monte Carlo simulation tool for quantifying cybersecurity risk using FAIR methodology. Built for EU SMBs, vCISOs, and security practitioners.

FAIR cyber risk quantification toolkits, agent-based control simulation (FAIR-CAM), threat event frequency estimator (PyPI), LLM classification validator (PyPI), Monte Carlo risk engine with IRIS benchmarks.

Reusable decision-science utilities for security: Monte Carlo, Bayes, Survival, VoI, light causal helpers.

Bayesian risk modelling and quantification notebooks for cybersecurity

Evidence-governed quantitative cyber risk — a trustworthy CLI and scenario engine where every number traces to a reviewed public source.

Local-first quantitative cyber risk platform built on the FAIR methodology: Monte Carlo simulation, portfolio aggregation, and executive reporting. No cloud, no telemetry. (Beta)

Cybersecurity risk intelligence dashboard analyzing CVE vulnerabilities, CVSS risk scores, and financial exposure using Power BI.

Simple risk quantification framework with scoring model and executive summary examples.

Open-source data breach cost predictor & cyber-risk quantification engine — IBM benchmarks + DPDP/GDPR penalties + Monte Carlo + security-investment ROI

Bayesian-inspired Impact Forecast Algorithm (IFA) for quantifying material impact risk

Threat modeling case study applying PASTA (7-stage) and FAIR (Monte Carlo) to quantify ransomware risk in a HIPAA-regulated SaaS environment. Includes control investment ROI analysis and presentation talking points.

Agentic, controls-as-code GRC engine: one SCF-mapped control set → every framework. OSCAL-validated, FAIR-quantified, policy-as-code, human-gated AI. CI proves it.

Vulnerability Financial Impact Engine — FAIR-lite Monte Carlo risk quantification that translates security findings into dollar-denominated expected loss

What does a bad year cost — and can you prove the number? Which shared dependency drags everything down at once? Did an AI agent just touch a tool it never should have? How fast do you really detect? Three working tools answer — from seeded, sealed data you can re-check in your browser.

Vulnerability Financial Impact Engine — FAIR-lite Monte Carlo risk quantification that translates security findings into dollar-denominated expected loss

FAIR Monte Carlo cyber risk quantification: translates technical vulnerabilities into probable financial loss distributions, then has Claude draft the board narrative. Next.js + Recharts + Trigger.dev + Supabase.

Cyber risk analysis, offline in a single HTML file — EBIOS RM threat modeling, MITRE ATT&CK kill chains, and Monte-Carlo risk quantification. Open-source companion to Aurelian Risk Manager.

GitHub profile README: GRC engineering, FAIR cyber risk quantification, compliance-as-code, and AI-assisted GRC.

SMC model (Markov Chains + Attack Graphs) for cloud security risk quantification — 9-component architecture, Monte Carlo simulation, countermeasure scenario analysis. Validated against IBM X-Force & CSA 2022.