A collection of awesome projects, blog posts, books, and talks on quantifying risk
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Updated
Apr 13, 2020
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
Cybersecurity risk intelligence dashboard analyzing CVE vulnerabilities, CVSS risk scores, and financial exposure using Power BI.
Local-first quantitative cyber risk platform built on the FAIR methodology: Monte Carlo simulation, portfolio aggregation, and executive reporting. No cloud, no telemetry. (Beta)
Bayesian-inspired Impact Forecast Algorithm (IFA) for quantifying material impact risk
Offline, self-contained HTML tools for calibrated probability estimation training: practice trainer with Brier scoring, a nine-module course, and a verified question bank.
Open-source data breach cost predictor & cyber-risk quantification engine — IBM benchmarks + DPDP/GDPR penalties + Monte Carlo + security-investment ROI
19 interactive Jupyter notebooks for statistical decision-making in security: Monte Carlo, Bayesian, survival analysis, causal inference, FAIR.
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.
Vulnerability Financial Impact Engine — FAIR-lite Monte Carlo risk quantification that translates security findings into dollar-denominated expected loss
Vulnerability Financial Impact Engine — FAIR-lite Monte Carlo risk quantification that translates security findings into dollar-denominated expected loss
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.
Simple risk quantification framework with scoring model and executive summary examples.
Industrial cybersecurity risk quantification platform for OT attacks and financial exposure built with LangGraph.
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