risk-quantification

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.

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.

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

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

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.

Industrial cybersecurity risk quantification platform for OT attacks and financial exposure built with LangGraph.