Risk Engine for Modern Security Teams

Binary³ Risk Quantification Engine (RQE)

Transform raw security findings into dollar-based risk scores. RQE converts vulnerability data, threat intelligence, and asset context into quantified financial impact — so you can prioritize what matters most to your business.

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See Research & Methodology →

Cybersecurity Threat Management & ROI

This is the financial model the RQE API exposes programmatically — quantifying the dollar impact of proactive cyber defense.

STEP 01

Total Cost of Cyber Attack

TC = C_d + C_i
STEP 02

Annual Probability of Attack

P_a = 1-(1-P)^(1/Y)
STEP 03

Annualized Loss Expectancy

ALE = TC × P_a
STEP 04

Annualized Program Cost

ACC = C_prog / N
STEP 05

Gross Margin Impact

GMI = (ALE × Eff) - ACC

Full methodology, variable definitions, and worked numerical example available in the research white paper below.

RESEARCH WHITE PAPER
Binary³ RQE White Paper
Cybersecurity Threat Management & Gross Revenue Margin Impact
PDF  |  7 Pages  |  v2.0

What's Inside
  • Formal variable notation for all five steps
  • Poisson model alternative for probability annualization
  • NPV-adjusted program cost formula
  • Worked numerical example — $200M firm
DOWNLOAD
Download the Full White Paper

Institutional-grade methodology. Peer-reviewed formulas. Board-ready worked example.

Download White Paper

or
Try the Interactive Simulator → Questions? Contact support@binarycubed.com

Risk Engine Capabilities

All engine capabilities are available through the RQE REST API.

Mathematical Scoring

Likelihood × Impact × Category Weight × Severity Multiplier — normalized to 0-100 risk scores.

Three Risk Branches

Identity, Perimeter, and Logging branches map findings to specific attack surfaces.

Exposure Modeling

Monte Carlo simulations model potential loss distributions and confidence intervals.

Assumption Detection

AI-powered detection of hidden assumptions in your risk calculations.

Cost-Benefit Analysis

Compare remediation costs against potential loss reduction with ROI projections.

API-First Architecture

RESTful JSON API designed for seamless integration into your existing workflows.

Remediation Tracking

Track remediation progress and measure risk reduction over time.

Historical Trend Modeling

Analyze risk trends over time to identify patterns and forecast future exposure.

View API Endpoints →

Unified Security Data Pipeline

RQE ingests findings from all Binary³ products and third-party sources into a single risk model.

Identity Branch

KeySweep credential detection + RedLure phishing simulation findings feed identity risk scores.

Perimeter Branch

MicroDefend vulnerability scans + Phoros security assessments map external attack surface.

Logging Branch

LogSentinel log analysis + ForensIQ incident data track detection & response capabilities.

Ready to Plug RQE Into Your Product?

Embed real-time risk scoring into your SaaS, dashboard, or automation pipeline.

Start Building With RQE

Choose your path: explore the API for developers or dive into the research methodology.