FRAMEWORK VALIDATION & METHODOLOGY

Built on Data.
Tested Against Reality.

AI-CRRQ™ combines documented assumptions with historical cyber incident analysis and structured simulation. The Survival Index™ was calibrated against aggregated public breach data (2020–2025) and stress-tested with 10,000+ Monte Carlo simulation iterations across realistic scenarios. This is a directional model under continuous calibration — it is not yet a validated predictor of real-world incident outcomes. AI-CRRQ™ is building a live client outcome dataset to test real-world predictive accuracy over time.

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5
Years of Historical Breach Data Analyzed
(2020–2025)
10K+
Monte Carlo Simulation Iterations
Across Realistic Attack Scenarios
6+
Established Frameworks Mapped Against
NIST · ISO · FAIR · NYDFS · SEC · DORA

Five-Year Historical Breach Data Analysis

AI-CRRQ™ was calibrated against aggregated and anonymized data from major cyber incidents across financial services, healthcare, and critical infrastructure sectors from 2020 through 2025.

What the Data Covered

Root causes of operational failure and survival across major incident types

Time-to-containment and operational downtime by sector and organization size

Leadership response effectiveness under active cyber crisis conditions

Recovery velocity — from initial event to operational resumption

Correlation between preparedness indicators and survivability outcomes

AI-related incidents including model compromise, data poisoning, and agentic AI failures

Key Finding

📊

In our internal simulation modeling, ORCI showed the largest effect on modeled survivability. Organizations with strong Operational Response Capability Index scores — leadership clarity, practiced crisis protocols, and cross-functional coordination — showed faster simulated recovery and higher modeled likelihood of continued operations, even under high threat exposure conditions. This internal finding informed ORCI's weighting as the primary determinant of survivability in the model; it reflects model construction, not yet a proven real-world relationship.

🔗

TEI as denominator reflects modeled pressure dynamics. In our simulations, organizations facing elevated threat exposure showed reduced survivability regardless of resilience investments — supporting TEI's position as the denominator in the Survival Index™ formula rather than a simple additive variable, within the model as currently constructed.

Monte Carlo Simulation — 10,000+ Iterations

Extensive simulation modeled thousands of realistic cyber attack scenarios, including emerging AI-specific threat vectors, to stress-test the Survival Index™ scoring model under varied conditions.

Attack Scenarios Modeled

🔐
Ransomware
Multiple variant types across healthcare and financial services
🔗
Supply Chain Compromise
Third-party vendor and software dependency attacks
🤖
AI Model Poisoning
Corrupted training data and model manipulation scenarios
Prompt Injection
Enterprise LLM and agentic AI system attacks
🎭
AI Social Engineering
Deepfake impersonation and voice cloning at scale
💾
Destructive Attacks
Wiper malware and critical infrastructure disruption

Simulation Variables

Each simulation incorporated real-world probability distributions for detection time, leadership response effectiveness, third-party AI dependency exposure, backup integrity, recovery velocity, and regulatory notification obligations — enabling the model to reflect realistic operational dynamics rather than idealized scenarios.

Result: Strong internal consistency between Survival Index™ scores and simulated operational continuity outcomes across all 10,000+ iterations — demonstrating the model behaves stably across scenarios. This confirms internal consistency, not real-world predictive validity, which is being tested through an ongoing client outcome research program.

Simulation volume reflects computational stress-testing across scenario variations, not the number of organizations studied, and should not be interpreted as independent validation of predictive accuracy.

Mapped Against Established Frameworks

AI-CRRQ™ was stress-tested against established risk and regulatory frameworks to identify gaps, confirm complementary positioning, and ensure regulatory alignment across major compliance regimes.

NIST CSF 2.0

Control and maturity-focused. AI-CRRQ™ adds the operational survivability layer that NIST CSF does not directly measure.

ISO 27001

Information security management system. AI-CRRQ™ complements with operational continuity quantification under active threat conditions.

FAIR

Financial loss quantification model. AI-CRRQ™ adds operational survival dimension that FAIR's financial lens does not cover.

NYDFS Part 500

72-hour breach notification requirement. AI-CRRQ™ RVI scores map directly to notification and recovery timeline obligations.

SEC Cyber Rules

Material incident disclosure within four business days. AI-CRRQ™ supports operational impact quantification for disclosure decisions.

DORA

EU Digital Operational Resilience Act. AI-CRRQ™ survivability scoring maps to DORA's ICT resilience quantification requirements.

Ongoing Calibration

The AI-CRRQ™ model undergoes continuous calibration using emerging threat intelligence, updated breach data, and anonymized feedback from assessment engagements. This ensures the Survival Index™ remains current against the evolving threat landscape — including new AI-specific attack vectors as they emerge.

Which Scenarios Matter Most for Your Sector

While all 20 disruption scenarios apply to every organization, historical data and regulatory patterns show that certain scenarios carry disproportionate survivability risk by sector. Use this as a starting point for scenario prioritization.

Healthcare

Priority Scenarios

1

Ransomware — Clinical operations and patient care continuity

2

Mass Data Breach — PHI exposure and HIPAA 72-hour notification

3

Key Person Loss — Clinical technology leadership single points of failure

4

Pandemic / Workforce Crisis — Mass staff unavailability during patient surge

5

AI Model Failure — Clinical decision support systems acting outside boundaries

Financial Services

Priority Scenarios

1

Regulatory Enforcement Action — NYDFS exam failure, SEC consent order, Fed scrutiny

2

Business Email Compromise — Wire fraud at scale, C-suite impersonation

3

Cloud Provider Outage — Trading systems, payment processing, core banking

4

Supply Chain Attack — Third-party fintech and data vendor compromise

5

AI-Enabled Attack — Deepfake wire fraud, AI-powered phishing targeting finance teams

Government / Critical Infrastructure

Priority Scenarios

1

Power Grid Failure — Extended utility outage affecting critical operations

2

Natural Disaster — Geographic risk and supply chain concentration

3

Internet / Connectivity Takedown — Nation-state BGP hijack or ISP attack

4

Insider Threat — Privileged access abuse with national security implications

5

Data Center Fire — Physical infrastructure redundancy for critical services

Industry prioritization guidance is included in the professional assessment scoping conversation. A multi-scenario portfolio assessment covers all relevant scenarios for your sector and produces a complete Operational Survivability Portfolio for board reporting. Request a scoping conversation →

What the Data Shows. What It Doesn't Claim.

What AI-CRRQ™ Produces

  • A directional, scored survivability posture for executive decision-making
  • Specific gap identification at the vector level (ORCI, RVI, TEI)
  • Prioritized 30–90 day improvement roadmap
  • Board-ready documentation of operational resilience posture
  • Regulatory alignment mapping for NYDFS, SEC, DORA, FFIEC (advisory only — not legal or compliance advice)

What AI-CRRQ™ Does Not Claim

  • Actuarially precise risk probability predictions
  • A replacement for professional risk assessments or audits
  • Guaranteed security or resilience outcomes
  • Compliance certification of any kind
  • Specific incident outcome prediction
  • Proven predictive accuracy against real client outcomes (in progress — see below)
  • Proven predictive accuracy against real client outcomes (in progress — see below)

Ongoing validation: AI-CRRQ™ is building a live client outcome research program. Organizations completing a Professional Assessment may opt in to longitudinal outcome tracking, so that future Survival Index™ scores can be validated against real-world results rather than simulation alone.

Access to Full Technical Methodology

Detailed technical methodology, full simulation parameters, and supporting datasets are available under NDA for enterprise clients, research partners, and qualified organizations. The framework is designed to complement — not replace — your existing risk, governance, and compliance programs. It provides a shared survivability lens that security, GRC, legal, finance, and business teams can use collaboratively.

Request Methodology Brief →

Ready to Apply the Framework?

The free Survival Index™ calculator applies the validated scoring model to your organization in 60 seconds. For a facilitated professional assessment with the full methodology, request a briefing.

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