Cross-Domain Threat Modeling
Multi-vector convergence analysis across biological, cyber, chemical, radiological, economic, geopolitical, climate, and AI threat surfaces — with cascading failure propagation and adversarial simulation.
Cross-Domain Threat Surfaces
Each cross-domain threat surface is modeled with explicit attack vectors, service integrations, compliance overlays, and cascading failure pathways.
Biological-Cyber Convergence
Services 24, 39, 43, 55Models the intersection of biological threats with cyber attack vectors — including attacks on laboratory information management systems (LIMS), electronic health records, biosurveillance networks, and genomic sequencing infrastructure. Simulates cascading failures where cyber intrusion enables biological data manipulation or surveillance blindness.
ATTACK VECTORS
- ◆LIMS compromise leading to false-negative pathogen detection
- ◆EHR manipulation creating phantom outbreak signals or suppressing real ones
- ◆Genomic sequencing pipeline poisoning via adversarial data injection
- ◆Biosurveillance network DDoS during active outbreak response
- ◆Supply chain firmware attacks on diagnostic equipment
- ◆Ransomware targeting vaccine cold-chain management systems
COMPLIANCE OVERLAY
CMMC Level 3, NIST SP 800-53, NDAA Section 889
Biological-Chemical-Radiological Nexus
Services 7, 15, 31, 42Multi-agent threat modeling for scenarios where biological, chemical, and radiological threats converge — either through deliberate adversarial action or cascading industrial/environmental failures. Models synergistic effects, detection interference, and response resource competition.
ATTACK VECTORS
- ◆Combined biological-chemical release in urban environments
- ◆Radiological contamination complicating biological sample collection
- ◆Industrial accident cascades triggering multi-hazard responses
- ◆Adversarial use of chemical agents to mask biological release signatures
- ◆Environmental contamination creating novel pathogen reservoirs
- ◆Cross-contamination of medical countermeasure supply chains
COMPLIANCE OVERLAY
EPA CERCLA, FEMA NRF, CDC/ATSDR guidelines
Geopolitical-Biological Threat Surfaces
Services 21-30, 71-80Models the intersection of geopolitical instability with biological threat emergence — including state-sponsored bioweapons programs, dual-use research exploitation, sanctions evasion through biological technology transfer, and conflict-zone biosurveillance gaps.
ATTACK VECTORS
- ◆State-sponsored dual-use research programs with offensive potential
- ◆Biological technology transfer through sanctions evasion networks
- ◆Conflict-zone biosurveillance collapse enabling undetected outbreaks
- ◆Refugee/displacement-driven disease transmission corridors
- ◆Adversarial exploitation of pandemic response for strategic advantage
- ◆Treaty non-compliance detection through open-source intelligence
COMPLIANCE OVERLAY
BWC, UNSCR 1540, Australia Group, Wassenaar Arrangement
Economic-Biological Cascading Failures
Services 31-40, Economic Impact AnalyticsModels how biological events trigger economic cascading failures — and conversely, how economic disruptions create biological vulnerability. Includes supply chain collapse modeling, pharmaceutical manufacturing concentration risk, and economic coercion through biological threat manipulation.
ATTACK VECTORS
- ◆Pharmaceutical supply chain single-point-of-failure analysis
- ◆API manufacturing concentration risk in adversarial nations
- ◆Economic coercion through threat of biological agent release
- ◆Pandemic-driven supply chain collapse cascading to medical countermeasures
- ◆Insurance/financial system stress from biological event uncertainty
- ◆Agricultural bioterrorism targeting food security and economic stability
COMPLIANCE OVERLAY
NDAA, BioSecure Act, DPA Title III, CFIUS review protocols
Climate-Biological Threat Emergence
Services 1-10, Environmental MonitoringModels how climate change creates novel biological threat surfaces — including permafrost pathogen release, vector range expansion, agricultural pest migration, and climate-driven population displacement creating disease transmission corridors.
ATTACK VECTORS
- ◆Permafrost thaw releasing ancient pathogens (anthrax, unknown agents)
- ◆Vector-borne disease range expansion (dengue, malaria, Zika northward migration)
- ◆Agricultural pest and pathogen migration threatening food security
- ◆Climate-driven displacement creating novel disease transmission corridors
- ◆Extreme weather events disrupting biosurveillance infrastructure
- ◆Ocean warming enabling marine pathogen proliferation
COMPLIANCE OVERLAY
WHO IHR, CDC climate-health guidelines, EPA environmental monitoring
AI-Biological Threat Convergence
Services 41-55, Cyberbiosecurity SuiteModels the intersection of artificial intelligence capabilities with biological threat creation — including AI-assisted pathogen design, automated gain-of-function research, AI-driven evasion of biosurveillance, and adversarial AI attacks on biodefense systems.
ATTACK VECTORS
- ◆AI-assisted de novo pathogen design using publicly available models
- ◆Automated gain-of-function research optimization
- ◆AI-driven evasion of biosurveillance detection algorithms
- ◆Adversarial AI attacks on biodefense decision-support systems
- ◆Deepfake biosurveillance data generation for strategic deception
- ◆AI-accelerated dual-use research with lowered expertise barriers
COMPLIANCE OVERLAY
EU AI Act, NIST AI RMF, Executive Order on AI Safety, BWC
Modeling Methodology
Multi-Vector Convergence Analysis
Simultaneous simulation of threats across biological, cyber, chemical, radiological, economic, and geopolitical domains using MPPT multi-branch decomposition.
Cascading Failure Propagation
Graph-theoretic modeling of how failures in one domain propagate to create vulnerabilities in adjacent domains — with quantified probability chains and intervention points.
Adversarial Red-Team Simulation
Automated adversarial agents probe cross-domain attack surfaces, identifying novel threat combinations that evade single-domain detection systems.
Scenario-Complete Branching
V-Framework mandates conservative, aggressive, and asymmetric scenario branches for every cross-domain threat model — ensuring no blind spots in preparedness planning.
Evidence-Anchored Confidence Scoring
Every cross-domain threat assessment includes explicit confidence intervals, evidence provenance chains, and contradiction registers — with blockchain-audited outputs.
Dynamic Threshold Adaptation
Self-modifying agents continuously adapt detection thresholds and alert criteria as cross-domain threat landscapes evolve — all within Helios governance rails.
Multi-Vector Threat Intelligence
No single-domain analysis captures the full threat landscape. Cross-domain modeling reveals the convergence points where real-world catastrophic risk emerges.