CISA-X™

Cyber Intelligence & Secure AI Infrastructure eXecution Framework

According to IBM’s 2024 Cybersecurity Index, more than 62% of enterprises operating AI systems report critical security exposures that traditional cybersecurity tools fail to detect—leading to system downtime, compromised data, regulatory failures, and multimillion-dollar losses.

This is the critical gap CISA-X™ was designed to solve.

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Across the modern digital ecosystem

Organizations increasingly rely on AI-driven systems, cloud platforms, distributed ML workloads, and hyperscale compute infrastructure.

Yet despite heavy investments in digital transformation and AI adoption, most enterprises fail to secure these environments adequately.

Cyber attackers now exploit:

  • AI model vulnerabilities
  • Cloud misconfigurations
  • Weaknesses in distributed ML systems
  • Unmonitored data pipelines
  • Infrastructure blind spots
  • Outdated security frameworks not designed for AI-era threats

CISA-X™ turns cybersecurity from a reactive support function into a strategic, intelligence-driven protection engine that empowers organizations to transform:

  • From fragmented controls → to unified infrastructure defense
  • From manual detection → to autonomous AI-driven security
  • From system vulnerabilities → to predictive resilience
  • From operational risk → to measurable infrastructure reliability

Introducing the CISA-X™ Framework

Drawing from his specialization in AI infrastructure security, his hands-on work securing newly invented ML/AI servers at Google, and his peer-reviewed research on AI-powered threat detection, cloud vulnerabilities, and cybersecurity automation, Edoise Areghan developed CISA-X™, a proprietary enterprise cybersecurity framework engineered to unify:

  • Predictive cyber intelligence
  • Dynamic zero-trust enforcement
  • Cloud workload security
  • Threat detection using explainable AI
  • AI/ML infrastructure integrity
  • Automated containment of adversarial threats
  • Resilience measurement across distributed systems

It functions as:

  • A cybersecurity diagnostic engine
  • A predictive threat-intelligence architecture
  • A cloud workload risk scoring system
  • A governance and operational readiness model
  • A resilience and uptime measurement engine
  • A comprehensive AI infrastructure security blueprint

CISA-X™ is the first framework that synchronizes enterprise strategy + AI/ML security + cloud protection + threat intelligence + operational resilience into one unified solution.

What is CISA-X™?

CISA-X™ (Cyber Intelligence & Secure AI Infrastructure eXecution) is a five-pillar enterprise cybersecurity framework that evaluates an organization’s readiness to secure AI-powered infrastructure, applies predictive analytics to detect emerging threats, enforces zero-trust across distributed systems, strengthens ML model integrity, and measures the real stability and resilience outcomes of AI-driven operations.

The Five Strategic Pillars of CISA-X™

Identify

— AI-aware threat intelligence and vulnerability mapping

This pillar determines whether the organization understands its true exposure in the AI and cloud ecosystem.

It evaluates:

  • AI-specific attack vectors
  • Cloud workload vulnerabilities
  • Data pipeline weaknesses
  • Internal threat patterns
  • Adversarial behaviors linked to ML-driven systems
  • System blind spots and misconfigurations

Impact:
Organizations gain visibility into hidden risks across AI systems, cloud environments, and ML compute clusters - allowing proactive remediation instead of post-incident firefighting.

Protect

— Zero-trust architecture for AI/ML and cloud workloads

This pillar implements advanced protection mechanisms across distributed AI and cloud environments.

It includes:

  • Dynamic Zero-Trust enforcement
  • Micro-segmentation of ML servers
  • Identity and access hardening
  • Continuous validation of cloud interactions
  • Encryption and secret-management governance
  • Policy-driven access to training data and models

Impact:
Organizations establish a hardened AI infrastructure with strict verification across every device, entity, and interaction - blocking unauthorized lateral movement and preventing escalation of attacks.

Detect

— Explainable AI threat detection engines

This pillar integrates real-time detection and intelligence-driven monitoring into enterprise systems.

It assesses:

  • Anomaly detection accuracy
  • Behavioral monitoring for AI/ML workloads
  • Explainable AI (XAI) insights for security teams
  • Predictive breach indicators
  • Detection latency
  • Automated alert correlation

Impact:
Enterprises reduce detection time from hours to seconds, uncover hidden adversarial behaviors, and adopt explainable detection tools that enhance decision-making for security teams.

Respond

— Autonomous isolation and ML integrity controls

This stage evaluates organizational capacity to respond quickly and effectively to threats.

It measures:

  • Automated isolation of compromised nodes
  • Incident response orchestration
  • AI/ML integrity verification
  • Rollback and resilience strategies
  • Cross-functional communication during attacks
  • Forensic readiness and adversary tracking

Impact:
Organizations eliminate downtime, prevent system-wide failures, and maintain AI model integrity during attacks, ensuring critical operations remain uninterrupted.

Sustain

— Long-term resilience and compliance measurement

Most enterprises adopt AI and cloud systems but do not measure security resilience.

This pillar establishes quantifiable metrics, including:

  • Uptime reliability metrics
  • MTTR (Mean Time to Respond) improvement
  • ML integrity stability scores
  • Cloud risk-reduction performance
  • Compliance readiness
  • Attack-prevention ROI

Impact:
Organizations finally gain transparent visibility into the resilience and performance of their AI and cloud systems, enabling continuous optimization and long-term security maturity.

Use Cases and Industry Impact

Financial Services

  • AI-driven fraud detection
  • Cloud workload protection
  • Secure data-pipeline governance
  • High-availability infrastructure for real-time banking

Healthcare

  • Protection of AI diagnostic models
  • Secure handling of patient data
  • HIPAA-compliant cloud environments
  • Zero-trust architecture for sensitive infrastructure

Manufacturing & Smart Systems

  • Secure digital-twin pipelines
  • ML-driven automation integrity
  • Predictive maintenance security

Government & Defense

  • Threat intelligence acceleration
  • National-critical AI system protection
  • High-grade resilience protocols

AI & Cloud Enterprises

  • ML server security
  • Model integrity checkpoints
  • Autonomous containment for distributed systems

CISA-X™ becomes not just a framework, but an industry-transforming engine shaping how organizations defend AI-powered infrastructure in a threat landscape evolving faster than ever.

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