Intelligent Continuous Security Marc Hornbeek

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• Foreword
• Preface
  • Conventions Used in This Book
  • OReilly Online Learning
  • How to Contact Us
  • Acknowledgments
• 1. Introduction to Intelligent Continuous Security
  • Definition and Overview
    • History of DevSecOps and SecOps
      • Timeline of SecOps evolution (20002025)
      • Timeline of DevSecOps evolution (20082025)
    • Definition of Intelligent Continuous Security
  • Importance of Intelligent Continuous Security in the Modern Threat Landscape
    • DevSecOps Risk Landscape
    • SecOps Risk Landscape
    • Continuous Security Risk Landscape
  • Regulatory and Compliance Landscape
    • Regulatory Landscape
    • Compliance Landscape
    • Real-Time Compliance and Security Audits
  • Summary
• 2. From DevSecOps and SecOps to Intelligent Continuous Security
  • Limitations of Separate DevSecOps and SecOps Practices
    • Limitations of the DevSecOps Approach to Software Security
    • Limitations of the SecOps Approach to Software Security
  • The Need for an Integrated Continuous Security Approach
    • Continuous Security: An Integrated Solution
    • Mitigating Exploits with ML for Continuous Security
    • AI-Augmented Tools for Continuous Monitoring and Response
      • Enhanced security collaboration and unified operations
      • Continuous learning and improvement
      • Recent examples of Intelligent Continuous Security in action
    • Generative AI and Its Vital Role in Intelligent Continuous Security
  • Summary
• 3. Foundations of Intelligent Continuous Security
  • Core Principles and Concepts
    • Security Embedded in Every Phase
    • Proactive, AI-Driven Threat Mitigation
    • Automation and Scalability
    • Unified Collaboration Across Teams
    • Continuous Improvement and Adaptability
  • What AI Can Do for Continuous Security
    • Proactive Threat Detection and Prevention
    • Security Workflow Automation
    • Real-Time Incident Response
    • Enhanced Threat Intelligence
    • Continuous Monitoring Support
    • Adaptive Learning and Improvement
    • Collaboration Across Teams
    • Conclusion
  • Limitations and Pitfalls for AI and Continuous Security
    • Data Quality and Bias
    • Overreliance on Automation
    • False Positives and Alert Fatigue
    • Cost and Resource Requirements
    • Lack of Transparency in AI Decisions
    • Vulnerability to Adversarial Attacks
    • Ethical and Privacy Concerns
    • Conclusion
  • Maturity Levels of Intelligent Continuous Security
    • Continuous Security Maturity Level Concepts
    • Level 1: Initial (Ad Hoc and Unpredictable)
    • Level 2: Managed (Defined at a Project Level)
    • Level 3: Defined (Standardized Across the Organization)
    • Level 4: Quantitatively Managed (Measured and Optimized)
    • Level 5: Optimized (Adaptive and Continuous Improvement)
  • Intelligent Continuous Security Concepts
    • Level 1: Initial (Ad Hoc and Unpredictable)
    • Level 2: Managed (Defined at a Project Level)
    • Level 3: Defined (Standardized Across the Organization)
    • Level 4: Quantitatively Managed (Measured and Optimized)
    • Level 5: Optimized (Adaptive and Continuous Improvement)
  • Intelligent Continuous Security Pillars of Practice
    • AI-Driven Continuous Security Culture
    • Intelligent Continuous Security Awareness and Training
    • Integrated Security Lifecycle
    • Automated and Adaptive Security Testing
    • Proactive Security Risk Intelligence
    • Intelligent Incident Response
    • Continuous Security Monitoring and Predictive Compliance
    • Security Feedback Loops and Continuous Evolution
  • Summary
• 4. Empowering Teams
  • Roles and Responsibilities
  • AI Center of Excellence
  • Collaboration Strategies
  • Team Topologies for Intelligent Continuous Security
    • Team Topologies That Work
      • The integrated security team
      • The CoE model
      • Embedded AI security expertise in teams
      • The platform team for security and AI
      • The hybrid topology for transitional organizations
    • Team Topologies to Avoid
      • The isolated security silo
      • The one-person security team
      • The overloaded platform team
      • The isolated AI CoE
      • The inflexible hierarchical structure
    • Overcoming Team Challenges
      • Addressing challenges in proven topologies
      • Transitioning from ineffective to proven topologies
  • Summary
• 5. Generative AI and Machine Learning for ICS
  • Generative AI for Continuous Security
  • Machine Learning for Continuous Security
  • Combining Generative AI and Machine Learning for Continuous Security
  • AI and ML Technologies for Continuous Security
  • Secure Supply Chain Management: Safeguarding Dependencies
  • Evaluating and Selecting AI Technologies for AI-Assisted Continuous Security
    • The Importance of a Methodical Approach
    • A Stepwise Process for Evaluation and Selection
    • Validating the Choice
    • Ethical Considerations in Evaluating AI Technologies for Security Applications
    • The Stakes of Ethical Missteps
    • Incorporating Ethical Considerations into the Evaluation Process
  • Governance and Accountability: Balancing Security and Ethics
  • Sustaining AI Technologies in Security Applications
  • Summary
• 6. Seven-Step Transformation Blueprint for ICS
  • Seven Transformation Blueprint Steps
    • Step 1: Leadership Visioning
      • Step 1 activities
      • Step 1 deliverable outputs
      • Tools to help with Step 1
        • Using the ICS maturity model to set strategic goals
        • Using a scorecard to choose which applications to transform
        • Using document templates
        • Using project management tools
        • Using an internal documentation site
    • Step 2: Team Alignment
    • Step 3: Discovery and Assessment
    • Step 4: Solution Mapping
    • Step 5: Realization
    • Step 6: Operationalize
    • Step 7: Expansion
  • Transformation Implementation Practices
    • The Role of the Transformation Consultant
    • AI-Assisted Tools and AI-Generated Templates
    • Phase-by-Phase Breakdown
      • Leadership Visioning and Team Alignment (Steps 1 and 2)
      • Discovery and Assessment (Step 3)
      • Solution Mapping (Step 4)
      • Realization, Operationalize, and Expansion (Steps 5, 6, and 7)
      • Why this framework works
  • Themes in the ICS Implementation Roadmap
    • Theme 1 Example: AI-Enabled Security MVP
    • Theme 2 Example: Standardization and Scaling
    • Theme 3 Example: Coverage Expansion
    • Theme 4 Example: Optimization and Continuous Improvement
    • Why This Approach Works
    • Continuous Security Macro-Flows (Epics)
      • Epics for Theme 1: AI-enabled security MVP
      • Epics for Theme 2: Standardization and scaling
      • Epics for Theme 3: Coverage expansion
      • Epics for Theme 4: Optimization and continuous improvement
      • Why macro-flows (epics) matter
  • AI-Assisted Templates
    • AI-Assisted Micro-Flows (Stories)
      • Example stories for Theme 1: AI-enabled security MVP
      • Example stories for Theme 2: Standardization and scaling
      • Example stories for Theme 3: Coverage expansion
      • Example stories for Theme 4: Optimization and continuous improvement
      • How these stories drive success
  • Common Pitfalls and Challenges: Sustaining ICS Solutions
  • Summary
• 7. ICS Technologies
  • ICS Technology Frameworks
    • Threat Intelligence
    • Vulnerability Management
    • Zero Trust Architecture
    • Secrets Management
    • Identity and Access Management
    • Immutable Infrastructure as Code
    • Secure Software Supply Chain
    • Security Observability
    • Detection Engineering
    • Security Monitoring
    • Automated Security Testing
    • Conclusion
  • ICS Testing Tools
    • Software Composition Analysis
    • Static Application Security Testing
    • Container Security Testing
    • Dynamic Application Security Testing
    • Interactive Application Security Testing
    • Fuzz Testing
    • Penetration Testing Automation
    • Vulnerability Scanning
    • Threat Modeling
    • API Security Testing
    • Cloud Security Testing
    • Load Testing for Security
    • SQL Injection Testing
    • Security Compliance Validation
    • Conclusion
  • ICS Integration Platforms
    • DIY Platforms: Custom-Built ICS Integration
    • CI/CD Platforms: Embedding Security in Software Delivery
    • Value Stream Management Platforms: Security as a Business Function
    • Automated Release Orchestration Platforms: Secure Deployments at Scale
    • Platform Engineering: Security as a Service Capability
    • SIEM: Centralized Threat Visibility
    • Security Orchestration, Automation, and Response: Automating Incident Response
    • Conclusion
  • ICS Dashboards
    • ICS Dashboard Requirements
    • ICS Dashboard Solutions and Best Practices
    • ICS Dashboard Challenges, Pitfalls, and Solutions
    • Real-World Example: The MOVEit Ransomware Attack
  • ICS Technology Governance Tools
    • Governance Practices
    • Governance Challenges
  • ICS Technology Transformation Tools
    • Defining ICS Technology Solution Requirements and Priorities
    • Selecting ICS Technology Solutions
    • Monitoring and Operating ICS Technology Solution Performance
    • Sustaining and Evolving ICS Technology Solutions
  • Summary
• 8. Real-World Applications and Use Cases
  • Large Enterprises with Siloed DevSecOps and SecOps Teams
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for Large Enterprises
  • Software Suppliers Separated from Their Customers
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for Software Suppliers and Customers
  • Government and Military Institutions Where Software Suppliers Are Separate from End Applications
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for Government and Military Environments
  • Network Software Manufacturers Separated from Network Systems Operators
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for Network Software and Network Operators
  • Cloud Service Providers and the Need for ICS Practices
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for CSPs
  • Financial Institutions Handling Large-Scale Transactions
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for Financial Institutions
  • Healthcare and Pharmaceutical Sectors
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for Healthcare and Pharmaceutical Sectors
  • Critical Infrastructure Operators: Energy, Utilities, and Transportation
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for Critical Infrastructure
    • The Benefits of ICS for Critical Infrastructure Security
  • Retail and Ecommerce Platforms
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for Retail and Ecommerce
  • DevOps Teams in CI/CD Pipelines with High Deployment Frequencies
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for CI/CD Pipelines
    • The Benefits of ICS for High-Velocity DevOps Teams
  • Organizations with Strict Regulatory and Compliance Requirements
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for Regulated Organizations
  • Multicloud and Hybrid Cloud Environments
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for Multicloud and Hybrid Cloud Environments
  • AI and ML Workloads in Security-Sensitive Environments
    • Security Concerns in Typical DevSecOps and SecOps Practices
    • Real-World Organizations That Match This Use Case
    • How ICS Practices Improve Security for AI/ML Workloads
  • Summary
• 9. Metrics for Intelligent Continuous Security
  • A Landscape View of ICS Metrics
    • Business Outcome Metrics
    • ICS Effectiveness Metrics
    • ICS Transformation and Improvement Metrics
    • Risk and Threat Exposure Metrics
    • Compliance and Governance Metrics
    • Aligning Metrics with ICS Goals
  • Business Outcome Metrics
  • ICS Effectiveness Metrics
  • ICS Transformation and Improvement Metrics
  • Risk and Threat Exposure Metrics
  • Compliance and Governance Metrics
  • ICS Measurement Observability
    • The Importance of ICS Observability
    • Observability Requirements Across ICS Metrics Categories
    • Designing an ICS Observability Strategy
    • Real-Life Examples of ICS Observability Design
  • ICS Security Architecture
    • The Five-Layer ICS Security Architecture Model
      • Collection layer
      • Smart data lake layer
      • Data API layer
      • Intelligent metrics application layer
      • Intelligent metrics user layer
    • Use Case: Custom Dashboards for ICS Metrics Categories
  • Sustaining a Reliable ICS Metrics Architecture
    • Tactics for Ensuring Sustainability, Reliability, and Adaptability
      • Implement excellent change management
      • Automate testing for all architecture components
      • Embed built-in health metrics
      • Design for scalability, performance, and ease of onboarding
      • Treat an ICS metrics architecture as a product, not just a project
      • Ensure security best practices for an ICS metrics architecture
    • The Consequences of Failing to Maintain a Sustainable ICS Metrics Architecture
  • Choosing ICS Metrics
    • Pitfalls to Avoid When Choosing ICS Metrics
      • Choosing too many metrics
      • Selecting metrics that are too complex
      • Using potentially unreliable metrics
    • Best Practices for Effective ICS Metrics Selection
  • Summary
• 10. The Future of Intelligent Continuous Security
  • Emerging Trends in Intelligent Continuous Security
    • People: Emerging Trends
    • Process: Emerging Trends
    • Technology: Emerging Trends
  • Preparing for Future Trends
    • Preparing for People Trends
    • Preparing for Process Change Trends
    • Preparing for Technology Trends
  • Summary
  • Final Thoughts
• A. Resources for Further Learning
  • Books
  • Websites
  • Articles, Blogs, Ebooks, and Webinars
  • Courses and Certifications
• Glossary of Continuous Security Terms
• Index

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