AI Identities Governing the Next Generation of Autonomous Actors (Rosario Mastrogiacomo)（Z-Library）

AI Identities Governing the Next Generation of Autonomous Actors — Rosario Mastrogiacomo

AI Identities Governing the Next Generation of Autonomous Actors Rosario Mastrogiacomo

AI Identities: Governing the Next Generation of Autonomous Actors ISBN-13 (pbk): 979-8-8688-2033-5 ISBN-13 (electronic): 979-8-8688-2034-2 https://doi.org/10.1007/979-8-8688-2034-2 Copyright © 2025 by Rosario Mastrogiacomo This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Managing Director, Apress Media LLC: Welmoed Spahr Acquisitions Editor: Susan McDermott Development Editor: Laura Berendson Project Manager: Jessica Vakili Cover art was created by Laura Mastrogiacomo Distributed to the book trade worldwide by Springer Science+Business Media New York, 1 New York Plaza, New York, NY 10004. Phone 1-800-SPRINGER, fax (201) 348-4505, e-mail orders-ny@springer-sbm.com, or visit www.springeronline.com. Apress Media, LLC is a Delaware LLC and the sole member (owner) is Springer Science + Business Media Finance Inc (SSBM Finance Inc). SSBM Finance Inc is a Delaware corporation. For information on translations, please e-mail booktranslations@springernature.com; for reprint, paperback, or audio rights, please e-mail bookpermissions@springernature.com. Apress titles may be purchased in bulk for academic, corporate, or promotional use. eBook versions and licenses are also available for most titles. For more information, reference our Print and eBook Bulk Sales web page at http://www.apress.com/bulk-sales. If disposing of this product, please recycle the paper Rosario Mastrogiacomo Annandale, NJ, USA

For Jessica and Gavin

v Table of Contents About the Author xxi About the Technical Reviewer xxiii Introduction: Governing AI Identities in a Post-automation World xxv Part I: Identity Security 1 Chapter 1: The New Actors 3 AI Agents in Identity Workflows5 AI Agents Aren’t Coming; They’re Already Here 9 Chapter Summary 13 Chapter 2: Understanding Identity Security (Primer) 15 Human Identities 16 Machine Identities 17 Identity Lifecycle 18 Security Controls 19 Common Identity Risks 20 Why Machine Identity Was Already Hard—And Why AI Is Harder 23 Identity in the Age of AI 23 Chapter Summary 25 Chapter 3: Introducing AI Identities—Automation Reimagined 27 Introduction to Automation27 Traditional Automation 28 AI-Driven Automation (Non-agentic) 29

vi AI Agent Automation (Agentic AI) 31 Implications for Identity Security 33 Chapter Summary 34 Chapter 4: Identity Hygiene—Foundations for Securing All Identities 35 The Importance of Good Identity Hygiene 35 Key Components of Identity Hygiene 36 Ownership Clarity 36 Least Privilege and Access Control 36 Regular Recertification 37 Lifecycle Management 37 Continuous Visibility and Monitoring 37 Intelligent Discovery and Identity Hygiene 37 Consequences of Poor Identity Hygiene 38 AI Amplifies the Need for Identity Hygiene 39 Implementing Robust Identity Hygiene 39 Chapter Summary 40 Part II: Identity Security and AI 41 Chapter 5: Ownership As a Security Control 43 What Ownership Means 44 How Missing or Stale Ownership Introduces Risk 45 Ownership Is Identity Hygiene 46 Ownership Enforcement as a Control 47 Automating and Maintaining Ownership 47 Ownership for AI Identities 48 Chapter Summary 49 Key Takeaways 50 Table of ConTenTs

vii Chapter 6: What AI Agents Really Are—AI Identities and the Case for a New Category 51 AI Agents Are Intelligent Machine Identities52 The Need for a New Identity Type 54 Common Misconceptions: Why AI Agents Are Misclassified 62 IAM/IGA Failure Points: Blind Spots in Discovery and Ownership 62 IAM Vendors 64 IGA Vendors 65 PAM Vendors 66 What Vendors Aren’t Doing (Yet) 66 Technological Foundations: Machine Learning, Neural Networks, and LLM Architectures 68 The Dynamic and Unpredictable Nature of AI Identities 68 Managing Opacity Through Ownership and Auditing 69 Ongoing Oversight: A Continuous Activity 69 Transparency and Explainability in Governance 69 Introducing the RAISE Framework 70 Chapter Summary 71 Chapter 7: The Evolution of Identity Governance 73 Redefining Identity Models for AI Agents 74 Ownership and Lifecycle Management 74 Behavioral Monitoring and Risk Scoring 75 Centralized AI Identity Management System 76 Governance for Collaborative AI Agent Systems 76 Looking Forward 77 Chapter Summary 77 Table of ConTenTs

viii Chapter 8: Technical Implementation of AI Identity Governance 79 Core Challenge: Continuous Discovery and Visibility 79 Solution: Establishing an Independent Identity Center 80 Identity Center Operational Requirements 81 Policy Violation Detection and Remediation 82 Credential Misuse and Replay Attacks by AI Agents 83 What Makes AI Credential Use Different? 83 Real-World Example 84 Why Traditional PAM Isn’t Enough 84 Governance Must Evolve 85 Closing the Loop 86 Actionable Dashboards and Reporting 86 Workflow and Remediation Integration 87 Chapter Summary 88 Key Takeaways 88 Chapter 9: Delegation, Authority, and the Risk of Agent Autonomy 89 The Shift from Assistance to Authority 90 Understanding Horizontal, Vertical, and Recursive Delegation 90 Delegation Chains and Accountability Loops 91 The Dangers of Unchecked Autonomy 93 Delegation: From Agents to Networks 94 Replication: The Agentic Multiplier 94 Horizontal Delegation Risks: Visibility and Control 96 Recursive Delegation Risks: Exponential Complexity 97 Visibility: The Cornerstone of AI Agent Management 97 Historical Precedents: Lessons from Active Directory 97 Table of ConTenTs

ix Real-World AI Agent Failures Due to Autonomy Issues 98 Mitigating Delegation Risks: Practical Guardrails 99 Policy-Based Delegation Controls 100 Human Oversight: The Essential Safeguard 100 Chapter Summary 100 Part III: Securing AI Agents with RAISE 103 Chapter 10: The RAISE Framework for Governing AI Identities 105 Why a New Framework? 105 The RAISE Framework 106 R: Reveal 107 A: Assign Ownership 108 I: Interpret Behavior 108 S: Secure Autonomy 109 E: Evaluate Lifecycle Risk 109 How to Operationalize RAISE 110 Reveal: Continuous Discovery and Identity Awareness 111 Assign: Enforce Accountable Human Ownership 112 Interpret: Monitor and Explain Agent Behavior 113 Secure: Apply Least Privilege and Autonomy Constraints 114 Evaluate: Measure Risk, Drift, and Lifecycle Status 115 Recommendations for CISOs 116 Chapter Summary 116 Chapter 11: REVEAL—Discovery and Inventory of AI Identities 119 What Makes AI Identity Discovery Hard? 120 The Explosive Growth of AI Agents 121 Starting from What You Do Know: Account-Centric Discovery 122 Accountability and Liability in the Age of Autonomous Agents 122 Table of ConTenTs

x AI Agent Liability: What Changes, What Doesn’t 123 Shared Risk: Enterprise vs Vendor Accountability 124 What Every AI Vendor Contract Must Now Include 124 Regulatory Shifts That Will Impact AI Identity Governance 126 How to Structure Governance for AI Agent Accountability 127 Discovering AI Agents in SaaS and Shadow Environments 128 Declarative Discovery: Asking the Humans 129 Building a Living Inventory 130 Real-World Example: Large Medical Organization Breach 130 SPHEREboard and Advanced Discovery 131 Enhanced Metadata Collection for AI Agents 131 Comprehensive AI Agent Discovery Methods 132 Chapter Summary 132 Chapter 12: ASSIGN—Ownership in the Age of AI 135 So, How Do You Operationalize Ownership at Scale? 139 Chapter Summary 142 Chapter 13: INTERPRET—Trust, Explainability, and AI Agent Reputation 145 Why Trust Matters for AI Identities 146 AI Hiring Bias: Systematic Discrimination Hidden in Black Boxes 147 Tesla’s Persistent Autonomy Failures: When AI Oversight Falls Short 148 Explainability as a Pillar of Trust 149 Transparency 153 Building and Managing AI Agent Reputation 154 Example: AI Agent Reputation Dashboard 156 Continuous Monitoring vs Periodic Reviews (Event-Driven and Time-Based Models) 156 Table of ConTenTs

xi Trust and Explainability in Multi-agent Ecosystems 158 Maintaining Trust Through Life Cycles 159 Real-World Examples: Trust Breakdown and Recovery 161 Chapter Summary 167 Key Takeaways 167 Chapter 14: SECURE—Building Resilience into AI Identity Lifecycles 169 Rethinking the AI Identity Lifecycle for Security 170 Common Pitfalls and Failure Modes 172 Lessons from Human Identity Failures 172 Identity Hygiene As the Core Principle 173 Human Ownership and Control: Non- negotiable 173 Real-World Examples: The Emerging Risk of Prompt Injection 174 Designing an AI Identity Discovery Program 175 Why AI Discovery Requires a New Model175 Program Design: Strategic Pillars 176 Success Metrics 178 What Makes a Program Successful 178 Measurement and Enforcement 178 Compliance and Risk Metrics 179 Operational Performance Metrics 180 User/Entity Behavior Metrics 180 Program Maturity Metrics 181 Implementation Recommendations 182 Chapter Summary 183 Table of ConTenTs

xii Chapter 15: EVALUATE—The Lifecycle of an AI Identity 185 Challenges in Managing Identity Lifecycles 186 Primary Causes of Orphaned Machine Identities 187 Creation: Defining Purpose and Boundaries 190 Deployment and Operation: Monitoring and Maintenance 191 Decommissioning: Properly Retiring the Identity 192 Ensuring AI Identity Lifecycle Adherence 193 Practical Tools for Secure AI Identity Lifecycle Management193 Evaluate Is Not the End of RAISE 194 Chapter Summary 195 Part IV: Governance, Controls, and Risk Management 197 Chapter 16: Navigating Complex Regulatory and Compliance Frameworks for AI Identities 199 Europe: GDPR and EU AI Act 200 United States: Sectoral Privacy and State-Level Regulations 200 America’s AI Action Plan: Overview and Implications for AI Governance 201 China: Personal Information Protection Law (PIPL) 204 Other Regions 204 Cross-Border Data Transfers and International Complexity 204 Strategic Approaches to International Compliance 205 Integrated Governance Solutions for AI Identities 205 Core Metadata and Tracking 206 Conflict Detection and Alerting 206 Procedural Enhancements for Rigorous Compliance 207 Implementation Roadmap 207 Proactive Compliance Management: A Strategic Necessity 208 Table of ConTenTs

xiii Global Regulatory Matrix for AI Identity Compliance 209 Accountability and Liability in the Age of Autonomous Agents 209 AI Agent Liability: What Changes, What Doesn’t 210 Shared Risk: Enterprise vs Vendor Accountability 210 What Every AI Vendor Contract Must Now Include 211 Regulatory Shifts That Will Impact AI Identity Governance 213 How to Structure Governance for AI Agent Accountability 214 Recommendations for CISOs and Security Teams 215 Chapter Summary 216 Chapter 17: Inherited Risk—Managing Third- Party AI Identities in the Supply Chain 219 The Illusion of Transparency 220 The Access Tells 221 A Case Without a Name 221 Rethinking Vendor Due Diligence 222 Practical Contractual and Governance Safeguards for Third-Party AI Agents 223 Explicit Disclosure Requirements 223 Mandatory Explainability and Auditability Clauses 223 Defined Liability and Indemnification Terms 224 Human Oversight and Intervention Obligations 224 Right to Review and Periodic Assessment 224 Revisiting What You Already Own 224 Procurement As a Security Control 225 Chapter Summary 226 Table of ConTenTs

xiv Chapter 18: Malicious Use and Insider Threats in AI Identity Systems 227 The Hybrid Insider 227 Strategic Misuse: Not Just a Bug 228 Compromise Without Detection 229 The External Threat Loop 229 RAISE and the Malicious Actor 230 Beyond the Firewall 231 Planning for the Inevitable 232 Chapter Summary 232 Chapter 19: When AI Goes Off Script—Real-World Agentic AI Failures 233 Case 1: The ChatGPT Legal Hallucination 233 Case 2: The Air Canada Chatbot That Invented Policy 234 Case 3: AutoGPT’s Infinite Loop Problem 235 Case 4: Hallucinated Package Names and Slopsquatting Risk 236 Case 5: Failure at Scale—Error Accumulation in Agentic Workflows 237 Case 6: Prompt Injection and Privilege Escalation in Embedded Agents 238 Case 7: Grok’s Algorithmic Hate Speech and the Absence of Guardrails 239 When Failure Is the Default 240 Hard Truth: These Are Not Malfunctions 240 Chapter Summary 241 Chapter 20: Cognitive Instability in AI Agents—Security Risks from Misjudgment, Hallucination, and Drift243 AI Isn’t Infallible—It’s Unpredictable 243 What We Mean by Cognitive Instability 244 How These Issues Become Security Failures 245 Table of ConTenTs

xv The Identity Governance Impact 246 Applying the RAISE Framework 247 Design Principles for Mitigation 247 Chapter Summary 248 Chapter 21: Ethical Considerations and Responsible AI Governance249 Key Ethical Risks with AI Agents 250 Over-reliance and Deskilling: Silent Threats 251 When Human Agency Fades251 Case 1: Virtual Recruiters Replace First Contact 252 Case 2: Bias Hidden in Automation 252 Case 3: Outsourcing Judgment in Healthcare 253 Principles for Preserving Human Agency 253 1 Human-in-the-Loop by Design 253 2 Explainability and Challengeability 253 3 Human Override with Accountability 254 4 Role Demarcation 254 5 Periodic Impact Review 254 AI Identity Governance As Ethical Infrastructure 254 Ethical Oversight Requires Comprehensive Governance 255 Embedding Ethical Governance into Enterprise AI 256 Operationalizing Ethical Frameworks 257 Integrating Ethical Governance with Risk Management 257 Practical Implementation Steps 258 Addressing Governance Challenges 258 Future Governance Models 259 Chapter Summary 260 Table of ConTenTs

xvi Part V: Resilience and Response 261 Chapter 22: Security Controls and Countermeasures for AI Identities 263 Technical Controls for AI Identity Security 263 AI-Specific Authentication and Authorization 263 Guardrails and Privilege Escalation Prevention 265 AI Model and Data Integrity 265 Adversarial Training 265 Differential Privacy 266 Data Sanitization Pipelines 266 API and Tool Security 267 Strict API Monitoring and Tool Invocation Guardrails 267 Encryption and Key Management 267 Homomorphic Encryption (HE) 268 Dynamic Key Rotation 268 Administrative and Governance Controls 268 Zero Trust Architecture 268 AI-Specific Threat Intelligence 269 Compliance and Auditing 269 Incident Response for AI 269 Human-Approved Circuit Breakers 269 Chapter Summary 270 Chapter 23: Incident Response and Resilience for AI Identities 271 The Challenge of Early Detection in AI Incidents 272 AI Identity Breaches as Insider Threats 272 Immediate Response Steps for a Rogue AI 274 Table of ConTenTs

xvii Investigating Multi-agent Failures 274 Frameworks and Drills for AI Incident Response 275 Chapter Summary 275 Chapter 24: Forensics for AI Identities 277 Unique Incident Response Challenges 277 AI-Specific Incident Response Planning 278 Essential Forensic Data Collection 278 Identity Lifecycle Artifacts 278 Decision-Making Traces 279 Operational Metadata 279 Behavioral Context279 Model Integrity Evidence 279 Forensic Data Management Practices 280 Structured Implementation Checklist 281 Chapter Summary 281 Chapter 25: AI Identities in Critical Infrastructure 283 The Core Risks 284 Healthcare: When Lives Are on the Line 284 Finance: Speed Meets Fragility 285 Utilities: Infrastructure in the Crosshairs 286 National Security: Escalation at Machine Speed 286 Where the First Governance Failures Will Happen 287 A Tiered Approach to Control—By Role, Not Industry 287 Where to Start: Visibility and Discovery 288 Chapter Summary 289 Table of ConTenTs

xviii Chapter 26: Building a Lifecycle for AI Identity Management 291 The Lifecycle Stages of an AI Identity 292 Provision: Starting with Purpose 292 Delegate: Clarity Before Autonomy 293 Observe: Visibility As a Control 293 Reevaluate: Scope Is Not Static 294 Expire: End of Life Is Not Optional 294 Cementing Lifecycle Thinking 295 Chapter Summary 295 Chapter 27: Operationalizing AI Identity Governance: A CISO’s Playbook 297 Why the CISO Must Own AI Identity Governance 298 First 90 Days: Stabilize and Baseline 298 Months 3–6: Build the Foundation 299 Months 6–9: Scale Controls and Enforce Accountability 300 Months 9–12: Measure, Report, and Evolve 301 Success Factors 302 Chapter Summary 302 Part VI: Looking Ahead 303 Chapter 28: Futureproofing and Strategic Roadmaps for AI Identity Governance 305 Prioritizing Emerging Technologies for Resilience 306 AI-Driven Identity Intelligence 306 Decentralized Identity Systems 307 Agentic Workflow Controls 307 Building the Right Skills for Adaptive Governance 308 Integrating Adaptive Risk Frameworks 309 Table of ConTenTs

xix Stress-Testing for the Unexpected 310 Documentation and Governance Infrastructure 311 A Phased Implementation Roadmap 311 Why This Approach Works 312 Chapter Summary 312 Chapter 29: The Future Role of the Identity Architect 313 From Gatekeeper to Governor 313 New Responsibilities of the Modern Identity Architect 314 Core Skills for the AI-Aware Identity Architect 315 Designing Identity for AI Agents 316 Partnering Across the Organization 317 The Identity Architect As Risk Owner 317 Chapter Summary 318 Chapter 30: Human-AI Collaboration and the Future of Work 319 Designing Human-AI Organizations Thoughtfully 320 Who Owns the AI That Knows You? 321 What the Ideal Relationship Looks Like 322 Where AI Creeps In—And Where Humans Must Stay 323 From Tools to Partners: The Philosophical Shift 324 Final Summary 324 Closing Thoughts 325 Appendix A: AI Identity Governance Maturity Model 327 Appendix B: RAISE Framework Implementation Checklist 333 Appendix C: Glossary of Key Terms: AI Identity Governance 337 Appendix D: AI Identity Governance—Board Briefing Template 343 Table of ConTenTs