CompTIA SecAI+ Study Guide: Securing AI Systems & AI-Powered Cybersecurity

CompTIA SecAI+ Study Guide: Securing AI Systems & AI-Powered Cybersecurity book cover

CompTIA SecAI+ Study Guide: Securing AI Systems & AI-Powered Cybersecurity

Author(s): Fransesco Malila (Author)

  • Publisher: Independently published
  • Publication Date: April 8, 2026
  • Language: English
  • Print length: 146 pages
  • ISBN-10: B0GWLTRH7H
  • ISBN-13: 9798255593170

Book Description

AI is transforming cybersecurity — and cybersecurity must transform to secure AI. The CompTIA SecAI+ certification validates the skills professionals need at this critical intersection, and this study guide is your comprehensive companion for mastering every exam objective.

Written by cybersecurity and AI practitioner Fransesco Malila, this book covers both sides of the AI-security equation: protecting AI systems from adversarial attacks, data poisoning, model theft, and prompt injection — and harnessing AI to power threat detection, vulnerability management, incident response, and identity security.

WHAT’S INSIDE:

Part I — Foundations: AI/ML fundamentals for security professionals, neural network architectures, LLM concepts, the CIA triad applied to AI, and the expanded attack surface of machine learning systems.

Part II — Securing AI Systems: The complete AI threat landscape including adversarial attacks, data poisoning, and supply chain risks. Securing the ML pipeline from data collection through deployment. Privacy-preserving techniques, federated learning, model versioning, and AI data governance under GDPR and the EU AI Act.

Part III — AI-Powered Cybersecurity: AI-driven anomaly detection, SIEM and SOAR enhancement, vulnerability discovery and prioritization, adaptive authentication, behavioral biometrics, insider threat detection, AI-augmented penetration testing, deepfake threats, and AI-generated malware countermeasures.

Part IV — Governance, Ethics, and Risk Management: Deep dives into the NIST AI RMF, MITRE ATLAS, OWASP ML Top 10, and ISO 42001. AI explainability, accountability, human-in-the-loop controls, the EU AI Act, U.S. regulatory landscape, and building an organizational AI security program.

Part V — Exam Preparation: 30 practice questions with detailed explanations covering all four exam domains, including complex scenario-based questions. Six hands-on lab exercises using open-source tools — adversarial attack simulation, data poisoning detection, prompt injection testing, AI-driven log analysis, model security assessment, and an incident response tabletop exercise.

APPENDICES: Complete exam objective mapping for all 64 objectives, a 90-term glossary, curated tools and resources reference, and a comprehensive acronym list.

EVERY CHAPTER INCLUDES: Exam objective callouts, exam tips, real-world scenarios, security implication notes, and ten review questions.

Whether you are a cybersecurity professional expanding into AI security, an ML engineer who needs to understand the security implications of your work, or an IT professional preparing for the SecAI+ exam, this book gives you both the knowledge to pass and the practical understanding to secure AI systems in production.

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