AI Large Language Model (LLM) Security Series
Where Algorithms Become the New Attack Surface
By Eckhart Mehler for CISOsCISO — a perspective on cybersecurity leadership, governance and the decisions that determine whether organizations retain control.
Artificial Intelligence has crossed a threshold. What once lived in research labs is now woven into boardroom decisions, global operations, and everyday productivity tools. Yet, while organizations celebrate efficiency gains, few realize that their Information Security Management Systems (ISMS) are already being tested by invisible algorithms—systems that learn, decide, and sometimes deceive. Large Language Models (LLMs) don’t just automate tasks; they reshape the meaning of trust, integrity, and accountability across business processes. For CISOs, the message is clear: the ISMS must evolve from static compliance to dynamic intelligence governance.
This collection — “AI Large Language Model (LLM) Security” — explores how generative AI redefines security strategy, governance, and culture. It is structured into seven interconnected blocks, guiding security leaders from scope definition and risk management to governance alignment, operationalization of ISO/IEC 27001:2022 Annex A, and continuous improvement. Each article builds on real-world challenges faced by organizations integrating LLMs into core workflows — from shadow deployments to regulatory paradoxes under the EU AI Act, NIS2, and GDPR.
More than a taxonomy of threats, this series offers a strategic blueprint for CISOs and decision-makers who understand that AI is not merely another IT service — it’s a new attack surface, a new governance frontier, and, ultimately, a test of leadership maturity.
AI LMM Security - ISMS Scope & Strategic Risk
- Expanding the ISMS Scope: Why LLMs Are Now Business-Critical Assets
- From “Shadow AI” to Governance: Bringing LLM Use Cases Under Control
- Defining Criticality: When Does a Chatbot Become a Business-Critical Service?
- AI Risk ≠ IT Risk: Rethinking ISMS Boundaries in the Age of Generative AI
- The Blind Spot in Many ISMS: LLMs in Third-Party SaaS Environments
Governance & Compliance Alignment
- OWASP Top 10 for LLMs Meets the EU AI Act: Practical Governance Bridges
- NIS2, AI Act, GDPR: The Triad Every CISO Must Master for AI Governance
- The CLOUD Act vs. GDPR in AI Deployments: A Strategic Risk Balancing Act
- ISO/IEC 42001: Where AI Governance and ISMS Meet
- When Compliance Fails: Realistic Non-Compliance Scenarios with AI
Risk Management & Threat Modeling
- Prompt Injection as a Strategic Integrity Risk
- Model Theft and Intellectual Property: Protecting AI as a Business Asset
- Data Poisoning and the Long-Term Erosion of Trust
- From Threat Catalogues to LLM-Specific Playbooks
- CIA Triad Under AI Stress: Which Security Goals Are Most at Risk?
Operationalization of Annex A Controls
- Threat Intelligence for AI: Using OWASP Top 10 as a Source
- Secure Coding in the Age of AI: Adapting A.8.28 to LLM-Specific Threats
- Supplier Monitoring Beyond Contracts: AI APIs and Plugins Under A.5.20
- Monitoring AI Use: How A.8.16 Evolves with Generative AI
- Security Testing for AI: Operationalizing A.8.29 in Practice
Awareness, Culture & Leadership
- Awareness 2.0: Training Boards on AI-Specific Risks
- Why “Trust the AI” Is the Wrong Message: Culture of Healthy Skepticism
- AI Security as a Cultural Challenge, Not a Technical One
Auditability, Evidence & Continuous Improvement
- Documenting AI Risks in the Risk Register: From Prompt Injection to Model Theft
- Penetration Testing for AI: What Auditors Will Ask For
- Continuous Monitoring of AI: From One-Time Audit to Ongoing Assurance
- Closing the Loop: How AI Incidents Feed Back into the ISMS (Cl. 10.2)
Business Continuity & Global Strategy
- AI in Business Continuity: Planning for LLM Downtime and Abuse
- Incident Response for AI: Preparing for the Unthinkable
- Global Perspectives on AI Security: EU, US, and China Compared
Cyber AI Governance (NEW SERIES 2025)
- Why Every CISO Needs an AI Governance Standard Before Deploying a Single Model
- ISO 42001 Is Not a Checkbox: How to Build a Real AI Risk Program in a Global Enterprise
- Governance vs. Security: Why Cyber AI Fails Without a Board-Approved Risk Appetite
Publication Note & Disclaimer
This article was originally published on LinkedIn on November 1, 2025 and may have been edited or updated for publication on this site.
It reflects my personal professional perspective and does not represent the official policy or position of my employer. Drafting and editorial refinement may have been supported by commercially available AI-assisted tools. The analysis, conclusions and final curation are entirely my own.
For information regarding image credits, copyrights, trademarks and other intellectual property rights, please refer to the Imprint.
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