AI for Cybersecurity Professionals: Intensive 5-Day Course
About
As AI capabilities become increasingly integrated into government and enterprise systems, they bring new security challenges that differ from those found in traditional software. AI applications — especially those built on Large Language Models (LLMs) — are dynamic, data-driven, and operate at scale, creating unique risks such as prompt injection, model extraction, data poisoning, and adversarial manipulation.
Cybersecurity professionals must therefore be equipped to evaluate AI-driven systems, understand how they function, and implement the controls needed to secure them across their lifecycle.
This 5-day pilot course provides cybersecurity leadership and governance teams with the essential understanding of AI system components, threat models, and security approaches required to safely adopt and oversee AI technologies in their organizations.
Participants will learn how AI systems are designed and deployed, how adversaries may target them, and how organizations can apply security controls, evaluation techniques, and governance frameworks to manage AI risks. The course includes a blend of lectures, demonstrations, hands-on activities, and structured case studies.
Topics
- Using AI tools responsibly in daily cybersecurity work
- Understanding LLM architectures, memory systems, tools, and agent frameworks
- Identifying AI-specific attack vectors and integrating them into threat models
- Applying security controls across the AI lifecycle
- Conducting AI risk assessments and responding to security incidents
- Implementing AI governance practices (e.g., AI RMF, AIBOM, model registries)
Syllabus Summary
Days 1-2: AI in Daily Work & Anatomy of AI Systems
Duration: 2 days
Participants are introduced to predictive, generative, and agentic AI, and how these systems support cybersecurity tasks such as analysis, research, documentation, and decision-making.
Hands-on exercises cover prompt engineering, context use, and safe application of chat-based tools.
The course then examines the main components of AI systems — LLMs, retrieval systems (RAG), memory, tools, and agent orchestration — and how these components expand the security surface.
Days 3-4: Cybersecurity Risks & AI Threat Landscape
Duration: 2 days
This module covers the adversarial risks facing AI systems, using frameworks such as ENISA's AI security model and MITRE ATLAS.
Participants investigate practical attack vectors including data poisoning, prompt injection, jailbreaks, supply-chain compromise, and misuse of tools or system prompts.
The defensive segment introduces security controls across data, inference, access control, MLOps, supply chain, monitoring, and privacy-enhancing technologies.
GovTech's AI Guardian platform is presented as a case study for operational AI security.
Day 5: AI Incident Response & Governance
Duration: 1 day
Participants learn how to detect, investigate, and remediate AI-related incidents, including contaminated data, compromised prompts, or manipulated outputs.
The governance module introduces organization-wide AI risk management using the NIST AI RMF, including documentation practices (AIBOM), model registries, and oversight of employee use of external AI tools.
Course Pricing & Payment Terms
- Course must be purchased as a group class with a minimum of 10 pax.
- The course will commence with a minimum subscription of 20 pax and is limited to 30 pax per cohort.
- Corporate rates are available. Government subsidies/grants do not apply to this course.
- For organisations sending more than 10 participants, please email [email protected] for a customised quotation.
Payment Terms
- Payment must be made before the start of the course.
- Refund policy:
- More than 30 days before the start date: 100% refund
- Between 5-30 days before the start date: 50% refund
- Less than 5 days before the start date: No refund
To sign up or learn more about course dates, please contact us at [email protected]