AI Application Attack Surface
Map models, applications, data, tools and trust boundaries.
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AI SECURITY / COURSE
An introduction to security risks created by modern AI applications and tool-using systems.
WHAT YOU WILL LEAVE WITH
A clear model of AI application trust boundaries
Understanding of prompt-injection risk
Awareness of tool-use authorization problems
01 / OVERVIEW
Build a practical security mindset for AI-enabled applications by reasoning about trust boundaries, data, permissions, tools, and application behavior.
LEARNING OBJECTIVES
Understand the security model of modern AI applications
Recognize prompt-injection risk
Understand tool-calling and permission boundaries
Connect traditional application security to AI-enabled systems
02 / CURRICULUM
Each module develops one layer of the security model before moving to the next.
Map models, applications, data, tools and trust boundaries.
Understand direct and indirect instruction-manipulation risks.
Examine authorization and control boundaries around agentic actions.
03 / REQUIREMENTS
The course is designed to make AI application security approachable from a practical cybersecurity perspective.
BEFORE YOU START
Basic application-security awareness
No advanced machine-learning background required
04 / OUTCOMES
The outcome is not memorising prompt tricks. It is learning how to reason about real AI-enabled application risk.
A clear model of AI application trust boundaries
Understanding of prompt-injection risk
Awareness of tool-use authorization problems
Ability to connect AI security to conventional application security
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