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AI Security

Technology Fundamentals

AI Security

1 min readPublished 22 Jul 2026

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Building with AI introduces new security risks. This reuses the core from Cyber Security Fundamentals: AI Security, applied to building AI systems.

Interactive explainer

AI Security

Securing AI — and defending against AI-powered attacks.

1New AI threats2AI in attacks3AI in defence4AI governance

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New AI threats

OWASP LLM Top 10.

AI systems face new risks: prompt injection (manipulating inputs), data poisoning (corrupting training data), model theft and sensitive-data leakage. OWASP's LLM Top 10 is the reference.

Check your understanding

1. What is prompt injection?

2. What reference lists AI/LLM risks?

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AI SecurityGovernance & Compliance CompTIA SecurityX / CASP+
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Key risks when building AI

  • Prompt injection — malicious input that hijacks an AI's instructions (especially dangerous for agents with tool access).
  • Data leakage — sensitive data pasted into prompts or returned in outputs.
  • Data poisoning & model theft — corrupting training data or stealing the model.
  • The OWASP Top 10 for LLMs — the reference for securing LLM applications.

Controls

Validate and constrain inputs and outputs, apply least privilege to any tools an agent can call, never trust model output blindly, and keep sensitive data out of untrusted models. Security must be designed into AI systems from the start — the same secure-by-design principle.

Interview Intelligence

How this topic actually shows up in interviews — and how to demonstrate you understand it.

Why employers ask about this

As organisations build AI, securing it is a fast-emerging, high-value specialism.

Technical questions
What are the main risks when building an AI application?+

Prompt injection, data leakage, data poisoning and model theft — mitigated per the OWASP LLM Top 10.

Behavioural questions
Describe considering security in something you built.+

Show designing in controls rather than adding them later.

Real-world scenarios
“Your AI agent can access internal APIs.”+

Expected answer: Apply least privilege, validate inputs (prompt-injection defence) and add human approval for risky actions.

Practise in AI Interview™Rehearse these questions, scored.Plan with Career Coach™A personalised path to your goal.Evidence it in Career Passport™Prove this skill to employers.

Employability Intelligence

Where this knowledge takes you — the jobs, skills and certifications it feeds into.

Relevant roles
AI Security EngineerSecurity EngineerAI Engineer
Skills you're proving
AI securityPrompt injectionOWASP LLM Top 10
Recommended certifications
CompTIA Security+Microsoft AI-900
Career progression

AI & Automation + Cyber Fundamentals → AI Security roles.

What employers expect

That you can use AI tools effectively, understand their limits, and automate work responsibly.

Frequently asked questions

What is prompt injection?

Malicious input crafted to override an AI's instructions or make it perform unintended actions — a top risk for agents.

What is the OWASP LLM Top 10?

A reference list of the most critical security risks for LLM applications, used to secure AI systems.

How do you secure an AI application?

Validate inputs/outputs, apply least privilege to tools, never trust output blindly, and protect sensitive data.

Related guides

AI & Automation Fundamentals: LLMs, Prompting, RAG, Agents & AutomationAI Fundamentals: ML, Deep Learning & Generative AILarge Language Models (LLMs)Prompt Engineering

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