LLM Security Fundamentals
LLM security isn't about finding a bug in a black box — it's about understanding the system well enough to see where trust breaks. This course traces a prompt through the eight steps every LLM takes to turn text into an answer, then maps real attacks — the full OWASP LLM Top 10 — to the exact step each one targets. You'll leave able to audit an AI system, name its risks in shared vocabulary (OWASP + MITRE ATLAS), and connect the controls to what the EU AI Act and ISO 42001 now require.
Curriculum
Five modules, about 2 hr 15 min — understand the system, walk the pipeline, name the risks, know the rules, keep what matters.
Introduction
What an LLM really is (prediction, not logic), why the model isn't the app, and the trust-boundary problem that makes everything after it click. Six lessons.
The 8-Step Pipeline
Follow a prompt from Enter to answer, one step at a time — tokenization, embeddings, context assembly, attention, decoding — and see the exact mechanics an attack exploits. Eleven lessons.
OWASP LLM Top 10
All ten named risks — from prompt injection to unbounded consumption — each tied back to the pipeline step it hits, with the guardrails that contain it. Ten lessons.
Frameworks & Governance
MITRE ATLAS, the EU AI Act, and ISO 42001 — what regulators are already asking for, and how every control you've learned maps to a specific obligation. Four lessons.
Wrap-Up: What to Remember
The attack-surface map, five principles, and a five-question audit checklist for the next time you're handed an AI system. Three lessons.
Earn a certificate
Finish the course and earn a verifiable certificate — issued by AI Security University with its own public verification page, and shareable straight to your LinkedIn profile.
- Public verification page
- Counts toward CPE credit
- Open Badge compatible
- Add to LinkedIn
Your instructor
Know where to look when you're handed an AI system.
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