Secure AI Application Engineering

About this paper

An advanced examination for engineers and architects who build applications around large language models. It assesses threat modelling of LLM systems, trust boundary design, sandboxing and egress control, agent tool architecture, model supply chain integrity, and safe release engineering. Candidates should have hands-on experience shipping at least one production LLM feature.

What it covers

• Threat modelling LLM applications: trust boundaries, untrusted model output, and injection paths
• Agent and tool security: least privilege per tool, capability tokens, and schema validation
• Runtime containment: code interpreter sandboxing, egress control, and SSRF defence
• Economic and availability attacks: denial of wallet, rate limiting, and quota design
• Model supply chain: unsafe deserialisation, registry integrity, signing, and plugin risk
• Release engineering: caching hazards, secret handling, evaluation gates, and safe rollback

How it is marked

• Questions and answer options are shuffled for every sitting.
• Multi-answer questions are marked as a set: you need all of the correct options and none of the wrong ones. There is no partial credit.
• You need 75% to pass.
• You can revisit and change any answer until you submit.
• Afterwards you see every question, the answer you gave, whether it was right, and the reasoning behind it. The answer key itself is never printed, so the paper stays worth sitting.
• You can re-sit the paper, but not immediately: there is a short wait between attempts.