Training Catalogue / Security and Threat Modelling
Architecting Secure LLM Applications
Delivered by a CEH-certified instructor
Modules
Take single modules or the whole track. Two hour sessions, combined into half days where it suits your calendar.
Secure-by-Design for AI Features
Build security into AI features from the start, not bolted on afterwards.
- The LLM security landscape and OWASP LLM Top 10
- Trust boundaries, zero trust and least privilege for AI
- The unique attack vectors LLM integration introduces
- Where AI Threat Modelling finds risks, this fixes them
Defending the AI Data and Tool Flow
Prompt-injection defence, safe data handling and secure tool calling.
- Prompt-injection defence and input sanitisation
- Secure data handling and training-data leakage prevention
- Output handling, validation and sandboxing
- RAG and tool-calling security
Hardening AI for Production
Rate limiting, monitoring and the supply-chain concerns of shipping AI.
- Supply-chain and deployment security
- API gateways, rate limiting and circuit breakers
- Logging, monitoring and detection
- Security testing, red teaming and production hardening
Teams Often Pair This With
Related modules other teams add alongside this track.
Securing RAG and Agentic AI
Retrieval poisoning, autonomous-action risk and multi-agent coordination threats.
View module Applied AI Engineering · Building GenAI ApplicationsShipping AI Features to Production
Scaling, caching, monitoring and the operational realities of running AI features.
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