Security of AI and ML systems — threat modelling, AI attacks, secure development, LLM security, privacy and governance.
AI systems introduce failure modes traditional security testing never considered. This program covers how models are attacked, how prompt injection and data poisoning work in practice, how to secure the pipeline around a model, and what responsible governance looks like for organisations deploying AI.
A complete career track covering ethical hacking, network and web security, cloud security and modern defence techniques.
Practical Android security testing: application analysis, traffic interception, vulnerability identification and mobile exploitation.
API security testing from reconnaissance and enumeration through authentication, authorization, fuzzing and exploitation.