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Build your understanding from AI fundamentals to production AI systems.
Prefer a guided sequence? Explore Learning PathsAI Security & Governance
Build AI systems that protect data, models, users, and enterprise workflows.
10 conceptsGenAI Security Fundamentals
GenAI introduces new risks beyond traditional application security, because a model treats everything in its context as text it might act on.
Intermediate · 4 minJailbreaks & Adversarial Inputs
A jailbreak is an input crafted specifically to bypass a model’s safety training or stated instructions.
Advanced · 5 minRAG Security
RAG security means treating retrieved documents as untrusted data and filtering retrieval by the requesting user’s actual permissions.
Advanced · 5 minAgent Security
Agent security means scoping tool access tightly and requiring approval for irreversible actions, since an agent turns a decision into a real effect.
Advanced · 5 minData Leakage & PII Protection
Preventing data leakage means detecting and redacting personal information before it reaches a prompt, a log, or a model’s output.
Advanced · 4 minAI Access Control & Identity
AI services need their own identity and access controls — which service can call which model, and with which permissions.
Advanced · 4 minAI Supply Chain Security
AI supply chain security means verifying the provenance of third-party models, datasets, and framework dependencies before trusting them.
Advanced · 4 minAI Red Teaming
Red teaming an AI system means deliberately attacking it with adversarial inputs before real attackers do.
Advanced · 4 minAI Governance & Compliance
AI governance sets organizational policy for what models and data can be used, by whom, and under what oversight.
Intermediate · 4 minResponsible AI
Responsible AI considers fairness, transparency, and the real-world impact of a system’s outputs, not just whether it works technically.
Intermediate · 4 min