Enterprise AI Safety & Governance

Establish defense-in-depth safety controls: prompt injection guardrails, automated red-teaming, safety alignment constrained MDPs, delegated credentials, and audit retention policies.

Topological Progression0 of 18 Concepts Verified (0%)

Step Navigator

Step 1 of 18

security-safety-governance

lesson

Full Concept Guide

Security and Privacy for LLM Systems

How untrusted inputs sensitive data tools and external knowledge expand the threat model.

Architectural Intuition

An LLM is an untrusted probabilistic component processing both instructions and data. Security comes from system boundaries, least privilege, validation, and data governance, not from asking the model to behave. <ConceptDiagram sourceIds="owasp-llm|openai-data-controls" steps="Threat model|Trust boundaries|Minimize and isolate|Validate and authorize|Monitor and respond" />

Local Subgraph Topology

0 Prerequisites • 4 Unlocks

Foundational Prerequisites (0)

First-principles foundation node.

Unlocks Next (4)

Tool Sandboxing and Egress Control

Unlocks

Access-Aware Retrieval

Unlocks

AI Data Classification and Minimization

Unlocks

Tool Authorization

Unlocks

Micro-Assessment Verification

Answer correctly to advance

Which statement best captures the operating model for Security and Privacy for LLM Systems?