# Where Trust Boundaries Exist in AI Systems

> Map the critical trust boundaries in AI architectures. Learn where untrusted data crosses into trusted systems and how to secure these seams.

Canonical: https://codelivly.com/rooms/where-trust-boundaries-exist-in-ai-systems
Last updated: 2026-10-07

| | |
|---|---|
| Level | Beginner |
| Category | Cybersecurity |
| Lessons | 4 |
| Estimated time | 30 min |
| XP | 100 |

This module dives deep into the concept of trust boundaries within modern AI applications. You will learn to identify the exact points where untrusted data (user input, retrieved documents, LLM outputs) crosses into trusted execution environments. By mapping these seams, you will understand how vulnerabilities like Indirect Prompt Injection, Insecure Output Handling, and Data Poisoning occur, and how to implement strict validation and zero-trust principles at every handoff.

## Lessons

1. What is a Trust Boundary and Why It Matters (30 min)
2. User Input as an Untrusted Boundary (30 min)
3. Retrieved Content (RAG, Web, Documents) as an Untrusted Boundary (30 min)
4. Tool/Function Outputs as an Untrusted Boundary (30 min)

## Related

- [Learning path: AI Application Architecture and Attack Surface](https://codelivly.com/learning-paths/ai-application-architecture-and-attack-surface)
- [All rooms](https://codelivly.com/rooms)