Latest / Big Iron Radio / Homelab Brief - Prompt-Injection Defenses: Input and Output Guards
Transcript
- 0:02Welcome to the Homelab Brief from Big Iron.
- 0:06Today, defending self-hosted LLM apps against prompt injection
- 0:11and being realistic about what defending even means.
- 0:15Quick note, this is an AI voice drawn from a Big Iron guide.
- 0:20Links below.
- 0:21Start with the hard truth.
- 0:23You cannot fully prevent prompt injection.
- 0:26The model has no hard boundary between instructions and data to an LLM.
- 0:31Text is text.
- 0:31So the realistic goal isn't prevention.
- 0:35It's blast radius containment.
- 0:38Making it so that when injection happens, it doesn't matter much.
- 0:42Which means the strongest defense is architectural, not a clever filter.
- 0:47Least privilege tools.
- 0:49Authorization enforced in your code, never in the prompt.
- 0:53Minimal context.
- 0:55Sandboxed execution.
- 0:57And a human in the loop for anything genuinely dangerous.
- 1:00Structure beats string matching every time.
- 1:03The design principle to internalize.
- 1:06Assume the model is compromised and build so it doesn't matter.
- 1:11A model with no dangerous tools and real per-tool authorization can be completely jailbroken and still cause no harm.
- 1:18That's the bar not unbreakable prompt, but harmless when broken.
- 1:23Two rules that follow directly.
- 1:26Never put secrets in the system prompt it can leak, and it is not a security boundary.
- 1:31And treat every tool call argument the model produces as untrusted input.
- 1:35Validate the ID, check the authorization fields in code, before you act on them.
- 1:42Input and output guards scanning for injection attempts on the way in and leaks on the way out are worth adding, but as a second layer.
- 1:50They catch the lazy attacks.
- 1:52The architecture is what saves you from the clever ones.
- 1:55The full defense stacks in the show notes.
- 1:59That's your brief.