Prompt Injection Defenses as Boundary Enforcement
Explore methods to defend AI systems from prompt injection attacks by enforcing clear trust boundaries, separating instruction from untrusted content, and validating tool actions. Understand how to implement input and output contracts, context assembly controls, and tool execution checks to maintain governance and security in AI applications.
The threat model skeleton named the boundary crossings that need a control. The instruction boundary is the first, and the most argued about: untrusted text trying to pass as a command. Prompt injection is an integrity failure at that boundary. The system accepts text that should stay untrusted data, and lets it influence a decision that must stay governed by a higher-authority rule. Treat the mitigation goal as boundary enforcement with an explicit check, not as making ...