Researcher demonstrates runtime security layer that treats AI agents as untrusted actors to prevent prompt injection attacks during tool execution.

Prompt injection becomes a runtime problem once LLM agents gain access to tools, APIs, and databases—not just a static prompt issue

New approach applies zero-trust security model to AI agents by validating tool usage and enforcing execution-time policies

System intercepts malicious requests, applies allow/block/constrain policies, and logs full decision traces for transparency

Runtime controls complement but don't rely solely on prompt engineering and model guardrails as primary defense mechanisms