SOURCE-LINKED INTELLIGENCE
Semantic Overlays: Mitigating Prompt Injection with Annotations Beyond Tokens and Steering Vectors
Everything a language model sees is tokens. The serving stack knows what each span is -- user input, tool output, instructions -- but the model must keep track of that itself, and can lose track or be confused: text can be written to read like anything. Prompt injection is a natural exploit of this phenomenon. By scrambling the model's understanding of span identity, an attacker can induce unwanted and dangerous actions. Adding a non-textual channel to the model's input -- a way to communicate span identity beyond text -- mitigates this class of attack. We thus introduce a general steering tec
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-24T22:26:58.000Z
First collected: 2026-09-21T10:22:00.206Z. This is not the publication date.