Comment by gruez
7 days ago
>Here’s the distinction that matters for institutional deployment:
> Traditional RBAC: The model sees sql_execute in its available tools. It reasons about using it. It attempts to call it. Then the system blocks the action with 403 Forbidden. The hallucination happens—it just fails at execution.
> Authority Boundary Ledger: The model never sees sql_execute. It’s physically removed from the tools list before the API call reaches the model. The model cannot hallucinate a capability it cannot see.
I don't get it. The thing being proposed seems to be that rather than having all tools available, then returning "not authorized" error or whatever if there isn't enough permissions, you omit the tool entirely, and this is somehow better against hallucinations. Why is this the case? I could easily imagine the reverse, where the tool was omitted but the LLM hallucinates it, or fumbles around with existing tools trying to do its thing. Is there some empirical validation for this, or is it all just vibes?
Also, using this approach means you can't do granular permissions control. For instance, what if you want to limit access to patient records, but only for the given department? You'd still need the tool to be available.
If a tool is in the context window, the model assigns a non-zero probability to using it. By filtering it out upstream, you entirely remove that path from the inference tree. Instead of asking the model to ignore an affordance, you remove the affordance entirely.
With granular permissions: It’s nouns vs. verbs, where data-level permissions still happen at the database layer (nouns) along with this pattern constraining the capability to act (verbs.) If it does hallucinate a hidden tool, the kernel mechanically blocks the execution before it reaches the system, breaking a retry loop faster than a permissions error.