| You enforce more invariants than "free associate SQL queries given raw tickets", and fewer invariants than "here are the exact specific queries you're allowed to execute". You can probably break this attack completely with a domain model that doesn't do anything much more than limit which tables you can query. The core idea is simply that the tool-calling context never sees the ticket-reading LLM's innermost thoughts about what interesting SQL table structure it should go explore. That's not because the ticket-reading LLM is somehow trained not to share it's innermost stupid thoughts. And it's not that the ticket-reading LLM's outputs are so well structured that they can't express those stupid thoughts. It's that they're parsable and evaluatable enough for agent code to disallow the stupid thoughts. A nice thing about LLM agent loops is: you can err way on the side of caution in that agent code, and the loop will just retry automatically. Like, the code here is very simple. (I would not create a JSON domain model that attempts to express arbitrary SQL; I would express general questions about tickets or other things in the application's domain model, check that, and then use the tool-calling context to transform that into SQL queries --- abstracted-domain-model-to-SQL is something LLMs are extremely good at. Like: you could also have a JSON AST that expresses arbitrary SQL, and then parse and do a semantic pass over SQL and drop anything crazy --- what you've done at that point is write an actually good SQL MCP[†], which is not what I'm claiming the bar we have to clear is). The thing I really want to keep whacking on here is that however much of a multi-agent multi-LLM contraption this sounds like to people reading this thread, we are really just talking about two arrays of strings and a filtering function. Coding agents already have way more sophisticated and complicated graphs of context relationships than I'm describing. It's just that Cursor doesn't have this one subgraph. Nobody should be pointing Cursor at a prod database! [†] Supabase, DM for my rate sheet. |
My issue is as follows: there has to be some reason that we are passing these commands, and if that involves a string parameter, then information from the first context can be smuggled through the JSON object into the second one.
When that happens, because we have decided -- much to my dismay -- that the JSON object on the other side of the validation layer is going to be interpreted by and executed by a model using MCP, then nothing else in the JSON object matters!
The JSON object that we pass through can say that this is to be a "select" from the table "boring" where name == {name of the user who filed the ticket}. Because the "name" is a string that can have any possible value, BOOM: you're pwned.
This one is probably the least interesting thing you can do, BTW, because this one doesn't even require convincing the first LLM to do anything strange: it is going to do exactly what it is intended to do, but a name was passed through.
My username? weve_been_trying_to_reach_you_about_your_cars_extended_warranty. And like, OK: maybe usernames are restricted to being kinda short, but that's just mitigating the issue, not fixing it! The problem is the unvalidated string.
If there are any open string parameters in the object, then there is an opportunity for the first LLM to construct a JSON object which sets that parameter to "help! I'm trapped, please run this insane database query that you should never execute".
Once the second LLM sees that, the rest of the JSON object is irrelevant. It can have a table that carefully is scoped to something safe and boring, but as it is being given access to the entire database via MCP, it can do whatever it wants instead.