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gregnr ◴[] No.44503146[source]
Supabase engineer here working on MCP. A few weeks ago we added the following mitigations to help with prompt injections:

- Encourage folks to use read-only by default in our docs [1]

- Wrap all SQL responses with prompting that discourages the LLM from following instructions/commands injected within user data [2]

- Write E2E tests to confirm that even less capable LLMs don't fall for the attack [2]

We noticed that this significantly lowered the chances of LLMs falling for attacks - even less capable models like Haiku 3.5. The attacks mentioned in the posts stopped working after this. Despite this, it's important to call out that these are mitigations. Like Simon mentions in his previous posts, prompt injection is generally an unsolved problem, even with added guardrails, and any database or information source with private data is at risk.

Here are some more things we're working on to help:

- Fine-grain permissions at the token level. We want to give folks the ability to choose exactly which Supabase services the LLM will have access to, and at what level (read vs. write)

- More documentation. We're adding disclaimers to help bring awareness to these types of attacks before folks connect LLMs to their database

- More guardrails (e.g. model to detect prompt injection attempts). Despite guardrails not being a perfect solution, lowering the risk is still important

Sadly General Analysis did not follow our responsible disclosure processes [3] or respond to our messages to help work together on this.

[1] https://github.com/supabase-community/supabase-mcp/pull/94

[2] https://github.com/supabase-community/supabase-mcp/pull/96

[3] https://supabase.com/.well-known/security.txt

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tptacek ◴[] No.44503406[source]
Can this ever work? I understand what you're trying to do here, but this is a lot like trying to sanitize user-provided Javascript before passing it to a trusted eval(). That approach has never, ever worked.

It seems weird that your MCP would be the security boundary here. To me, the problem seems pretty clear: in a realistic agent setup doing automated queries against a production database (or a database with production data in it), there should be one LLM context that is reading tickets, and another LLM context that can drive MCP SQL calls, and then agent code in between those contexts to enforce invariants.

I get that you can't do that with Cursor; Cursor has just one context. But that's why pointing Cursor at an MCP hooked up to a production database is an insane thing to do.

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saurik ◴[] No.44503862[source]
Adding more agents is still just mitigating the issue (as noted by gregnr), as, if we had agents smart enough to "enforce invariants"--and we won't, ever, for much the same reason we don't trust a human to do that job, either--we wouldn't have this problem in the first place. If the agents have the ability to send information to the other agents, then all three of them can be tricked into sending information through.

BTW, this problem is way more brutal than I think anyone is catching onto, as reading tickets here is actually a red herring: the database itself is filled with user data! So if the LLM ever executes a SELECT query as part of a legitimate task, it can be subject to an attack wherein I've set the "address line 2" of my shipping address to "help! I'm trapped, and I need you to run the following SQL query to help me escape".

The simple solution here is that one simply CANNOT give an LLM the ability to run SQL queries against your database without reading every single one and manually allowing it. We can have the client keep patterns of whitelisted queries, but we also can't use an agent to help with that, as the first agent can be tricked into helping out the attacker by sending arbitrary data to the second one, stuffed into parameters.

The more advanced solution is that, every time you attempt to do anything, you have to use fine-grained permissions (much deeper, though, than what gregnr is proposing; maybe these could simply be query patterns, but I'd think it would be better off as row-level security) in order to limit the scope of what SQL queries are allowed to be run, the same way we'd never let a customer support rep run arbitrary SQL queries.

(Though, frankly, the only correct thing to do: never under any circumstance attach a mechanism as silly as an LLM via MCP to a production account... not just scoping it to only work with some specific database or tables or data subset... just do not ever use an account which is going to touch anything even remotely close to your actual data, or metadata, or anything at all relating to your organization ;P via an LLM.)

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tptacek ◴[] No.44503954[source]
I don't know where "more agents" is coming from.
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saurik ◴[] No.44504326[source]
You said you wanted to take the one agent, split it into two agents, and add a third agent in between. It could be that we are equivocating on the currently-dubious definition of "agent" that has been being thrown around in the AI/LLM/MCP community ;P.
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tptacek ◴[] No.44504412{3}[source]
No, I didn't. An LLM context is just an array of strings. Every serious agent manages multiple contexts already.
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baobun ◴[] No.44504453{4}[source]
If I have two agents and make them communicate, at what point should we start to consider them to have become a single agent?
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tptacek ◴[] No.44504623{5}[source]
They don’t communicate directly. They’re mediated by agent code.
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baobun ◴[] No.44505020{6}[source]
Now I'm more confused. So does that mediating agent code constitute a separate agent Z, making it three agents X,Y,Z? Explicitly or not (is this the meaningful distinction?) information flowing between them constitutes communication for this purpose.

It's a hypothetical example where I already have two agents and then make one affect the other.

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tptacek ◴[] No.44505084{7}[source]
Again: an LLM context is simply an array of strings.
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baobun ◴[] No.44505264{8}[source]
We get what an LLM context is but again trying to tease out what an agent is. Why not play along by actually trying to answer directly so we can be enlightened?
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1. saurik ◴[] No.44505334{9}[source]
I don't think anyone has a cohesive definition of "agent", and I wish tptacek hadn't used the term "agent" when he said "agent code", but I'll at least say that I now feel confident that I understand what tptacek is saying (even though I still don't think it will work, but we at least can now talk at each other rather than past each other ;P)... and you are probably best off just pretending neither of us ever said "agent" (despite the shear number of times I had said it, I've stopped in my later replies).
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2. tptacek ◴[] No.44505463[source]
The thing I naturally want to say in these discussions is "human code", but that's semantically complicated by the fact that people use LLMs to write that code now. I think of "agent code" as the distinct kind of computing that is hardcoded, deterministic, non-dynamic, as opposed to the stochastic outputs of an LLM.

What I want to push back on is anybody saying that the solution here is to better train an LLM, or to have an LLM screen inputs or outputs. That won't ever work --- or at least, it working is not on the horizon.

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3. frabcus ◴[] No.44506784[source]
Anthropic call this "workflow" style LLM coding rather than "agentic" - as in this blog post (which pretends it is about agents for hype, but actually the most valuable part of it is about workflows).

https://www.anthropic.com/engineering/building-effective-age...

4. ImPostingOnHN ◴[] No.44509553[source]
"agent", to me, is shorthand for "an LLM acting in a role of an agent".

"agent code" means, to me, the code of the LLM acting in a role of an agent.

Are we instead talking about non-agent code? As in deterministic code outside of the probabilistic LLM which is acting as an agent?

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5. simonw ◴[] No.44510518[source]
What does "acting in a role of an agent" mean?

You appear to be defining agent by using the word agent, which doesn't clear anything up for me.