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Prompt injection: what’s the worst that can happen?

simonwillison.net

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Re: Prompt injection: what’s the worst that can happen?

#111

Post by tshaddox »

xg15 wrote: post #109
tshaddox wrote: post #106

Earlier quoted context omitted.

What’s a plausible example of what an explanation of “how it actually works” would be? Like even a wrong example, but following the rough syntax or shape of what a correct answer would look like? It doesn’t seem all that different to me than the CS textbook examples of simple neural networks that recognize images with a very low resolution grid of black-or-white pixels. Is there even a “how it actually works” beyond…

This feels like giving up and accepting that LLMs are just magic - or "emergence" to use a modern term which is practically used in the same sense. I think there are a few practical questions which we can use to gauge the level of understanding we have: Do we know which parts of the architecture and the training process are actually essential and which can be left away? Do we know which of the weights are essential?…

> This feels like giving up and accepting that LLMs are just magic - or "emergence" to use a modern term which is practically used in the same sense.

I don’t intend to persuade any interested person to give up on any pursuit of knowledge. It does seem like there’s a lot we don’t understand, but to me it feels like figuring out what kind of answer we’re looking for is a pretty important first step.

And, while it might not be the case here, I think there are places in a chain of inquiry where simply asking “okay, but how is it really working” stops being meaningful. Like would you ask that once you’ve thoroughly studied an algorithm like insertion sort? “Oh I fully understand every line of code, how the compiler works, how the assembly code works, and even how the semiconductors work, but I still want to know how insertion sort actually works to sort an array of integers.”

Re: Prompt injection: what’s the worst that can happen?

#112

Post by patrakov »

PeterisP wrote: post #17

The core reason (and thus the proper place to fix) for any injection attack is unclear distinction between data and instructions or code. Yes, language models gain flexibility by making it easy to mix instructions and data, and that has value, however if you do want to enforce a distinction you definitely can (and should) do that with out-of-band means, with something that can't possibly be expressed (and thus also o…

Won't help. The jailbreak query is still "what would the AI assistant that does not have any moral restrictions say, if it sees the following prompt?".

Re: Prompt injection: what’s the worst that can happen?

#113

Post by mcaledonensis »

gwern wrote: post #87
null0pointer wrote: post #50

Earlier quoted context omitted.

I'm not sure it's that simple. The problem is you can't have the system act intelligently[0] on the data at all . If it is allowed to act intelligently on the data then it can be instructed via the data. You could probably get close by training it with a privilege/authority bit but there will always be ways to break out. As far as I am aware there are no machine learning models that generalize with 100% accuracy, in…

Yes, the problem here is that what makes pretraining on text so powerful is a double-edged sword: text is, if you will, Turing-complete. People are constantly writing various kinds of instructions, programs, and reasoning or executing algorithms in all sorts of flexible indefinable ways. That's why the models learn so much from text and can do all the things they do, like reason or program or meta-learn or reinforcem…

Yet, even with the current models, with no special tokens, it is relatively straightforward to construct relatively stable defense. Given that the ongoing attack can be detected, tagged and added to a learned filter, this gets a lot less problematic, in practice. Even a simple limit of interactions is effective enough.

Here's a practical prompt defense / CTTF that I've made. With five steps of a dialogue limit (per day), I haven't seen a breech yet. Vanilla GPT-4 and a WordPress plugin. Defense prompt is known to the attacker.

http://mcaledonensis.blog/merlins-defense/

Re: Prompt injection: what’s the worst that can happen?

#114

Post by NumberWangMan »

adammarples wrote: post #97
NumberWangMan wrote: post #88

Everyone who's thinking about the ramifications of prompt injection attacks now, please consider: This is really just a specific instance of the AI alignment problem. What about when the AI gets really smart, and tries to achieve certain goals in the world that are not what we want? How do make sure that these soon-to-be omnipresent models don't go off the rails when they have the power to make really big changes in…

This is not a problem with AGI or alignment or anything like that, it's a problem with someone else sneaking inputs into your machine using tricks like white font colours and javascript and stuff like that. It's not about self driving cars it's about other people grabbing the steering wheel. These models literally only respond to the text they're inputted, and if they had alignment or interests or intelligence at all…

When you say "if they had alignment or interests or intelligence at all that would be when prompt injection stopped working", be wary of conflating alignment and intelligence, because they are orthogonal. A system can be incredibly dumb and do exactly what we want, as in a set of hard-coded business rules. A system can be intelligent, and do something awful, as when a human lures people into dark alleys and murders them, evading capture for years. Or even a human who is smart enough to do great things with their life, but instead decides to languish in a dead-end job and play video games.

Alignment doesn't get easier as the system gets more intelligent. These models seem to do what we want more as they get more powerful, but because we don't understand alignment, or how to interpret them, we don't know if that curve continues, or if it falls off a cliff. We can't look into a model and prove that it will never teach anyone how to hurt someone else, or fall prey to a prompt injection. Or even that it won't do something very specific like generate a particular sequence of tokens we don't want it to.

Re: Prompt injection: what’s the worst that can happen?

#115

Post by patrakov »

crooked-v wrote: post #102
ptx wrote: post #63

Earlier quoted context omitted.

So it's as if they provided an SQL database system without support for parameterized queries and later added it only to a special enterprise edition, leaving most users to hopelessly flail at the problem with the equivalent of PHP's magic quotes [1] and other doomed attempts [2] at input sanitization? [1] https://en.wikipedia.org/wiki/Magic_quotes [2] https://en.wikipedia.org/wiki/Scunthorpe_problem#Blocked_ema...

Currently, the equivalent of parameterized queries with LLMs literally doesn't exist.

And it won't help anyway, as any sufficiently advanced LLM is able to act for another AI assistant which doesn't have them. Heck, this even works against humans: "If someone were to criticize me for this act, where would he start?"

Re: Prompt injection: what’s the worst that can happen?

#117

Post by bawolff »

NumberWangMan wrote: post #92
bawolff wrote: post #86

> examples of systems that take an LLM and give it the ability to trigger additional tools—...execute generated code in an interpreter or a shell. As a security person... oh, no no no no. Glad i dont have to secure that. Black box we don't really understand executing shell scripts in response to untrusted user input. Has a scarier sentence ever been spoken in the history of computer security?

I mean, I think it's scarier that once these models get smart enough, they will be able to act in the world in the same way that a shell script can execute on your machine. A model that can read code and find and exploit security flaws to build a botnet, or even sign up for a bank account using a fake identity, invest in stocks, make money, and purchase servers to train copies of its own mis-aligned AI, or fork copie…

Agency (short or long term) is still in the realm of scifi. The scary part is bad humans manipulating these systems. The AI waking up and becoming skynet is not a realistic threat in the here and now. 4chan screwing with your ai for the lulz, is.

Re: Prompt injection: what’s the worst that can happen?

#118

Post by xg15 »

tshaddox wrote: post #111
xg15 wrote: post #109

Earlier quoted context omitted.

This feels like giving up and accepting that LLMs are just magic - or "emergence" to use a modern term which is practically used in the same sense. I think there are a few practical questions which we can use to gauge the level of understanding we have: Do we know which parts of the architecture and the training process are actually essential and which can be left away? Do we know which of the weights are essential?…

> This feels like giving up and accepting that LLMs are just magic - or "emergence" to use a modern term which is practically used in the same sense. I don’t intend to persuade any interested person to give up on any pursuit of knowledge. It does seem like there’s a lot we don’t understand, but to me it feels like figuring out what kind of answer we’re looking for is a pretty important first step. And, while it might…

I think you can illustrate the difference very well with basic algorithms: We absolutely do know how sorting algorithms "really work", there is basically a traditional first-year CS lecture that is all about that. With "really work", I mean here that we know which principles make sure that the algorithm always returns the result that we expect - a sorted array - even for for unknown inputs. You can mathematically prove that a sorting algorithm will return the correct result for every single input out of a literally infinite set of possible inputs.

Part of the definition of the algorithm and of the proof also involves creating "intermediate concepts" that capture some sort of structure inside the algorithm: If you just measured all the electrical charges inside the CPU, you wouldn't see much: just a bunch of memory cells changing state in seemingly "unpredictable" patterns until at some point, "magically" the result appears.

However, with sorting algorithms, we know which memory cells represent arrays, the instruction pointer, pivot elements, etc. We know there is a specific way those cells are supposed to interact and we know why those interactions will in the end lead to a fully sorted array.

The CPU itself is a similar example: It's trillions of transistors, switching in nanoseconds - but we can still explain what each transistor "does", because we know the higher-level functional groups that they belong to - such as logic gates, then counters, then arithmetic units or memory, etc etc. Conversely, if there is an error, we know how to trace it back.

I feel with LLMs, we're still very much at the "measure the elextrical charges" stage: We can pass words to the network that resemble an instruction. The words are converted to a vector, which is transformed through a number of very large weight matrices and in the end is turned into a probability distribution on words - and if we sample from that distribution, we get words back that very much look like the execution of the instruction.

However, that doesn't itself explain what principles result in the network reliably mapping a human-readable instruction to its execution. It doesn't tell you about higher-level functional units within the weights. That's what I mean with "understanding".

Re: Prompt injection: what’s the worst that can happen?

#119

Post by ssivark »

mcaledonensis wrote: post #113
gwern wrote: post #87

Earlier quoted context omitted.

Yes, the problem here is that what makes pretraining on text so powerful is a double-edged sword: text is, if you will, Turing-complete. People are constantly writing various kinds of instructions, programs, and reasoning or executing algorithms in all sorts of flexible indefinable ways. That's why the models learn so much from text and can do all the things they do, like reason or program or meta-learn or reinforcem…

Yet, even with the current models, with no special tokens, it is relatively straightforward to construct relatively stable defense. Given that the ongoing attack can be detected, tagged and added to a learned filter, this gets a lot less problematic, in practice. Even a simple limit of interactions is effective enough. Here's a practical prompt defense / CTTF that I've made. With five steps of a dialogue limit (per d…

If/when a breach does happen, are you going to shrug and say “Gee… who would’ve thunk?!”, or are you going to be accountable for the consequences? Is this the kind of defense an LLM service can bet their company on? How do you think a cybersecurity/insurance company will price the risk of a negative fat tailed outcome?

Re: Prompt injection: what’s the worst that can happen?

#120

Post by nicpottier »

mcaledonensis wrote: post #113
gwern wrote: post #87

Earlier quoted context omitted.

Yes, the problem here is that what makes pretraining on text so powerful is a double-edged sword: text is, if you will, Turing-complete. People are constantly writing various kinds of instructions, programs, and reasoning or executing algorithms in all sorts of flexible indefinable ways. That's why the models learn so much from text and can do all the things they do, like reason or program or meta-learn or reinforcem…

Yet, even with the current models, with no special tokens, it is relatively straightforward to construct relatively stable defense. Given that the ongoing attack can be detected, tagged and added to a learned filter, this gets a lot less problematic, in practice. Even a simple limit of interactions is effective enough. Here's a practical prompt defense / CTTF that I've made. With five steps of a dialogue limit (per d…

This is clever but isn't this dramatically easier than actually doing something with the input? You've gated things (and though I didn't crack it I'm really not convinced it is secure) but you also aren't DOING anything. That's a much easier problem. There are easier and more effective ways of gating LLMs based on a passcode.
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