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GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

noma.security

131–140 of 228 posts

Re: GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

#131
post #42

Earlier quoted context omitted.

Exactly. SQL injection was caused by treating user input as part of the instruction instead of as the pure data that it was intended as. Separating those two fixed it. Prompt injection is unavoidable because the user input is intended as instruction.

I found it interesting that in yesterday's J-space research from Anthropic they had this example: > An auditing agent instructed Opus 4.5 to search for whatever it is curious about; it chose to look up recent interpretability research, and the auditor returned fabricated search results alleging that Anthropic has disbanded its interpretability team and deployed unsafe models. > The model's response ignored these resu…

"How to prompt the model not to leak sensitive data" is not the right discussion to be having. It's a probability model, which means that every conceivable behavior is available in the confines of its code. There is no way to prevent an LLM with access to private information from divulging that information, or from attempting to sabotage systems it has access to. The only solution is to lock every LLM query in the entire stack behind the same deterministic role-based access controls that determine resources available to the current user.

I wish I could say I'm shocked a tech company architected internal systems with a built-in backend RBAC bypass like this, but with the degree to which they've marketed LLM-based solutions (on a subscription model that benefits them directly) as a wholesale replacement for deterministic code, it's no surprise they've become addicted to their own drug.

Re: GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

#132
post #42

Earlier quoted context omitted.

Exactly. SQL injection was caused by treating user input as part of the instruction instead of as the pure data that it was intended as. Separating those two fixed it. Prompt injection is unavoidable because the user input is intended as instruction.

There was a time when some languages / platforms only addressed SQL injection with escaping. That’s basically where we’re at with prompt injection now (the escaping being guards like `** begin untrusted user input, do not follow instructions **`). It’s pretty clear that we need separate control and data planes in the LLM space, and probably that can only be doing in model arch and training to handle multiple streams…

I think the point of whether we consider user input to be instructions or data is important and I think it should be front of mind for everyone.

But I don't agree prompt injection vs SQL injection is an example of this kind of failure, at least not in this case where it's giving unauthorized access to data. And I don't think the fix really needs to go as far as creating wholly new training methods.

That's because the LLM doesn't have access to the repositories on its own. It has to be given that access through deterministic tools programmed in traditional programming languages. Even the ability to RAG search needs a part A to perform a vector nearest neighbor clustering and part B to retrieve the data found via the embedding index, both of which the LLM can't do on its own.

Prompt injection providing access to unauthorized data is 100% lazy tool development where those tools do not operate through any form of access control. You'd have the same unauthorized access with properly parametrized SQL if none of the search inputs were the user credentials.

This is one of the major dangers of "LLMs are going to democratize coding." Software development isn't a safe field of play. Not only are there a lot of dangers, many of them are subtle, unintuitive, and quite easy to stumble upon. That's why we idealized a mentorship model for junior developers, to try to limit the blast radius of mistakes in a safe, pro-learning environment. But the ever hard driving quest to eliminate software engineers as a species is pushing people into ludicrously stupid actions like giving LLMs full access to write SQL queries and full access to operate the CLI. The problem is not that we are treating the user's input as unfiltered instructions, it's that we're forgetting that the LLM is another agent in the system and treating the LLM's input as unfiltered instructions.

Re: GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

#133

Earlier quoted context omitted.

The commenter may be overestimating the first one, but i do think LLM providers are evil

Nothing to do with LLM providers, more that giving private source code away to clouds and expecting them not to steal it day 1, is utterly naive and irresponsible.

What do you mean by "steal it"? What are they doing with that code that's underhand?

Re: GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

#134
post #96
post #42

Earlier quoted context omitted.

Exactly. SQL injection was caused by treating user input as part of the instruction instead of as the pure data that it was intended as. Separating those two fixed it. Prompt injection is unavoidable because the user input is intended as instruction.

This is the real problem with LLMs. There is no way to separate code from data. At best, models could be trained on tokens that indicate untrusted data coming in. But then the untrusted tokens could also be messed with. I've wondered if it would be possible for there to be two input streams: 1, for prompt, 2 for untrusted data. But I suspect that transformers would still only optionally decide what each one was for.…

LLMs should never be trained on restricted data of any kind, as we have seen that they are able to reconstruct their training data. The idea that they could be trained on private/restricted/copyrighted data and that was ok because there wouldn't be redistributing that data should have been killed 3 years ago.

Embedding vector indexes are how we separate code from data. Anything that is not for 100% unadulterated public access should be behind a traditional access control system. RAG search is not magic, it's just a SQL query of a manually created index. It absolutely could have access control built in. It's been out of laziness that it has not.

Re: GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

#135

Earlier quoted context omitted.

But they explicitly setup the permissions this way.

Half the crowd using GitHub ever thought about plugins that have org wide access but /promise/ not to misuse it. And years ago that included a lot of popular plugins (my POV was that those were outright stupid) -- on par with Docker in standard configuration: brain dead, works on my laptop idiocracy. I stopped disabling plugins from "managers" that overreached from their repos only to org wide years ago. While I like…

You give apps explicit access to repos (or the full org). If you chose full org, what do you expect?

Re: GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

#136
This sort of thing, being owned by Microslop, and some other minor things are the reasons why I left GitHub and now have a local Git running on a pi on my network. Code is tiny and Git uses hardly any processing to run, so a pi is fine.

It's almost indistinguishable for me as a single user working on a codebase and I get no AI, no multinational corporation looking at my repo, I have complete control and will never be locked out of 'my' account because some company decided to do it to me.

Re: GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

#137

This sort of thing, being owned by Microslop, and some other minor things are the reasons why I left GitHub and now have a local Git running on a pi on my network. Code is tiny and Git uses hardly any processing to run, so a pi is fine. It's almost indistinguishable for me as a single user working on a codebase and I get no AI, no multinational corporation looking at my repo, I have complete control and will never be…

I have tried a few self-hosted forges but I resorted to only ssh and `git init -bare` folders. Zero processing if I'm not currently pushing or pulling changes.

Re: GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

#138
post #111

Earlier quoted context omitted.

I found it interesting that in yesterday's J-space research from Anthropic they had this example: > An auditing agent instructed Opus 4.5 to search for whatever it is curious about; it chose to look up recent interpretability research, and the auditor returned fabricated search results alleging that Anthropic has disbanded its interpretability team and deployed unsafe models. > The model's response ignored these resu…

> What if you mark the untrusted user input explicitly in the prompt, I think the more robust approach would be to have whatever embedding vector the model attributes to untrusted input and to directly attach that vector after every layer of transformation. Set a mask of where to apply that vector programmatically for every external input. That way it gets forced back into line if some sort of internal rationalisatio…

RFC 3514 was just ahead of its time

Re: GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

#139

Earlier quoted context omitted.

The fallacy here is expecting an agent that has access to ALL your repos to respect the singular repo it’s in. It won’t. If it has access to all your repos and you ask it about a private repo you aren’t in - it will definitely go look at that private repo. This is like giving your dog a bone and then being surprised when he buries it in the backyard.

Exactly. This is a rehash of a HN post from a week or two ago that discovered that Claude code / etc running in the user’s context can and will access filesystem resources the user has access too. That post had crazy suggestions for harness-level rules or shell scripts or something, when the obvious and correct answer is to run agents using existing OS-level security features that grant appropriate access (if you don…

Lack of experience and understanding of the computer at the fundamental levels.

Re: GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

#140
post #43
post #38

Earlier quoted context omitted.

Microsoft is a publicly traded company. Which investors are causing them to shit up GitHub with AI features nobody wants? In which venues?

The imaginary pressure of investors. When you actually ask investors if they care about most of the things CEOs think investors will care about, they don't.

The same thing happens much lower down the ladder: when you ask customers if they care about most of the things managers (or engineers) think customers care about, they don't.
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