borenstein

SUPER interesting! You just earned star #508. Going to take a look at this.

1. It's designed to give you an experience identical to using the Claude Code CLI in every respect, but with a much smaller blast radius. It's not currently set up to to work with your IDE. In that sense, it's a niche solution: I made it because I was trying to use a lot of agents at once, and I found that the rate-limiting factor was my ability to review and respond to permission pop-ups.

2. The VM is, in some sense, packaging. The main value adds are the two indirections between the agent and the outside world. Its access to `git` and `gh` are both mediated by a rules-based dispatcher that exercises fine-grained control in excess of what can be achieved with a PAT. HTTP requests pass through a middleware that block requests based on configurable rules.

Ah, let me clarify: I'm only using this to help me code faster. There are zero agents in the runtime for the financial tool.

As a matter of fact, the tool is zero-knowledge by design: state is decrypted in your browser and encrypted again before it leaves. There are no account integrations. The persistence layer sees noise. There are a couple of stateless backend tools that transiently see anonymous data to perform numerical optimizations.

But that's a story for another Show HN...

No shame in this! When you're using Claude code (or Cursor, or similar), you get these pop-ups rather frequently. "May I do XYZ web search?" "May I run this command?" "May I make this HTTP request?" This is for security, but it becomes the limiting step in your workflow if you're trying to use parallel agents.

These tools generally offer the ability to simply shut off these guardrails. When you do this, you're in what has come to be called "yolo mode."

I am arguing that, sandboxed correctly, this mode is actually safer than the standard one because it mitigates my own fatigue and frustration. These threats surface every hour of every day. Malicious actors are definitely a thing, but your own exhaustion is a far more present danger.

> How safe do you think this solution would be to let users execute untrusted code inside while being able to pip install and npm install all sorts of libraries

It's designed to be fairly safe in exactly that situation, because it's sandboxed twice over: once in a container and once in a VM. You start to layer on risk when you punch holes in it (adding domains to the whitelist, port-forwarding, etc).

> how do you deploy this inside AWS Lambda/Fargate for the same usecase These both seem like poor fits. I suspect Lambda is simply a non-starter. For Fargate, you'd be running k8s inside a VM inside a pod inside k8s. As an alternative, you could construct an AMI that runs the yolo-cage microk8s cluster without the VM, and then you could deploy it to EC2.

Totally agreed, but that level of attack sophistication is not a routine threat for most projects. Making sense of any information so exfiltrated will generally require some ad-hoc effort. Most projects, especially new ones, simply aren't going to be that interesting. IMO if you're doing something visible and sensitive, you probably shouldn't be using autonomous agents at all.

("But David," you might object, "you said you were using this to build a financial analysis tool!" Quite so, but the tool is basically a fancy calculator with no account access, and the persistence layer is E2EE.)

Thank you, nice catch. I will patch that today. And cutoff date is almost certainly why it happened.

It wasn't "vibe coded" in the sense that I was just describing what I want and letting the agent build it. But it definitely was built indirectly, and in an area that is not my primary focus. A charitable read is that I am borrowing epistemic fire from the gods; an uncharitable one is that I am simply playing with fire.

I am not apologetic about this approach, as I think it's the next step in a series of abstractions for software implementation. There was a time when I sometimes took some time to look at Java bytecode, but doing so today would feel silly.

Abstracting to what is in essence a non-deterministic compiler is going to bring with it a whole new set of engineering practices and disciplines. I would not recommend that anyone start with it, as it's a layer on top of SWE. I compare it to visual vs instrument flight rules.

Docker isn't virtualization; it's not that hard to infiltrate the underlying system if you really want to. But as for VMs--they are enough! They're also a lot of boilerplate to set up, manage, and interact with. yolo-cage is that boilerplate.

IMO, you should treat your agent's environment as pre-compromised. In that reading, your goal becomes security-in-depth.

Anthropic is trying to earn developer trust; they have a strong incentive to make sure that private keys and other details that the agent sees do not leak into the training data. But the agent itself is just a glorified autocomplete, and it can get confused and do stupid stuff. So I put it in a transparent prison that it can see out of but can't leave.

That definitely helps with the main failure modes I was worrying about, but it's just one layer. You definitely want to make sure that your production secrets are in an external vault (Hashicorp Vault, Google Secret Store, GitHub secrets, etc) that the agent can't access.

The things that agent is seeing should be dev secrets that maybe could be used as the start of a sophisticated exploit, but not the end of it. There's no such thing as perfect security, only very low probabilities of breach. Adding systems that are very annoying to breach and have little offer when you do greatly lowers the odds.

The credential have been a PITA. I was working on a PR this morning before work; I should have it tonight. You have to be careful because if you look like you're spoofing the client, you can get banned.

For Claude specifically, there are two places where it tracks state:

~/.claude.json -- contains a bunch of identity stuff and something about oauth

~/claude/ -- also contains something about oauth, plus conversation history, etc

If they're not _both_ present and well-formed, then it forces you back through the auth flow. On an ordinary desktop setup, that's transparent. But if you want to sandbox each thread, then sharing just the token requires a level of involvement that feels icky, even if the purpose is TOS-compliant.

I'm with you here! The idea with yolo-cage is that the worst the LLM can realistically do is open an awful PR and waste your time. (Which, trust me, it will.) Claude suggested the phrase: "Agent proposes, human disposes."

Thank you! Rate limits are an interesting topic with Claude Code right now. The Max subscription has them, and the API does not; but the Max subscription is an all-you-can-eat buffet, and the API is not. yolo-cage was built to be compatible with the Max subscription while remaining TOS-compliant because it wraps the official CLI with no modifications. That has so far meant for me that the experience is _too_ rate limited.

That said, I have not yet started playing with MCP servers. I suspect that they are completely broken inside yolo-cage right now, as they almost certainly get stopped by the proxy.

The leakage issue is real. Before there was a way to use "GPT Pro" models on enterprise accounts, I had a separate work-sponsored Pro-tier account. First thing I did was disable "improve models for everyone." One day I look and, wouldn't you know it, it had somehow been enabled again. I had to report the situation to security.

As far as lock-in, though, that's been much less of a problem. It's insanely easy to switch because these tools are largely interchangeable. Yes, this project is currently built around Claude code, but that's probably a one-hour spike away from flexibility.

I actually think the _lack_ of lock-in is the single biggest threat to the hyperscalers. The technology can be perfectly transformative and still not profitable, especially given the current business model. I have Qwen models running on my Mac Studio that give frontier models a run for their money on many tasks. And I literally bought this hardware in a shopping mall.

This was 100% not AI generated! Honestly, though, I've been talking to AI chatbots so much in the last year that I'm sure their style has rubbed off on me. At some point, I did a little math and determined that I had probably exchanged an order of magnitude more words back and forth with AIs than I will with my spouse over the course of our entire lives.