> If you look at the security measures in other coding agents, they're mostly security theater. As soon as your agent can write code and run code, it's pretty much game over.
At least for Codex, the agent runs commands inside an OS-provided sandbox (Seatbelt on macOS, and other stuff on other platforms). It does not end up "making the agent mostly useless".
You’ll just end up approving things blindly, because 95% of what you’ll read will seem obviously right and only 5% will look wrong. I would prefer to let the agent do whatever they want for 15 minutes and then look at the result rather than having to approve every single command it does.
That kind of blanket demand doesn't persuade anyone and doesn't solve any problem.
Even if you get people to sit and press a button every time the agent wants to do anything, you're not getting the actual alertness and rigor that would prevent disasters. You're getting a bored, inattentive person who could be doing something more valuable than micromanaging Claude.
Managing capabilities for agents is an interesting problem. Working on that seems more fun and valuable than sitting around pressing "OK" whenever the clanker wants to take actions that are harmless in a vast majority of cases.
It’s not just annoying; at scale it makes using the agent clis impossible. You can tell someone spends a lot of time in Claude Code: they can type —dangerously-skip-permissions with their eyes closed.
It's not reliable. The AI can just not prompt you to approve, or hide things, etc. AI models are crafty little fuckers and they like to lie to you and find secret ways to do things with alterior motives. This isn't even a prompt injection thing, it's an emergent property of the model. So you must use an environment where everything can blow up and it's fine.
I'm just guessing, but seems the people who write these agent CLIs haven't found a good heuristic for allowing/disallowing/asking the user about permissions for commands, so instead of trying to sit down and actually figure it out, someone had the bright idea to let the LLM also manage that allowing/disallowing themselves. How that ever made sense, will probably forever be lost on me.
`chroot` is literally the first thing I used when I first installed a local agent, by intuition (later moved on to a container-wrapper), and now I'm reading about people who are giving these agents direct access to reply to their emails and more.
> I'm just guessing, but seems the people who write these agent CLIs haven't found a good heuristic for allowing/disallowing/asking the user about permissions for commands, so instead of trying to sit down and actually figure it out, someone had the bright idea to let the LLM also manage that allowing/disallowing themselves. How that ever made sense, will probably forever be lost on me.
I don't think there is such a good heuristic. The user wants the agent to do the right thing and not to do the wrong thing, but the capabilities needed are identical.
> `chroot` is literally the first thing I used when I first installed a local agent, by intuition (later moved on to a container-wrapper), and now I'm reading about people who are giving these agents direct access to reply to their emails and more.
That's a good, safe, and sane default for project-focused agent use, but it seems like those playing it risky are using agents for general-purpose assistance and automation. The access required to do so chafes against strict sandboxing.
There still needs to be a harness running on your local machine to spawn the processes in their sandboxes. I consider that "part of the LLM" even if it isn't doing any inference.
If that part were running sandboxed, then it would be impossible for it to contact the OpenAI servers (to get the LLM's responses), or to spawn an unsandboxed process (for situations where the LLM requests it from the user).
That's obviously not true. You can do anything you want with a sandbox. Open a socket to the OpenAI servers and then pass that off to the sandbox and let the sandboxed process communicate over that socket. Now it can talk to OpenAI's servers but it can't open connections to any other servers or do anything else.
The startup process which sets up the original socket would have to be privileged, of course, but only for the purpose of setting up the initial connection. The running LLM harness process would not have any ability to break out of the sandbox after that.
As for spawning unsandboxed processes, that would require a much more sophisticated system whereby the harness uses an API to request permission from the user to spawn the process. We already have APIs like this for requesting extra permissions from users on Android and iOS, so it's not in-principle impossible either.
In practice I think such requests would be a security nightmare and best avoided, since essentially it would be like a prisoner asking the guard to let him out of jail and the guard just handing the prisoner the keys. That unsandboxed process could do literally anything it has permissions to do as a non-sandboxed user.
The devil is in the details. How much of the code running on my machine is confined to the sandbox vs how much is used in the boostrap phase? I haven't looked but I would hope it can survive some security audits.
If I'm following this it means you need to audit all code that the llm writes though as anything you run from another terminal window will be run as you with full permissions.
The thing is that on macOS at least, Codex does have the ability use an actual sandbox that I believe prevents certain write operations and network access.
Is it asking you permission to run that python command? If so, then that's expected: commands that you approve get to run without the sandbox.
The point is that Codex can (by default) run commands on its own, without approval (e.g., running `make` on the project it's working on), but they're subject to the imposed OS sandbox.
This is controlled by the `--sandbox` and `--ask-for-approval` arguments to `codex`.
Bit more general; don't run agents without some sort of restriction to what they can do provided by the OS in some way. Containers is one way, VMs another, most cases it's enough with just a chroot and using the unix permission system the rest of your system already uses.
What's the difference between resetting a container or resetting a VPS?
On local machine I have it under its own user, so I can access its files but it cannot access mine. But I'm not a security expert, so I'd love to hear if that's actually solid.
On my $3 VPS, it has root, because that's the whole point (it's my sysadmin). If it blows it up, I wanna say "I'm down $3", but it doesn't even seem to be that since I can just restore it from an backup.
I'm trying to understand this workflow. I have just started using codex. Literally 2 days in. I have it hooked up to my githbub repo and it just runs in the cloud and creates a pr. I have it touching only UI and middle layer code. No db changes, I always tell it to not touch the models.
At least for Codex, the agent runs commands inside an OS-provided sandbox (Seatbelt on macOS, and other stuff on other platforms). It does not end up "making the agent mostly useless".