Drop - Rootless Linux sandbox with gVisor support
Show HN: Drop – a rootless Linux sandbox with gVisor support
Drop is a rootless Linux sandbox that isolates programs and coding agents without disrupting your workflow. Inspired by Python's virtualenv, it creates disposable environments with their own home directories, using your existing distribution so all installed programs remain available. Configure file, directory, and network access via TOML, and optionally run programs on the gVisor user-space kernel for an extra isolation layer. Perfect for safely running AI agents with --dangerously-skip-permissions or testing third-party packages from PyPI or npm, Drop contains potential damage within the sandbox while keeping your actual system secure.
A hallucinated rm -rf ~ doesn't touch your actual home dir. A prompt injection targeting ~/.ssh finds nothing. A connection to services running on localhost is rejected.
- refibrillator
Hi OP, funny enough I’m working on something very similar. Lots of us are I guess! Take that as validation of your thinking.
I like that your readme has a couple paragraphs comparing to popular tools in this space. Personally I feel it is a bit light on the security differentiators (if any). For example you are using the same fundamental primitives that are used in nsjail, runc, etc. Thus it seems you have recreated those libraries in some aspects, so would be curious to hear your rationale for approaching this way vs building explicitly on those primitives.
- programd
So there are a lot of ad-hoc solutions everybody is using for agent isolation and Drop looks well thought out. But the obvious question is what do the pros use? What does Anthropic, OpenAI, SpaceXAI, Google and Amazon do in house to deal with the isolated agent environment problem?
Based on past experience I'm guessing everybody is using Kubernetes, but what are the details? Stripped down VMs on Kubernetes? Hardened containers on Kubernetes? Can the rest of us spin up something comparable on K3s?
Anybody knows the answers and can share?
- saghm
This is super interesting to me. I've slowly been working on something similar (https://gitlab.com/saghm/tartarus) because my ideal sandboxing is "prevent writing to anything outside this dir but still allow reading to most things so that I don't have to manually copy things into a container/VM". I approached it by trying to figure out how to build up a bubblewrap based on a config that gave the properties I wanted, with the hope that I could eventually expand it to support other platforms via stuff like `sandbox-exec` on MacOS, but I haven't had time to work on it more for a while.
At a glance, this seems to be providing most of what I was originally looking for when I ended up deciding I'd have to write it myself, but focusing specifically on Linux and providing a more full-fledged sandbox rather than only caring about a small set of permissions that I personally had a need for. Probably the biggest (and least hardened) feature that I spent time on in mine was trying to figure out how to allow arbitrary GUI apps so that I could run agents in it via Zed.
I'm definitely going to try this out and see how well it works for me. It's insane to me that this is something none of the big AI companies have bothered solving this yet other than via opaque rules built into their harnesses or absolutely awful manual rules that expect me to hard-code shapes of shell commands that I want to allow or not allow.
- p2004a
Thank you for building it! I started using Drop a few weeks ago, and I've been very happy with it so far (thanks again for quickly fixing a few issues I've reported :)!).
For me, it nails the convenience vs isolation aspect quite well, and I would like to get to a point where I can use it for all my development by default.
The main challenges that I still have, which none of the solutions I've found so far resolve, are:
- development of containerized applications, where e.g., docker/podman compose is used to bring up services
- development of GUI applications with hardware acceleration, like games (maybe security contexts for pipewire and wayland, like what's done in flatpak would be a good path?)
When I did my research in this space last time, https://litterbox.work/ was another option I've considered, and it is very nice too, but the friction is a bit higher than drop: it's slower to rebuild envs, lacks a "base" config, etc. Drop was much easier to adopt for me so far.
- binsquare
Every comment is talking about their own sandbox implementation.