Deno Sandbox
The safest, simplest way to run untrusted code.
What it does
The safest, simplest way to run untrusted code. Secure Linux microVMs with instant startup, strict network policies, and isolated secrets.
Does a similar job
all alternatives →- ZSZerobox – Sandbox any command with file, network, credential controlsMar 2026 · github.com · ▲141
I'm excited to introduce Zerobox, a cross-platform, single binary process sandboxing CLI written in Rust. It uses the sandboxing crates from the OpenAI Codex repo and adds additional functionalities like secret injection, SDK, etc. Watch the demo: https://www.youtube.com/watch?v=wZiPm9BOPCg Zerobox follows the same sandboxing policy as Deno which is deny by default. The only operation that the command can run is reading files, all writes and network I/O are blocked by default. No VMs, no Docker, no remote servers. Want to block reads to /etc? zerobox…
- SASandy – A tiny Sandbox to run untrusted code ️2020 · github.com · ▲64
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- SUSandboxing untrusted code using WebAssemblyFeb 2026 · github.com · ▲76
Hi everyone, I built a runtime to isolate untrusted code using wasm sandboxes. Basically, it protects your host system from problems that untrusted code can cause. We’ve had a great discussion about sandboxing in Python lately that elaborates a bit more on the problem [1]. In TypeScript, wasm integration is even more natural thanks to the close proximity between both ecosystems. The core is built in Rust. On top of that, I use WASI 0.2 via wasmtime and the component model, along with custom SDKs that keep things as idiomatic as possible. For example, in Python we have a simple decorator:…
- LFLocal-First Linux MicroVMs for macOSFeb 2026 · shuru.run · ▲213
Shuru is a lightweight sandbox that spins up Linux VMs on macOS using Apple's Virtualization.framework. Boots in about a second on Apple Silicon, and everything is ephemeral by default. There's a checkpoint system for when you do want to persist state, and sandboxes run without network access unless you explicitly allow it. Single Rust binary, no dependencies. Built it for sandboxing AI agent code execution, but it works well for anything where you need a disposable Linux environment.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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