Show HN: Amla Sandbox – WASM bash shell sandbox for AI agents

This project looks very cool - I've been trying to build something similar in a few different ways (https://github.com/simonw/denobox is my most recent attempt) but this is way ahead of where I've got, especially given its support for shell scripting.

I'm sad about this bit though:

> Python code is MIT. The WASM binary is proprietary—you can use it with this package but can't extract or redistribute it separately.

sd2k · 12 days ago

I posted this elsewhere in the thread, and don't want to spam it everywhere (or take away from Amla!), but you might be interested in eryx [1] - the Python bindings [2] get you a similar Python-in-Python sandbox based on a WASI build of CPython (props to the componentize-py [3] people)!

[1]: https://github.com/sd2k/eryx/

[2]: https://pypi.org/project/pyeryx/

[3]: https://github.com/bytecodealliance/componentize-py/

simonw · 12 days ago

That's really cool.

Any chance you could add SQLite?

  % uv run --with pyeryx python 
  Installed 1 package in 1ms
  Python 3.14.0 (main, Oct  7 2025, 16:07:00) [Clang 20.1.4 ] on darwin
  Type "help", "copyright", "credits" or "license" for more information.
  >>> import eryx
  >>> sandbox = eryx.Sandbox()
  >>> result = sandbox.execute('''
  ... print("Hello from the sandbox!")
  ... x = 2 + 2
  ... print(f"2 + 2 = {x}")
  ... ''')
  >>> result
  ExecuteResult(stdout="Hello from the sandbox!\n2 + 2 = 4", duration_ms=6.83, callback_invocations=0, peak_memory_bytes=Some(16384000))
  >>> sandbox.execute('''
  ... import sqlite3
  ... print(sqlite3.connect(":memory:").execute("select sqlite_version()").fetchall())
  ... ''').stdout
  Traceback (most recent call last):
    File "<python-input-6>", line 1, in <module>
      sandbox.execute('''
      ~~~~~~~~~~~~~~~^^^^
      import sqlite3
      ^^^^^^^^^^^^^^
      print(sqlite3.connect(":memory:").execute("select sqlite_version()").fetchall())
      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
      ''').stdout
      ^^^^
  eryx.ExecutionError: Traceback (most recent call last):
    File "<string>", line 1, in <module>
    File "<string>", line 125, in _eryx_exec
    File "<user>", line 2, in <module>
    File "/python-stdlib/sqlite3/__init__.py", line 57, in <module>
      from sqlite3.dbapi2 import *
    File "/python-stdlib/sqlite3/dbapi2.py", line 27, in <module>
      from _sqlite3 import *
  ModuleNotFoundError: No module named '_sqlite3'

Filed a feature request here: https://github.com/eryx-org/eryx/issues/28

souvik1997 · 12 days ago

Thanks Simon! Denobox looks very cool: Deno's permissions model is a natural fit for this.

On the licensing: totally fair point. Our intention is to open source the WASM too. The binary is closed for now only because we need to clean up the source code before releasing it as open-source. The Python SDK and capability layer are MIT. We wanted to ship something usable now rather than wait. Since the wasm binary runs in wasmtime within an open source harness, it is possible to audit everything going in and out of the wasm blob for security.

Genuinely open to feedback on this. If the split license is a blocker for your use cases, that's useful signal for us.

simonw · 12 days ago

That's great to hear. The split license is a blocker for me because I build open source tools for other people to use, so I need to be sure that all of my dependencies are things I can freely redistribute to others.

vimota · 12 days ago

Simon - would love if you could take a look at Localsandbox (https://github.com/coplane/localsandbox) - it was partly inspired by your Pyodide post!

simonw · 12 days ago

I tried it (really like the API design) but ran into a blocker:

  uv run --with localsandbox python -c '
  from localsandbox import LocalSandbox
  
  with LocalSandbox() as sandbox:
      result = sandbox.bash("echo hi")           
      print(result.stdout)                
  '

Gave me:

  Traceback (most recent call last):
    File "<string>", line 5, in <module>
      result = sandbox.bash("echo hi")
    File "/Users/simon/.cache/uv/archive-v0/spFCEHagkq3VTpTyStT-Z/lib/python3.14/site-packages/localsandbox/core.py", line 492, in bash
      raise SubprocessCrashed(
      ...<2 lines>...
      )
  localsandbox.exceptions.SubprocessCrashed: Node subprocess crashed: error: Failed reading lockfile at '/Users/simon/.cache/uv/archive-v0/spFCEHagkq3VTpTyStT-Z/lib/python3.14/site-packages/localsandbox/shim/deno.lock'
  
  Caused by:
      Unsupported lockfile version '5'. Try upgrading Deno or recreating the lockfile

Actually that was with Deno 2.2.10 - I ran "brew upgrade deno" and got Deno 2.6.7 and now it works!

phickey · 12 days ago

https://github.com/bytecodealliance/ComponentizeJS is a Bytecode Alliance project which can run JS in a SpiderMonkey-based runtime as a Wasm component

Cool to see more projects in this space! I think Wasm is a great way to do secure sandboxing here. How does Amla handle commands like grep/jq/curl etc which make AI agents so effective at bash but require recompilation to WASI (which is kinda impractical for so many projects)?

I've been working on a couple of things which take a very similar approach, with what seem to be some different tradeoffs:

- eryx [1], which uses a WASI build of CPython to provide a true Python sandbox (similar to componentize-py but supports some form of 'dynamic linking' with either pure Python packages or WASI-compiled native wheels) - conch [2], which embeds the `brush` Rust reimplementation of Bash to provide a similar bash sandbox. This is where I've been struggling with figuring out the best way to do subcommands, right now they just have to be rewritten and compiled in but I'd like to find a way to dynamically link them in similar to the Python package approach...

One other note, WASI's VFS support has been great, I just wish there was more progress on `wasi-tls`, it's tricky to get network access working otherwise...

[1] https://github.com/eryx-org/eryx [2] https://github.com/sd2k/conch

souvik1997 · 12 days ago

Great question. We cheated a bit; we didn't compile the GNU coreutils to wasm. Instead, we have Rust reimplementations of common shell commands. It allows us to focus on the use cases agents actually care about instead of reimplementing all of the corner cases exactly.

For `jq` specifically we use the excellent `jaq_interpret` crate: https://crates.io/crates/jaq-interpret

curl is interesting. We don't include it currently but we could do it without too much additional effort.

Networking isn't done within the wasm sandbox; we "yield" back to the the caller using what we call "host operations" in order to perform any IO. This keeps the Wasm sandbox minimal and as close to "pure compute" as possible. In fact, the only capabilities we give the WASI runtime is a method to get the current time and to generate random numbers. Since we intercept all external IO, random number generation, time, and the Wasm runtime is just for pure computation, we also get perfect reproducibility. We can replay anything within the sandbox exactly.

Your approach with brush is interesting. Having actual bash semantics rather than "bash-like" is a real advantage for complex scripts. The dynamic linking problem for subcommands is a tough one; have you looked at WASI components for this? Feels like that's where it'll eventually land but the tooling isn't there yet.

Will check out eryx and conch. Thanks for sharing!

sd2k · 12 days ago

Hah, that is exactly the same approach I landed on. Fortunately the most common tools either seem to have Rust ports or are fairly easy to port 80% of the functionality! Conch's Wasm file is around ~3.5MB and only has a few tools though so I can see it growing. I think for the places where size really matters (e.g. the web) it should be possible to split it using the component model and `jco` (which I think splits Wasm components into modules along interface boundaries, and could defer loading of unused modules) but I haven't got that far yet.

I did something very similar to you for networking in eryx too (no networking in conch yet); defined an `eryx:net` interface in WIT and reimplemented the `urllib` module using host networking, which most downstream packages (httpx, requests, etc) use far enough down the stack. It's a tradeoff but I think it's pretty much good enough for most use cases like this, and gives the host full control which is great.

Oh full transparency, the vast majority of conch and eryx were written by Opus 4.5. Being backed by wasmtime and the rather strict Rust compiler is definitely a boon here!

quantummagic · 13 days ago

Sure, but every tool that you provide access to, is a potential escape hatch from the sandbox. It's safer to run everything inside the sandbox, including the called tools.

souvik1997 · 13 days ago

That's definitely true. Our model assumes tools run outside the sandbox on a trusted host—the sandbox constrains which tools can be called and with what parameters. The reason for this is most "useful" tools are actually just some API call over the network (MCP, REST API, etc.). Then you need to get credentials and network access into the sandbox, which opens its own attack surface. We chose to keep credentials on the host and let the sandbox act as a policy enforcement layer: agents can only invoke what you've explicitly exposed, with the constraints you define.

ai-christianson · 12 days ago

We went down the WASM sandboxing rabbit hole at Gobii when building our agent infra. The pitch is appealing until you realize the tradeoff: you either accept a limited environment with reimplemented tools, or you emulate your way back to a full Linux system (like agentvm does at 173MB) and wonder why you didn't just start with gvisor or Firecracker.

We landed on gvisor in k8s. Our agents run headless Chromium for browser automation, ffmpeg for media processing, yt-dlp, ripgrep, fzf - real tools that would be a nightmare to port or reimplement. Actual Linux with the full ecosystem, solid isolation, no emulation overhead.

Interesting project though - the capability-based tool validation layer seems useful regardless of what's running underneath.

benatkin · 12 days ago

The readme exaggerates the threat of agents shelling out and glosses over a serious drawback of itself. On the shelling out side, it says "One prompt injection and you're done." Well, you can run a lot of these agents in a container, and I do. So maybe you're not "done". Also it's rare enough that this warning exaggerates - Claude Code has a yolo mode and outside of that, it has a pretty good permission system. On glossing over the drawback: "The WASM binary is proprietary—you can use it with this package but can't extract or redistribute it separately." And who is Amla Labs? FWIW the first commit is in 2026 and the license is in 2025.

Fair points.

On containers: yes, running in Docker/Firecracker works. The "one prompt injection and you’re done" framing is hyperbolic for containerized setups. The pitch is more relevant for people running agents in their local environment without isolation, or who want something lighter than spinning up containers per execution.

On the licensing: completely valid concern. We are a new company (just two cofounders right now) and the binary is closed for now only because we need to clean up the source code before releasing it as open-source. The Python SDK and capability layer are MIT.

I get that "trust us" isn’t compelling for a security product from an unknown entity, but since the Wasm binary runs within wasmtime (one of the most popular Wasm runtimes) and you can audit everything going in and out of it, the security story should hopefully be more palatable while we work on open sourcing the Wasm core.

The 2025/2026 date discrepancy is just me being sloppy with the license

Sharing our version of this built on just-bash, AgentFS, and Pyodide: https://github.com/coplane/localsandbox

One nice thing about using AgentFS as the VFS is that it's backed by sqlite so it's very portable - making it easy to fork and resume agent workflows across machines / time.

I really like Amla Sandbox addition of injecting tool calls into the sandbox, which lets the agent generated code interact with the harness provided tools. Very interesting!

Thanks for sharing localsandbox! sqlite-backed VFS for fork and resume workflows is very interesting.

syrusakbary · 13 days ago

This is great!

While I think that with their current choice for the runtime will hit some limitations (aka: not really full Python support, partial JS support), I strongly believe using Wasm for sandboxing is the way for the future of containers.

At Wasmer we are working hard to make this model work. I'm incredibly happy to see more people joining on the quest!

apignotti · 13 days ago

Hi, if you like the idea of Wasm sandboxing you might be interested in what we are working on: BrowserPod :-)

https://labs.leaningtech.com/blog/browserpod-beta-announceme...

https://browserpod.io

Browserpod is great, been following it for a bit. Keep the good work up!

The main issue that I see with Browserpod is very similar to Emscripten: it's designed to work mainly in the browser, and not outside.

In my view, where Wasm really shines, is for enabling containers that work seamlessly in any of this environments: browsers, servers, or even embedded in apps :)

Appreciate your support! We deliberately chose a limited runtime (quickjs + some shell applets). The tool parameter constraint enforcement was more important to us than language completeness. For agent tool calling, you don't really need NumPy and Pandas.

Wasmer is doing great work—we're using wasmtime on the host side currently but have been following your progress. Excited to see WASM sandboxing become more mainstream for this use case.

> For agent tool calling, you don't really need NumPy and Pandas.

That's true, but you'll likely need sockets, pydantic or SQLAlchemy (all of of them require heavy support on the Wasm layer!)

rellfy · 12 days ago

I really like the capability enforcement model, it's a great concept. One thing this discussion is missing though is the ecosystem layer. Sandboxing solves execution safety, but there's a parallel problem: how do agents discover and compose tools portably across frameworks? Right now every framework has its own tool format and registry (or none at all). WASM's component model actually solves this — you get typed interfaces (WIT), language interop, and composability for free. I've been building a registry and runtime (also based on wasmtime!) for this: components written in any language, published to a shared registry, runnable locally or in the cloud. Sandboxes like amla-sandbox could be a consumer of these components. https://asterai.io/why

The ecosystem layer is a hard but very important problem to solve. Right now we define tools in Python on the host side, but I see a clear path to WIT-defined components. The registry of portable tools is very compelling.

Will checkout asterai, thanks for sharing!

skybrian · 12 days ago

Exposing tools to the AI as shell commands works pretty well? There are many standards to choose from for the actual network API.

Shell commands work for individual tools, but you lose composability. If you want to chain components that share a sandboxed environment, say, add a tracing component alongside an OTP confirmation layer that gates sensitive actions, you need a shared runtime and typed interfaces. That's the layer I'm building with asterai: standard substrate so components compose without glue code. Plus, having a central ecosystem lets you add features like the traceability with almost 1 click complexity. Of course, this only wins long term if WASM wins.