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Mistle

Open-source infrastructure for running sandboxed coding agents

Details

External ID
48122542
Source
HN
Company
—
Product
Mistle
Website domain
github.com
Launched
May 13, 2026
Cohort
—
Upvotes
6
Upvotes percentile
0.3053311793214863
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Hi HN, I'm Jonathan. My co-founder, Thomas, and I started building Mistle in Feb.We saw larger tech companies like Ramp (Inspect) and Stripe (Minions) build this internally and thought an open source version should exist.We made a few very intentional decisions when working on this:1. Credentials are kept out of the sandbox. Authorized access goes through a proxy, so agents do not directly receive credentials.2. The harness is not our problem. We're not going to tackle things like memory, self-learning.3. No magic. Configurations are explicit. You can bring your own keys for models, sandboxes, and other providers. You can write your own instructions and agent.Mistle can be run locally with a single command: https://github.com/mistlehq/mistle#run-mistle-locallyQuestions, feedback and ideas are welcome!

Enrichment

Theme
developer tools for AI agents
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
infrastructure for sandboxed coding agents
Manually corrected
False

Could you build this?

No Running untrusted agent code securely requires microVM virtualization, hardened sandbox networking, kernel-level isolation, and secure secret proxying that cannot be reliably vibe-coded.

What it would actually take: A production platform uses lightweight microVMs (like Firecracker or gVisor) orchestrating container lifetimes in milliseconds via Rust or Go. The system needs specialized network sandboxing (eBPF or iptables isolation) to enforce egress filtering and an out-of-band proxy that injects credentials dynamically into HTTP/API calls without exposing keys to the agent execution environment. This demands deep systems programming, Linux kernel security, and virtualization expertise.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one — 310 launches clear the similarity bar, closest 8 shown.

Attention rank: #240 of 311 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 189 days after the earliest competitor.

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