Cordium: FOSS sandbox platform that eliminates credential injection

Hacker News

Hello HN, Cordium is a general-purpose sandbox platform built on Kubernetes and Octelium, may main work https://github.com/octelium/octelium , that can be used for various use cases, including coding for developers with VSCode, Zed, etc. (i.e. self-hosted GitHub Codespaces alternative), AI agent tasks (i.e. FOSS alternative to AI sandbox products such as E2B, Daytona, etc.), CI/CD workloads (e.g. building and publishing Docker images etc.), and more importantly for secretless remote access to infrastructure for devs and automated workloads. The main _differentiator_ here, compared to other dev environments and sandbox platforms, is that Cordium automatically provides identity-based, secretless secure access to resources/infrastructure (e.g. APIs, SSH, databases, k8s, etc.) without having to inject credentials (e.g. API keys, SSH private keys, database passwords, etc.) into the sandbox where the upstream credential is held by the identity-aware proxy of the Octelium-protected resource outside the reach of the sandbox. You can simply think of it as a sandbox + ZTNA/remote-access-VPN baked-in where access to infrastructure is based on identity and policy-as-code rather than credentials. Cordium is a purely FOSS project under Apache 2.0 that's meant for self-hosting and there are no plans for a pro/SaaS/cloud version. The development of the project started back in 2022 and it is already being used by a few organizations that use Octelium since last year. Happy to answer any questions.

Visit product View on Hacker NewsMay 31, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, dock, tasks · Missing: mac, agents, macos

90%90% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, vpn, including · Missing: supports, reddit linkedin, podcasting

82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host · Missing: plus, intuitive, reviews

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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