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Sshifu – SSH Login with SSO. Alternative to Teleport and Smallstep

Hacker News

Sshifu – SSH Login with SSO. Alternative to Teleport and Smallstep

Almost every engineer knows SSH. And almost every team I’ve worked with manages access by copying public keys into servers, forgetting to remove them later, and sometimes sharing access in ways that are… not ideal. It works fine until you have dozens of servers, multiple engineers, short-term access needs, or any real security requirement. At that point, things start to get messy and a bit hard to trust. I looked into tools like Teleport and Smallstep, but they felt too heavy for what I needed in terms of infrastructure, setup, and learning curve. So I built Sshifu . The idea is simple: you run a small server that handles authentication (for example via a GitHub org), it issues short-lived SSH certificates, and users just run a CLI to get access automatically. No more manually managing `authorized_keys` across machines. Quick disclaimer: this is very much a “vibe-coded” project (probably 99%). I built it to scratch my own itch, so it’s still early and a bit rough around the edges. That said, it works well for my use case so far. Would love feedback, especially what’s missing for real-world usage, and what would stop you from using this.

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, user, using · Missing: agents, macos, agent
93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal
27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% 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.

Correct prediction on native model

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