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Supernetworks' Secure Programmable Router

Hacker News

Supernetworks' Secure Programmable Router

Hey HN, We recently saw that a bad router update made it to the front page, and thought you might like to hear about what we're building at Supernetworks. Our flagship product is a Secure Programmable Router (SPR), which is Linux-based software for running a hardened wifi network that enables easy addition and management of devices. SPR isolates each device into an individual VLAN and securely connects it to the rest of the network. What sets SPR apart is that we've engineered it to use the latest and greatest networking capabilities of Linux, all while employing best-in-class security practices and modern coding standards. SPR is designed to run in docker containers on systems with a bit more memory and storage, which opens up possibilities like hosting voice assistants, security testing tools, and media servers. We have built SPR mostly with golang and a react frontend, championing these languages especially for their robust security and memory-safety. Here's an overview of its key features: - Device Isolation: SPR ensures each WiFi device has its own VLAN and subnet. This makes network attacks like ARP/MAC spoofing a non-issue and protects devices from traffic sniffing. Notably, SPR was not affected by the MACStealer flaws [1] - Per-device passwords. The passphrase and MAC address combine to give each device a unique identity in the network. No custom code is required on clients and a wide variety of IOT devices are compatible. By the way, we do support WPA3 with multi-psk, and we were the first and might still be the only one that supports this. - Groups and Tags: Assign devices to groups to control their network access. Apply tags for special features and further organization - Privacy Preserved: Your data is only your data. SPR doesn’t send any telemetry or statistics to Supernetworks or any third party (beyond what Github might collect when downloading our containers and code). You can verify this by checking the code in our GitHub repo or inspecting the network traffic from SPR. Part of our product's motivation is to provide better capabilities to block telemetry going to all sorts of parties, using DNS block lists and firewall rules. - Extensible: SPR supports plugins running as docker containers, allowing a multitude of ways for customization and enhancement. It also has an API for programming the router directly. - Wireguard: SPR can run as a VPN host as well, and can be hosted as a router in the cloud or locally without WiFi for this purpose. Some more useful links for the project: Our Github page: http://github.com/spr-networks/super FAQ: https://www.supernetworks.org/pages/docs/faq Find us on Twitter: https://twitter.com/spr_networks Demo page: https://demo.supernetworks.org/ Join the Discord chat: https://discord.gg/EUjTKJPPAX Our API Docs: https://www.supernetworks.org/pages/api/0 Documentation Home: https://www.supernetworks.org/pages/docs/intro/ Raspberry Pi 4 Setup: https://www.supernetworks.org/pages/docs/pi4b General Setup Guide: https://www.supernetworks.org/pages/docs/setup_run_spr Check us out at https://www.supernetworks.org and let us know what you think! We’re open to feedback, suggestions, feature requests, and questions. Thank you! [1] https://news.ycombinator.com/item?id=35582798

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports, vpn, compatible · Missing: reddit linkedin, podcasting, created
93%93% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, dock, new · Missing: agents, macos, agent
86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
68%68% 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: host · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
35%35% 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
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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