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XDP firewall that auto-syncs open ports – built after my VPS got DDoS'd

Hacker News

XDP firewall that auto-syncs open ports – built after my VPS got DDoS'd

A few days ago, someone decided to DDoS the entire IP range of my Hong Kong VPS provider. fail2ban did its job a little too enthusiastically — banned 20,000+ IPs, ran the machine out of memory, and triggered a kernel panic. Great. :/ That's when I realized the problem: fail2ban lets packets hit the kernel stack first, then reacts. Under a real flood, that reaction cost alone is enough to kill the machine. I went down the XDP/eBPF rabbit hole — packets get dropped at the NIC driver level, before they even touch the kernel. The other thing that annoyed me was manually managing port rules, so I built a daemon that watches for new listening ports via Netlink Process Connector and updates the BPF whitelist automatically. What it does: ~34–65 ns/packet drop on KVM VPS, auto-syncs open ports, handles IPv6 extension headers, one-liner install. What it won't do: won't save you if your uplink is already saturated — not a replacement for upstream scrubbing. Would love feedback, especially if something breaks on your setup. First time posting here — hello everyone!

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
88%88% 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, new, open · Missing: agents, macos, agent
79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released
46%46% 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 · Missing: plus, platform, intuitive
38%38% 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
34%34% 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
19%19% 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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