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Enigma Machine and Bombe Implemented in eBPF – Turing's 113th Birthday

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Enigma Machine and Bombe Implemented in eBPF – Turing's 113th Birthday

I implemented the Enigma encryption machine and Bombe decryption device in eBPF to honor Alan Turing's legacy. This project uses eBPF to process network packets through virtual Enigma rotors and reflectors, just like the original WWII-era machines. Messages sent through virtual interfaces are not only encrypted but also decrypted in real-time, demonstrating how Turing's pioneering work can be reimagined with modern systems programming. The implementation includes configurable rotors, reflectors, and position settings.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac · Missing: agents, macos, agent
42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% 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
7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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