GP

GPG-fingerprint-filter-GPU – Collide GPG key fingerprints, CUDA powered

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GPG-fingerprint-filter-GPU – Collide GPG key fingerprints, CUDA powered

This is a tool to collide OpenPGP / GnuPG key fingerprints that follow specific pattern (e.g. ending with 8 identical digits). CUDA is required to accelerate the computation. Satisfy your vanity by getting a special key :) Initially I wrote this to learn CUDA programming, and partly to show people how easy it is to collide a short key ID - a 8-digit key fingerprint can be collided in a few seconds with my GTX 1650. Recently I found some similar tools on GitHub (keyword: vanity key) but it seems that only mine takes advantage of CUDA / GPU. My friends has used it to generate an ed25519 key that has a fingerprint ending with 16 identical digits. Disclaimer: I'm not sure if fixed fingerprints result in any security implication.

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Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos
57%57% 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
56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% 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
16%16% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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