My friend stole my data – now I have a small side hustle

Hacker News

Hello everyone Short story: My now former colleague got access to my computer while he lived in my apartment. The damage was not so big, an order of 120$ in an online shop. It could have been worse. "The past has shown time and again that the damage is often done by those closest to you. Ancient Rome is an example of this." The biggest problem was that I had not noticed it for a long time. For this reason, I have created a simple and cheap honeypot that you can spread out on your computer or print out. It takes the person to an attractive honeypot website with a login. After that you get notified per email that someone logged in. The page exists for 1 year, but I have redesigned it. What do you think about the page? [Demo] www.loginbait.com

Visit product View on Hacker NewsFeb 9, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

77%77% 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: computer, email · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, ide · Missing: https docs, excited, just released

37%37% 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 · Missing: mobile apps, ios, personal

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

15%15% 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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