Defendera – Chrome extension protecting from scams

Hacker News

Hey HN! I'd like to show you Defendera - a Chrome extension (other extensions are planned) which checks any visited website for scams and threats. The detection includes all kinds of (secret) automation, AI detection of suspicious patterns, and even a manual review from an on-call person when needed. Defendera cannot use any personal data, because it doesn't collect or save any information about your browsing activity, while still reviewing it all for your safety. While the scammer can catch off guard anyone, the most vulnerable are less technical people still spending time online - like parents or grandparents. Defendera is designed to make the setup trivial - send a sign-in link and Defendera guides you through the rest. Any feedback will be greatly appreciated!

Visit product View on Hacker NewsAug 14, 2023

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: activity · Missing: mac, agents, macos

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

43%43% 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 · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

42%42% 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

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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