Run a local LLM to analyse email for threats

Hacker News

After seeing sophisticated phishing attempts slip through Gmail's filters, a friend and I built a browser extension that uses local AI to analyse emails for threats. It runs entirely in your browser using web-llm, with any threat being clearly labelled with an explanation of why it's suspicious. Still early days, but we'd love feedback from the HN community. Even if you're not comfortable installing it yet, we have screenshots showing how it works. https://www.eguard.app https://chromewebstore.google.com/detail/eguard/dnpofinmilhb...

Visit product View on Hacker NewsSep 23, 2025

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Launch Intel predictions

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

81%81% 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

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal

48%48% 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

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: 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.

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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