BrowserTotal – Free, real-time AI scanner for browser extensions

Hacker News

Live extension analysis: Point us at a Chrome/Edge/Firefox extension (store URL or CRX). We spin up a safe sandbox and observe it in real time—permissions use, message passing, storage writes, network calls, remote code loading, and UI injections. Package scanning: Paste an npm/package URL or code. We do quick static + dynamic checks: install/postinstall scripts, obfuscation/eval, exfil endpoints, suspicious APIs, and typosquat/reputation signals. AI explainer: An LLM summarizes the behaviors and risk patterns in plain English (why it’s risky, what to verify, how to mitigate), and produces a shareable report.

Visit product View on Hacker NewsAug 29, 2025

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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: code, apis, plain · Missing: mac, agents, macos

68%68% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

47%47% 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: io · Missing: https docs, excited, just released

47%47% 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: scanner · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% 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

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: real time · Missing: web3, chat, crypto

13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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