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Helium Browser for Android with extensions support, based on Vanadium

Hacker News

Helium Browser for Android with extensions support, based on Vanadium

Been working on an experimental Chromium-based browser that brings 2 major features to your phone/tablet: 1. desktop-style extensions: natively install any extensions (like uBO) from the chrome web store, just toggle "desktop site" in the menu first. 2. privacy/security hardening: applies the full patch sets from Vanadium (with Helium's currently wip). Means you get both browsers' excellent privacy features, like Vanadium's webrtc IP policy option that protects your real IP by default, and security improvements such as JIT being disabled by default, all while being a reasonably efficient FOSS app that can be installed on any (modern) android. It's still in beta, and as I note in the README, it's not a replacement for the full OS-level security model you'd get from running the GrapheneOS Vanadium combo. However, goal was to combine privacy of Vanadium with the power of desktop extensions and Helium features, and make it accessible to a wider audience. (Passkeys from Bitwarden Mobile should also work straight away once merged in the list of FIDO2 privileged browsers) Build scripts are in the repo if you want to compile it yourself. You can find pre-built releases there too. Would love any feedback/support!

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Product HuntOn track for Day 1 leaderboard · Strong signals: model · 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
70%70% predicted probability of success on Indie Hackers, 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
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: efficient · Missing: plus, platform, intuitive
54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · 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 · 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.

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