Stormberry

Smarter sales. Global culture. AI-driven strategy. Visit us at: stormberry.as stormberryr7fz5xdopi7f265d7id27bgizc6uxeliaepzstompcfpyd.onion

Published Apps

SunApp SunApp calculates sunrise, solar noon and sunset for any location on Earth, handles the timezone properly, and says plainly when the sun does not rise or set at all. It can also wake you by the sun rather than by the clock. Set an alarm for six hours before solar noon, or eight hours after sunrise, and it recomputes every day as the seasons move. When you build a rule it shows you the next thirty days of fire times, so a rule that drifts to the afternoon in December is visible when you set it rather than discovered in November. During polar night it falls back to solar noon and tells you why. It never touches the network. There is no INTERNET permission, so it cannot, and there is no location permission either: coordinates come from a bundled catalogue of 25,007 cities or from numbers you type. Check for yourself: aapt dump permissions SunApp-v1.1.0.apk The nine permissions you will see are for the alarm feature and are documented one sentence each in the repository README. Sun times need none of them, and no dialog appears until you create your first alarm. Search 25,007 cities, accent-insensitive in both directions: "tromso" finds Tromso with the slash, "Herat" finds the one with the macron. English exonyms work too, so "Gothenburg" finds Goteborg and "Cologne" finds Koln. Every city carries its own IANA timezone. Times render in the place's zone, not your phone's. Any date, past or future. Midnight Sun and Polar Night are detected geometrically and labelled, not shown as a blank or an error. The same maths and the same catalogue run on the web at sun.stormberry.as, and the Kotlin port is tested against a golden corpus generated from the JavaScript one, so the two cannot silently disagree about when the sun comes up. Built by Stormberry AS in Askoy, Norway, where the gap between a December sunrise and a June one is nine and a half hours and the question stops being academic.
UsernameGenerator UsernameGenerator builds memorable usernames from curated word lists in 11 languages: English, Norsk, Português, Español, Deutsch, Français, Italiano, Nederlands, Polski, Română and Latina. Every list was reviewed by a native speaker of that language. It declares no Android permissions at all. Not "only the clipboard": genuinely none. Everything runs on word lists compiled into the APK, so there is no network access, no storage access and nothing to phone home with. Check it yourself before installing: aapt dump permissions UsernameGenerator-v1.1.0.apk The only line you should see is the package name. It also shows you what your settings are actually worth, as you change them: 44.6 bits of entropy 1 in 27 trillion combinations Even odds of a repeat after 6.1 million names Those are two different questions and the second is the one people guess wrong. Two words with no digits is 90,000 combinations but a coin-flip repeat after just 353 names. One word repeats after about twenty people. 1 to 5 words: mixed, or adjectives / nouns / verbs only. Digits: on by default, before or after each word, one to five per word. Each word gets its own independently drawn run. Languages: pick one, or let it draw one at random for the whole name, or mix every word from the pooled vocabulary of all eleven. Separators: none, hyphen, underscore, full stop, one drawn at random for the whole name, or a different one in every gap. No word ever appears twice in the same name. Accents are stripped after generation, so "condução" becomes "conducao" and the result is accepted everywhere. Randomness comes from SecureRandom, not a predictable PRNG. People generate usernames to keep identities apart, and that only works if the next one is not guessable from the last. Recent generations are kept in memory for the session and never written to disk. A saved list of the identities you generated is exactly the file you would not want on the device. A note on the entropy figures, since most apps quote the flattering number: the guessing figure uses min-entropy, the worst case, and the repeat figure uses collision entropy, because that is what actually governs how soon two people collide. Mixing languages is worth less than it looks, because the word lists overlap: "ninja" appears in nine of the eleven. The app measures what mixing is really worth rather than assuming. The same engine also runs on the web at username.stormberry.as and as a Python CLI in the repository. All three are pinned to a shared corpus of 4,684 expectations, so they cannot silently disagree.

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