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We've all seen password strength meters on sign-up forms. Most of them rely on simplistic, static rules: "Must contain at least 8 characters, one number, and one special character." But from a mathematical standpoint, these rules are a poor proxy for actual password security. A password like Tr0ub4dor&3 conforms to these rules but is far easier to compromise than a randomly generated four-word passphrase like correct-horse-battery-staple . To truly measure password security, we have to look at information theory and compute its Shannon Entropy . Here is how password entropy works, the math behind it, and how you can calculate it directly in the browser with 100% client-side privacy. What is Password Entropy? In cryptography, entropy is a measure of the unpredictability or randomness of a password. It is expressed in bits . An entropy of $N$ bits means there are $2^N$ possible combinations that an attacker would have to guess in a worst-case brute-force search. < 28 bits: Very weak (easily guessed in milliseconds). 28 to 35 bits: Weak (cracked in minutes or hours). 36 to 59 bits: Reasonable protection (days to months). 60 to 127 bits: Very strong (takes years to decades to crack). 128+ bits: Extremely secure (mathematically unfeasible to crack). The Mathematical Formula To calculate the entropy ($E$) of a password, we use the following equation: $$E = L \times \log_2(R)$$ Where: $L$ is the length of the password (number of characters). $R$ is the size of the pool of unique characters from which the password is drawn. $\log_2(R)$ is the binary logarithm of the pool size, representing the amount of information carried by each character. Determining Pool Size ($R$) To find $R$, we analyze which character sets are present in the password string: Lowercase letters ( a-z ): 26 characters Uppercase letters ( A-Z ): 26 characters Numbers ( 0-9 ): 10 characters Common special characters/punctuation: 33 characters (e.g., !@#$%^&*()-_=+[]{}|;:',.<>/? etc.) If a password uses ch

MarkDown - что это? [[Markdown]] — это язык разметки, с упрощенным до человекочитаемости синтаксисом. Markdown — создан Джоном Грубером ( John Gruber ) в 2004 году. Markdown — это фактически "микро" язык для трансляции "текста markdown"в подмножество языка XHTML. Markdown - итоговая презентация текста всегда документ HTML , и только потом если нужно следующим шагом PDF, др. стандарты документации. Markdown принципиально не может задействовать весь потенциал XHTML, результатом его работы всегда является ограниченный набор элементов. Markdown — это транслятор который при анализе интегрированного в "текст" markdown HTML/XHTML кода обязан по стандарту просто его транслировать в итоговый образ документа. Markdown — это, если цитировать автора > «Markdown — это инструмент преобразования текста в HTML для веб-писателей. Markdown позволяет писать в легко читаемом и удобном для написания текстовом формате, а затем преобразовывать его в структурно корректный HTML. ║ John Gruber » Примечание Термин транслятор , не обходимо понимать как сущность алгоритм Я не нашел программу реализующая концепт MarkDown по принципам John Gruber. Ни одна программа не умеет делать из Markdown валидный по John Gruber HTML. Все проверенные мною программы Obsidian, MarkText, Typora, на выходе из 10 строк генерируют портянку HTML в несколько тысяч строк!!! Причина Obsidian, Typora и MarkText используют Markdown не для веб-писателей и блогеров, а как формат хранения баз знаний (Knowledge Management)**. John Gruber - Wikipedia

Every junior developer or solo software engineer falls into the exact same engineering trap: They conflate writing code with building a business. They spend their initial excitement phase setting up intricate user database authentication schemas, writing custom cron jobs for automated subscription reminders, or building heavy background pipelines just to resize a user’s uploaded logo image. By the time their local environment is "infrastructure perfect," weeks have passed. The momentum is gone, burnout sets in, and the repository is abandoned before ever tasting real production traffic. In 2026, computing power has completely shifted to specialized edge layers. Infrastructure has become commoditized. If you are wasting creative bandwidth trying to compete on backend pipelines instead of focusing entirely on your unique value proposition, you are systematically killing your startup. Here is the architectural matrix to decouple your operational infrastructure and shift to a lean, hyper-scalable API-first codebase. Part 1: The Production Infrastructure Decoupling Layer The golden rule of modern systems design is clear: Your application should only maintain two core pillars internally—your proprietary business logic and your core user state database. Everything else—from security to user tracking—is a solved problem that should be offloaded to third-party micro-services. Let’s look at the financial and time trade-offs of building versus outsourcing across critical technical vectors: Microservice Vector The Native Way (High Friction) The 2026 API Standard Launch Velocity Impact Merchant of Record Raw Stripe API + Custom Tax Calculators Lemon Squeezy / Paddle Saves 5 days of legal & accounting setup Feature Rollouts Custom Postgres feature-flag logic loops GrowthBook / LaunchDarkly Zero deployment overhead for major pivots Customer Feedback Manual tables + Admin CRUD boards Featurebase API Instant roadmaps directly inside frontend Media Compression AWS S3 triggers + Edge

The crust expands at mid-ocean rifts. But how?

Political operatives in Trumpworld hope that US Senate candidate Graham Platner stays in the race as long as possible.

What if you had a drone that wasn't a buzzy, annoying fly people wanted to swat - but rather a cute dog that runs and jumps? What if it could do tricks on command, and film your tricks as well? What if it could get right back up after a nasty-looking crash, dozens of times […]

Vermilion Cliffs Ventures announced Wednesday the close of a $25 million Fund II.

We’re excited to announce our first ever Summer Bug Smash! Every app has its share of rockstar bugs....

Hi guys, I've been using Claude Code for almost everything lately. Have given one an email account so it can research business leads, draft emails, fact-check them and clear them with me before sending (works really well by the way). I also tend to have a few Claude Code agents running at any one time for coding. I used to create a split terminal to manage them from there, but found working in the terminal all day pretty depressing and, more importantly, found it hard to follow Claude Code's pro

It’s not a great time to shop for a gaming laptop. The unprecedented rise in cost for RAM (and storage to a slightly lesser extent) has made laptops with low-to-midrange specs cost much more than they should. Recent deals on gaming laptops worth your attention have been uninspiring, but one recently caught my eye: MSI’s […]

Apple has signed a $30 billion+ multiyear deal with Broadcom to design and produce more than 15 billion U.S.-made custom wireless connectivity chips for Apple products.

Airbnb engineers detailed Sitar-agent, a Kubernetes sidecar for dynamic configuration delivery across tens of thousands of pods, processing updates several times per minute. The system was redesigned with Java, Amazon S3 snapshot bootstrapping, and a migration from Sparkey to SQLite to improve reliability, startup performance, and configuration availability at scale. By Leela Kumili

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