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When AI Attacks Itself: A Fully Autonomous Red Team vs Blue Team Experiment Date: June 22, 2026 · Environment: Kali Linux VM · Azure OpenAI · Docker Tags: AI Security Penetration Testing AppSec Autonomous Agents GPT-4o gpt-5.2 The Idea I Couldn't Get Out of My Head What if two AI agents fought each other — one building and defending a web application, the other trying to break in? Two different models. No human intervention. No waiting. No typos in ...

I have been building a macOS window manager called SwipeX, and one thing became clear very quickly: moving windows on macOS is much harder than it looks. On the surface, window snapping sounds simple. Pick a target frame, move the window there, resize it, and you are done. In practice, macOS apps do not always behave that way. Some apps have strict minimum sizes. Some have custom title bars. Some expose extra accessibility windows. Finder may resize slowly. Xcode may refuse a requested ...

Working with relational databases often requires breaking down complex problems into manageable parts. Two powerful tools that help achieve this in SQL are subqueries and Common Table Expressions (CTEs). While they may seem similar at first, they serve different purposes and are best used in different scenarios. This article explores what subqueries and CTEs are, their types, use cases, and how they compare in terms of performance and readability. What is a Subquery? A subquery is a q...

Today, June 22, 2026 (wait it's past midnight I mean yesterday), I finally published my first crate to crates.io after over a month of hard work on this tiny idea that just might work: What if you had an in-memory graph database written in Rust, but without enduring the pain of an Arc<Mutex<Box<Rc<RefCell<Weak<RwLock<Cow<Node<T>>>>>>>>> ? What if there was no query language? What if there was only one dependency in cargo.toml , and it wasn...

Quick Answer: Never use floating-point numbers to represent money in software. Because floating-point math cannot perfectly represent base-10 decimals, it introduces microscopic inaccuracies that compound over time. I recommend using either a dedicated arbitrary-precision decimal library or storing currency as integers representing micro-units to guarantee exact calculations. If I ask you how to represent £1.29 in code, your naive first instinct might be to just drop it into a floating-point...

Quick Answer: Code is "correct by coincidence" when it relies on duplicated, fragile details—like matching magic strings—that just happen to align perfectly to make the application work. Code is "correct by design" when you structurally enforce stability, such as centralizing shared values, ensuring the system cannot easily break from simple typos. You can build an application a hundred different ways. From the outside, the users are happy, the behaviors are exactly what the product manager ...

Most chat analyzer apps ask you to export your entire conversation. We thought that was wrong. The real use case is simpler — you have messages you need to understand right now. Texts, DMs, WhatsApp messages, emails. You can paste them, take a picture, or upload a screenshot. TRTH handles all of it. That's why we built TRTH — an app that decodes any message. Within seconds you get an emotional breakdown powered by 23 primary human emotions, giving you specific percentage scores rather than...

AI-assisted coding tools are useful, but one problem keeps showing up in day-to-day development: PRs get bigger than the original task. You ask for one small fix. The AI also refactors nearby code. You ask for one endpoint change. The AI touches routing, tests, config, and documentation. You ask it to handle a review comment. It turns the comment into a broader cleanup. Each change may look reasonable in isolation. The problem is that the PR becomes harder to review, harder to ...

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Article URL: https://openai.com/index/daybreak-securing-the-world/ Comments URL: https://news.ycombinator.com/item?id=48639063 Points: 64 # Comments: 25

Article URL: https://swelljoe.com/post/will-it-mythos/ Comments URL: https://news.ycombinator.com/item?id=48640196 Points: 134 # Comments: 75

This is ymawky, a now-dynamic web server written entirely in ARM64 Assembly. I've previously posted about ymawky here: https://news.ycombinator.com/item?id=48080587 In the past month and a half, I've made some pretty major improvements: I've added CGI scripting support, so the server now supports query strings and dynamic content; and I've fully ported ymawky to run on Linux, rather than macOS-only. In addition to GET/PUT/HEAD/DELETE/OPTIONS requests, because of CGI support ymawky also accepts...

Article URL: https://kreya.app/blog/new-http-query-method-explained/ Comments URL: https://news.ycombinator.com/item?id=48640974 Points: 32 # Comments: 4

After using Claude Code at work for months I wanted to use it on my own projects too. Most probably because my vpn was on I got banned after 1 hour of usage. I got my 120$ back. 1 month later I signed up with vpn off. But this time probably because I used the same credit cart (and that's the only card I can use) they banned me again. Even after I contacted support I got a generic "we have determined that we cannot reinstate your account at this time due to a violation of our Usage Policy" answer...

OpenAI is attempting to tackle the security issues of the open source software community.

A running look — in reverse chronological order — at the bigger tech companies that have announced significant layoffs this year with AI as a stated factor.

I spent the last few months trying to understand why reconciliation errors keep appearing in high-throughput pipelines. Here is what I found. In the race to process millions of transactions daily, modern fintech ecosystems have achieved a genuine miracle of scale. But beneath the surface of that velocity lies a structural problem most engineering teams aren't measuring: causality violations in async event pipelines. Most teams assume that if a transaction shows "Success" in the database, the...

Nine years ago, I built two versions of Highlander: an original jQuery application and a React/Redux version that used the same backend concepts. After successfully reviving and deploying the jQuery version, I turned to Highlander-react-redux. The goal was not simply to make an old repository run again. I wanted to improve the product, modernize its architecture without rewriting everything, and deploy something people could actually explore. This time, I used Turtle AI: a plan-driven enginee...

LinkedIn automation has a trust problem. Not with users — with LinkedIn itself. Most automation tools treat LinkedIn's API like an obstacle to route around. They send at fixed intervals, ignore behavioral limits, and optimize purely for volume. The result: accounts flagged within weeks, connection limits imposed, and in the worst cases — permanent bans. When we built SendCopy.ai, we approached this differently. Here is the technical breakdown of how we built LinkedIn outreach automation that ...

When you work with AI long enough, you start to notice it makes the same kind of mistake over and over. "You're coming on too strong, dial it back." It shrinks and goes meek. "Stop being meek." It comes on strong again. Each time you point something out, it apologizes sincerely. The next round, the same type of problem comes back from a different angle. After a while you realize you're babysitting the AI instead of working with it. This isn't because the AI is bad. It's a design quirk: tod...

I had a long Google AI Studio (Gemini) session that I wanted to keep. I selected the conversation in the browser, copied it, and pasted it into a text file. File size: a few hundred KB. "OK, that's safe." Later, I exported the same session as JSON. File size: a few MB. More than half of the data had silently disappeared. What was missing I checked what the manual copy had dropped. The system prompt The instruction I had originally given the model — the sy...

I kept running eslint and thinking my codebase was fine — then someone opened a PR and the first comment was "this function needs JSDoc." The problem: linters check your syntax . Nobody checks whether your exported API is actually documented. Those are two very different things. So I built jsdocscan — a zero-dependency CLI that walks your JS/TS files and flags every exported function or class that is missing JSDoc, or has undocumented parameters. What it catches Err...

Arize Phoenix is one of the most popular open-source LLM observability platforms in 2026. If you are evaluating it alongside CortexOps, this article compares them directly on the things that matter for production agent workloads. Short version: Arize Phoenix is the right choice if you are doing notebook-based experimentation, RAG evaluation, or need embeddings analysis. It is well-established with 9,000+ GitHub stars and strong OTel support. CortexOps is the right choice if you ne...

Last night I ran external security scans on the public websites of 10 leading Shopify and Shopify Plus agencies — the same scan any browser or attacker would see. No credentials, no special access. One agency scored an A. Three scored C- or below. The most common finding appeared on 9 of 10 sites. TL;DR 1 agency scored an A. 3 scored C- or below. 1 scored a D. The most common finding — missing security headers — appeared on 9 of 10 sites. 6 of 10 agencies have no HSTS at all. ...

Part 6 of a beginner-friendly series on learning Python from scratch. In Part 5 , we learned to organize data with lists, dictionaries, and other collections. Now it's time to organize our code itself. A function is a reusable block of code that performs a specific task. Instead of writing the same code multiple times, you write it once in a function, then call that function whenever you need it. This is the foundation of writing clean, maintainable programs. Defining and C...

VibeThinker: A 3B-Parameter Model Just Beat Opus 4.5 on Reasoning — Here's How A team of researchers has quietly dropped one of the most surprising AI papers of the month. VibeThinker , a model with only 3 billion parameters, reportedly outperforms Anthropic's Opus 4.5 on key reasoning benchmarks — and the secret sauce is a novel training recipe combining Supervised Fine-Tuning (SFT) with Group Relative Policy Optimization (GRPO). For years, the dominant narrative has been that bigger is...