A walkthrough of prompt injection attacks against OopsSec Store's AI assistant, bypassing its input filters to extract a flag from the system prompt. OopsSec Store has an AI support assistant with a secret embedded in its system prompt. The only thing standing between us and the flag is a regex blocklist. Spoiler: four regexes are not enough. Initialize the OopsSec Store application: npx create-os
I have a confession. For years, when a developer proudly showed me their Python app — gray square buttons, a Listbox straight out of 1998 — I would politely nod. I've stopped doing that. Not because I turned mean. Because PyQt6 exists, and there's no excuse anymore. This article is my attempt to convince you — yes, you, the one still typing import tkinter out of habit — that something radically be
TL;DR — One API call subscribes a customer endpoint. Centrali signs each delivery with HMAC-SHA256, retries 5 times over ~40 minutes on failure, logs every attempt, and exposes a one-line replay endpoint. No queue. No retry logic. No Svix. The whole subscribe call is right below — scroll to it if you just want the shape. Your customers want webhooks. You know the checklist: A queue so user request
J'ai un aveu à faire : pendant longtemps, quand un dev me montrait fièrement son app Python avec un bouton gris carré et une Listbox qui sentait Windows 95, je hochais la tête poliment. Aujourd'hui, j'ai arrêté. Pas parce que je suis devenu méchant. Parce que PyQt6 existe, et qu'il n'y a plus aucune excuse. Cet article, c'est ma tentative de te convaincre — toi qui ouvres encore tkinter par réflex
You don’t notice the problem right away. Everything runs smoothly in MySQL… until a new report shows up. Then queries slow down, dashboards lag, and you start realizing you’re stretching the database beyond what it’s good at. That’s usually when BigQuery enters the picture. So the real question becomes: How do you actually move data between them without turning it into a side project? Let’s w
The Challenge: Beyond the "Lift and Shift" Fatigue The real fear isn’t migration itself—it’s operational fragmentation: different tools, different processes, and different failure modes between the data center and the cloud. After deep-diving into the Nutanix ecosystem, I realized that the goal shouldn't be just moving VMs, but achieving operational symmetry. This is where Nutanix Cloud Clusters
Originally published at https://allcoderthings.com/en/article/csharp-collections-list-dictionary-queue-stack In C#, collections are used to store multiple values dynamically and process them efficiently. Arrays have fixed size, but collections can grow and shrink as needed. This article covers List<T>, Dictionary<TKey,TValue> (and KeyValuePair<,>), SortedList<TKey,TValue>, Queue<T>, Stack<T>, Hash
Cuando una aplicación necesita leer un archivo, escribir en una conexión TCP o esperar datos de un disco, el kernel de Linux ofrece tradicionalmente dos caminos: bloquear el proceso hasta que la operación termine, o usar interfaces como epoll y Linux AIO para manejar múltiples operaciones concurrentes. Durante casi tres décadas, esas fueron las opciones dominantes. Pero desde la versión 5.1 del ke