Hobbyist hacker.

Joined June 2016
Free ChatGPT & DeepSeek API keys.
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We're excited to announce the release of Umami v3 for self-hosting! 🚀🎉 Read more about it on our blog, umami.is/blog/umami-v3 GitHub: github.com/umami-software/um…
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UI/UX Designers, this might be the best color generator out there. Website → uicolors.app/create Bookmarks it for later 💜
Issame retweeted
Offensive Development - Implementing Shellcode Retrieval klezvirus.github.io/posts/Of…
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Weaponizing Trust: ClickOnce Deployment with AppDomainManager Injection malcrove.com/weaponizing-tru…
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Open-source AI presentation generator
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HeroUI Native beta 1 is live 🔥 🌀 Fully migrated to Uniwind, boosting performance by up to 250% — everything feels smoother than ever 🎨 Brand-new design system, more beautiful and distinctive 📲 Redesigned Expo app, offering a whole new way to explore components HUGE step forward 🚀
Issame retweeted
Task management layout built with @shadcn GitHub: github.com/ln-dev7/square-ui Design by @_heyrico
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Scans a network and generates an interactive topology visualization
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Scaling LLM-Based Vulnerability Research via Static Analysis and Document Ranking x.com/i/broadcasts/1djxXWZvg…
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we are working on a Rust-based ETL server that can stream your Postgres database to S3/Iceberg (and other databases like BigQuery & ClickHouse) 100% open source, and designed so that it can be embedded in any Rust server
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Microsoft just released a Python framework to light up AI agents! Agent Lightning is an open source framework that lets you train and improve AI agents without rewriting the logic. It works with existing setups like LangChain, AutoGen, or the OpenAI Agents SDK. Agent frameworks could only run agents. They could not learn from experience or feedback. Improving them meant manual prompt tuning or retraining from scratch. Agent Lightning changes that by adding a simple training layer on top of your current agent. You can define reward functions, capture traces of how the agent performs, and use reinforcement learning to make it better over time. Key Features: • Works with existing agent stacks like LangChain and AutoGen • Adds a training loop with minimal code changes • Supports reinforcement learning, prompt tuning, and supervised fine-tuning • Automatically captures prompts, actions, and rewards for training • Lets you define custom reward functions for your use case It is 100% open source.
Issame retweeted
Another Nim C2-Framework developed by @virtualloc. Can't believe you actually wrote the whole client in Nim as well 😂 Nice one! github.com/jakobfriedl/conqu… Including a Blog for parts of it: jakobfriedl.github.io/blog/n…
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1/ Attackers "1 2 punch" to create a 0 click RCE exploit on WhatsApp: 1. OS 0-day RCE in some renderable format: iOS DNG parsing (CVE-2025-43300). 2. WhatsApp vuln to auto render it for preview, as usually files from unknown contacts are not auto-previewed (CVE-2025-55177)
We triggered WhatsApp 0-click on iOS/macOS/iPadOS. CVE-2025-55177 arises from missing validation that the [Redacted] message originates from a linked device, enabling specially crafted DNG parsing that triggers CVE-2025-43300. Analysis of Samsung CVE-2025-21043 is also ongoing.
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Hacking Marine Radar Systems (MRS): Cybersecurity challenges of modern ships. 😈📡၊၊||၊🚢🙈 More details on: LinkedIn: linkedin.com/posts/dlaskov_m… Substack: it4sec.substack.com/p/hackin…
Issame retweeted
How to get Claude code output top-tier UI? 👇 This is my 3-step process to turn Claude code into design mode
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