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Argus: A Python-based toolkit for Information Gathering & Reconnaissance #OSINT GitHub: "Argus is an all-in-one, Python-powered toolkit designed to streamline the process of information gathering and reconnaissance. It brings together a clean, intuitive interface and a wide range of reliable modules, allowing analysts to efficiently assess networks, web applications,... show more

Dark Web Informer

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I’m excited to introduce MASTER OSINT v2, a powerful Python toolkit for cybersecurity enthusiasts and investigators. This updated version includes 12 modules that streamline the collection and analysis of open-source intelligence. #OSINT #Cybersecurity

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New to OSINT and not sure where to start? The OSINT Investigator’s Toolkit is a searchable directory of free and paid OSINT tools Perfect for beginners and for discovering the core staples Simple, practical, and very handy

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I am happy to present to you all MASTER OSINT v3.0. The tool has been well refined, with precise results output and a user-friendly interface with a colorful outlook. - Section one: Scan Ops - Section Two: Track and Exploit #OSINT #Cybersecurity #InfoSec #Python

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D4rk_Intel

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Sahil Bloom explains why Type B people are BETTER as entrepreneurs “Type B people would thrive more as an entrepreneur. " "The risk with Type A people as entrepreneurs is that you're so organized, you're such a good planner, you're a perfectionist, and you never do anything. Right? It's like the trap of information gathering. Like, dopamine from information gathering is a dangerous drug. " "And Type A people, because they're perfectionists, tend to have a big gap. You like sit gathering all this information for a long period of time, you're like stewing on it, planning all of these things, where someone that's just willing to go out and test it, and figure it out, screw it up, and adjust, adapt, they're going to be more successful in the long run."

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The Iced Coffee Hour

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GLM 4.6 in Claude Code to build a python app Took me around 3 mins to make this python app with a Streamlit web ui and llamacpp python bindings The app lets you run an inference via a simple chat interface plus configurable params 👇 (video 4x speed)

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RustGIS is now on PyPI: pip install rustgis RustGIS is a fast, free and open-source GIS in pure Rust for mapping, analyzing and sharing geospatial data. It runs natively on Windows, macOS and Linux, and in your web browser. Your data stays on your machine unless you send it to an AI model you choose, and every action is a command you can script. The new rustgis Python package brings the RustGIS engine into Python and the full RustGIS app into your Jupyter notebook, with no server to run and nothing else to install. What you can do - The engine in-process: open the same data the app opens, run any of RustGIS's commands and geoprocessing tools, style layers and render maps, all from Python. - GeoPandas in and out: turn any layer into a GeoDataFrame, or add a GeoDataFrame as a layer. - The whole app in a notebook cell: shows the ribbon, panes and map right below your code. - Two-way sync: what Python adds or styles appears in the app, and what you pan, edit or add in the app comes back to Python. - Projects that travel: save a .rgis project from Python and open it as it is in the desktop app or the web app. - Runs where you work: JupyterLab, Jupyter Notebook, VS Code and Google Colab, with prebuilt wheels for Windows, macOS and Linux. Get started in three lines: import rustgis m = m Try it out - Open the getting-started notebook in Colab: - PyPI: - Python guide: - Launch the web app: - GitHub: #GIS #Rust #Python #Jupyter #OpenSource #Geospatial

RustGIS is now on PyPI: pip install rustgis RustGIS is a fast, free and open-source GIS in pure Rust for mapping, analyzing and sharing geospatial data. It runs natively on Windows, macOS and Linux, and in your web browser. Your data stays on your machine unless you send it to an AI model you choose, and every action is a command you can script. The new rustgis Python package brings the RustGIS engine into Python and the full RustGIS app into your Jupyter notebook, with no server to run and nothing else to install. What you can do - The engine in-process: open the same data the app opens, run any of RustGIS's commands and geoprocessing tools, style layers and render maps, all from Python. - GeoPandas in and out: turn any layer into a GeoDataFrame, or add a GeoDataFrame as a layer. - The whole app in a notebook cell: shows the ribbon, panes and map right below your code. - Two-way sync: what Python adds or styles appears in the app, and what you pan, edit or add in the app comes back to Python. - Projects that travel: save a .rgis project from Python and open it as it is in the desktop app or the web app. - Runs where you work: JupyterLab, Jupyter Notebook, VS Code and Google Colab, with prebuilt wheels for Windows, macOS and Linux. Get started in three lines: import rustgis m = m Try it out - Open the getting-started notebook in Colab: - PyPI: - Python guide: - Launch the web app: - GitHub: #GIS #Rust #Python #Jupyter #OpenSource #Geospatial

Qiusheng Wu

13,435 views • 6 days ago

THIS IS F**KING DANGEROUS SOME COMPANIES ARE LEAVING WAY TOO MUCH EXPOSED I found 3 OSINT tools that can uncover a ridiculous amount of information from the outside. LEAKIX -> Give it a domain and it can surface publicly exposed services and databases connected to that infrastructure. ARGUS -> Runs 135+ recon and security checks against a website to build a much broader picture of its external footprint. GITGRABER -> Monitors GitHub for accidentally exposed secrets like API keys, passwords, and sensitive information —> with Telegram alerts when something is found. Different tools. Same idea: find what shouldn’t be publicly visible. If you’re learning OSINT, bug bounty, or pentesting, these are worth knowing. BOOKMARK it before someone take it down LINK’S BELOW

THIS IS F**KING DANGEROUS SOME COMPANIES ARE LEAVING WAY TOO MUCH EXPOSED I found 3 OSINT tools that can uncover a ridiculous amount of information from the outside. LEAKIX -> Give it a domain and it can surface publicly exposed services and databases connected to that infrastructure. ARGUS -> Runs 135+ recon and security checks against a website to build a much broader picture of its external footprint. GITGRABER -> Monitors GitHub for accidentally exposed secrets like API keys, passwords, and sensitive information —> with Telegram alerts when something is found. Different tools. Same idea: find what shouldn’t be publicly visible. If you’re learning OSINT, bug bounty, or pentesting, these are worth knowing. BOOKMARK it before someone take it down LINK’S BELOW

MAX

247,581 views • 1 month ago

🚨 THIS IS ACTUALLY INSANE Python developers are still installing five different tools to manage one project. `pip` for packages. `virtualenv` for environments. `pyenv` for Python versions. `pipx` for CLI tools. `poetry` for project management. uv replaces all of them with one tool. And it’s written in Rust. The headline number: 10–100× faster than pip. But speed isn't even the most interesting part. uv can: → Create and manage Python projects → Resolve dependencies with a universal lockfile → Create virtual environments → Install and switch between Python versions → Run standalone Python scripts with dependencies → Install CLI tools with `uvx` → Compile and sync requirements → Manage Cargo-style workspaces The workflow becomes ridiculously simple: `uv init` → create a project `uv add` → add dependencies `uv run` → run your code `uv lock` → lock dependencies `uv sync` → reproduce the environment And if you're already using pip? You don't have to throw your workflow away. The `uv pip` interface is designed as a drop-in replacement while giving you the speed boost. The other clever bit: uv uses a global cache to deduplicate dependencies and save disk space. So instead of assembling a Python toolchain piece by piece, you get one fast CLI that covers the whole workflow. And unlike a lot of newer developer tools, uv is already considered stable and production-ready. If you work with Python, this is one of those tools you should probably try once. You might not go back. #Python #DevTools #Rust #OpenSource #Programming #AIEngineering

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Y Combinator

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USA-229 is a pair of Naval Ocean Surveillance Satellites (NOSS) in control of the US Navy. Their systems are classified but their purpose is to track boats and airplanes. The satellites were launched in 2011. BAE Systems was awarded a $50 million contract in 2010 to develop Argus-IR. Testing was spring 2012 consistent with the satellite launch having the Argus payload. "ARGUS-IR further expands military capability by providing 24-hour, day-night reconnaissance and surveillance capabilities over a much wider area than previously possible," said Dr. John Antoniades "ARGUS-IR will provide at least 130 independently steerable video streams to enable real-time tracking of individual targets throughout the field of view." This is the real location of USA-229 on March 7th, 2014 and that bubble is the coordinates of the satellite video. USA-229 relays to NROL-22, which beams the data to ground based computers to produce the fully interactive video. Ladies and gentlemen, we f'ing got them.

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Ashton Forbes

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🚀 Excited to announce the publication of our latest paper in the Journal of Open Source Software! 🎉 bingqing liu 📖 Title: HyperCoast: A Python Package for Visualizing and Analyzing Hyperspectral Data in Coastal Environments 🔗 GitHub: 🌐 Website: 📄 Paper: #Geospatial #OpenSource #DataViz #Python

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#DarkCrawler I'm happy to launch version 2.4 of DarkCrawler - a python-based tool that provides comprehensive dark web crawling capabilities with integrated threat detection, marketplace analysis, images extraction, and professional reporting features. #OSINT #Cybersecurity

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