Observable Notebooks Data Loaders
https://observablehq.com/notebook-kit/data-loaders
#HackerNews #Observable #Notebooks #Data #Loaders #DataVisualization #DataScience #JavaScript #Notebooks #Programming
Observable Notebooks Data Loaders
https://observablehq.com/notebook-kit/data-loaders
#HackerNews #Observable #Notebooks #Data #Loaders #DataVisualization #DataScience #JavaScript #Notebooks #Programming
(Feels good to close two-year-old feature requests.) :)
https://codeberg.org/kitten/app/issues/25
https://codeberg.org/kitten/app/issues/26
💕
#Kitten #SmallWeb #web #dev #html #css #JavaScript #ESM #loaders #NodeJS
Currently, the only way to include HTML is to wrap it in an ``` html`…` ``` template tag in a JavaScript file (.component, .fragment). But you might want to include some static HTML in an .html file: ```js import someStaticHtml from './static.html' ``` This loader will load th...
We have released a new CppCon 2023 Video!
Linkers, Loaders and Shared Libraries in Windows, Linux, and C++ – Ofek Shilon – CppCon 2023
https://youtu.be/_enXuIxuNV4
#Binaries #cpp #Libraries #linkers #LinuxUnix #loaders #Windows
▪️◾️◼️◾️▪️ CSS loaders
by T. Afif @ChallengesCss
The Biggest Collection of Loading Animations
Over 500+ CSS-only loaders made using a single element
#loaders #css #webdev #LoadersLibrary
Y. Zhu et al., "Devils in the Clouds: An Evolutionary Study of Telnet Bot Loaders"¹
One of the innovations brought by Mirai and its derived malware is the adoption of self-contained loaders for infecting IoT devices and recruiting them in botnets. Functionally decoupled from other botnet components and not embedded in the payload, loaders cannot be analysed using conventional approaches that rely on honeypots for capturing samples. Different approaches are necessary for studying the loaders evolution and defining a genealogy. To address the insufficient knowledge about loaders' lineage in existing studies, in this paper, we propose a semantic-aware method to measure, categorize, and compare different loader servers, with the goal of highlighting their evolution, independent from the payload evolution. Leveraging behavior-based metrics, we cluster the discovered loaders and define eight families to determine the genealogy and draw a homology map. Our study shows that the source code of Mirai is evolving and spawning new botnets with new capabilities, both on the client side and the server side. In turn, shedding light on the infection loaders can help the cybersecurity community to improve detection and prevention tools.
#arXiv #ResearchPapers #Mirai #Botnets #Loaders
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¹ https://arxiv.org/abs/2211.14790
One of the innovations brought by Mirai and its derived malware is the adoption of self-contained loaders for infecting IoT devices and recruiting them in botnets. Functionally decoupled from other botnet components and not embedded in the payload, loaders cannot be analysed using conventional approaches that rely on honeypots for capturing samples. Different approaches are necessary for studying the loaders evolution and defining a genealogy. To address the insufficient knowledge about loaders' lineage in existing studies, in this paper, we propose a semantic-aware method to measure, categorize, and compare different loader servers, with the goal of highlighting their evolution, independent from the payload evolution. Leveraging behavior-based metrics, we cluster the discovered loaders and define eight families to determine the genealogy and draw a homology map. Our study shows that the source code of Mirai is evolving and spawning new botnets with new capabilities, both on the client side and the server side. In turn, shedding light on the infection loaders can help the cybersecurity community to improve detection and prevention tools.