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Reporter: Pauline Caballero 1. Top 10 Trends in Software Development Software development is constantly changing, with new trends and technologies emerging every year. Here are some of the top 10 trends that are shaping the software development industry in 2020: • Artificial Intelligence: Artificial intelligence (AI) is becoming increasingly important in the software development process. AI-driven software can help automate processes, detect patterns, and provide insights into data. • Microservices Architecture: Microservices architecture is a way of developing software that focuses on breaking down applications into small, independent services. This allows for easier scalability and quicker development times. • Cloud Computing: Cloud computing is becoming increasingly popular in software development, as it allows applications to be hosted in remote servers and accessed from anywhere. • Containers: Containers are a way of packaging applications so that they can run in any environment without needing to be re-configured. This makes deployment easier and faster. • Serverless Computing: Serverless computing is a way of running applications without the need for a dedicated server. This can help reduce costs and increase scalability. • DevOps: DevOps is an approach to software
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WinRAR CVE-2025-8088: RomCom’s Doorway to Remote Code Execution - SecPod Blog
Executive Summary A critical vulnerability in WinRAR, identified as CVE-2025-8088, was exploited as a zero-day in targeted phishing attacks to deploy RomCom backdoors. This flaw, a directory traversal vulnerability, allows attackers to craft malicious archives that place executable files in Windo
15000 Jenkins Servers Exposed to Unauthenticated RCE Attack - SecPod Blog
A recently identified command injection vulnerability, CVE-2025-53652, in the Jenkins Git Parameter plugin puts approximately 15,000 Jenkins servers at risk of remote code execution (RCE). This flaw could allow attackers to compromise unauthenticated Jenkins servers, potentially leading to significa
Puppo, The Corgi: Cuteness overload with the Unity ML-Agents Toolkit
Building a game is a creative process that involves many challenging steps including defining the game concept and logic, building assets and animations, specifying NPC behaviors, tuning difficulty and balance and, finally, testing the game with real players before launch. We believe machine learning can be used across the entire creative process and in today’s blog post we will focus on one of these challenges: specifying the behavior of an NPC. Traditionally, the behavior of an NPC is hard-coded using scripting and behavior trees. These (typically long) lists of rules process information about the surroundings of the NPC (called observations) to dictate its next action. These rules can be time-consuming to write and maintain as the game evolves. Reinforcement learning provides a promising, alternative framework for defining the behavior of an NPC. More specifically, instead of defining the observation to action mapping by hand, you can simply train your NPC by providing it with rewards when it achieves the desired goal.