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An Ultimate Guide about SQL Injection for WordPress Users

The Structured Query Language (SQL) is a Relational Database Management System (RDBMS) that is pronounced like the word "sequel." It was the first simple way to store and retrieve many sorts of data on computer systems, and it was invented in 1974. Since then, the language has grown in popularity, and it is still used in many content management systems (CMS) today, such as WordPress.

Deploying a Kong Gateway Data Plane With Pulumi

Infrastructure as code is a core component of all modern SRE team’s day-to-day work. There are plenty of options available, but the one that I’m most excited about is Pulumi. Instead of writing a domain-specific language (DSL) to configure your infrastructure, Pulumi lets you write the language you already know. For me, that’s Typescript, but if you prefer Go, Python or DotNet programming languages, that’s an option too.

Why is Testsigma a perfect solution for automating your cross-browser testing on the cloud?

Today, there are 1.88 billion websites on the internet and the number is rapidly increasing. There are 3.8 billion people in the world that own smartphones today – which amounts to 48.16% of the world population. The internet traffic from mobile (as compared to that from desktops) has also been increasing, and now stands at 56%. The point I am trying to make is that if you have a website – it can be accessed from a web browser or a mobile browser.

Design Environment Challenges: Using PLM for Semiconductors

Following up on an earlier blog post where we discussed what is product lifecycle management for semiconductors, in this blog we will delve deeper into the challenges that PLM presents for a semiconductor design environment. Although PLM tools have seen some success in industries such as defense, automobile, aerospace, and others with large design teams and well-established methodologies, the adoption rate in the semiconductor space has been slow.

That's a Wrap! What You Missed at Kong Summit 2021

So many announcements, so many surprises and a seemingly never-ending list of impactful customer stories! After two and a half days packed with fun and learning, we bid farewell to Kong Summit for another year. If you were one of the almost 5,000 people that registered, you know exactly what we are talking about. Here is a recap of some of the most exciting parts of Kong Summit 2021.

IP Security Vulnerability Detection

The severity and ingenuity of cyberattacks continues to increase as malicious actors become more proficient, breaking through the software layers and aiming to also compromise hardware like integrated circuits. Relative to software, it is much more difficult to patch security vulnerabilities in ICs – making early identification of IP security weaknesses increasingly important.

Of Low-code, Digital Trust, and Staying Ahead of the Risk Curve, Part 2

Business process automation shifted into high gear during the COVID-19 crisis, making technologies such as low-code platforms, AI, and robotic process automation (RPA) critical success factors for any organization in the decade ahead. The same is true for the insurance industry where many companies are leaning into hyperautomation to streamline operations and take friction out of the customer journey as well. But pivoting from paper to digital isn’t easy.

How Xplenty Helps Employers Keep Track of Time

Up to 20% of all employees in the United States are regularly late for work, costing organizations like yours billions of dollars a year. The solution? Timesheets, which monitor employee hours, tardiness, performance, and absenteeism. These documents also collect valuable data for payroll, accounting, billing, and project management. So they're critical for human resource teams everywhere. But there's a problem or two.

Building Machine Learning Pipelines with Real-Time Feature Engineering

Real-time feature engineering is valuable for a variety of use cases, from service personalization to trade optimization to operational efficiency. It can also be helpful for risk mitigation through fraud prediction, by enabling data scientists and ML engineers to harness real-time data, perform complex calculations in real time and make fast decisions based on fresh data, for example to predict credit card fraud before it occurs.