Nowadays, we do virtually everything online: book flights, pay for goods, transfer bank funds, message friends, store documents, and so on. Many things we do require giving out sensitive information like our credit card details and banking information. If a website uses an unsecured network, a malicious hacker can easily steal user information. This is why encryption is so important.
If you’re like me, you really appreciate a test automation step as part of your pull request (PR) CI for that added confidence before merging code. I want to show you how to add Playwright tests to your PRs and how to tie it all together with a GitHub Actions CI workflow.
Snyk Code supports various languages important in the cloud native arena, Ruby being among them (and we’ve seen great adoption, so thank you!). Our researchers are constantly monitoring our rule sets, using our training set of open source projects, but also — and, yes this is an advantage of a SaaS service — how the rules do on the code that is scanned. Just as a reminder, Snyk does not use your code to train our sets — but we do aggregate usage statistics.
In our previous blog breaking down The 5 Fundamentals of Cloud Security, we discussed the importance of knowing your environment. Teams need to have a comprehensive inventory of their cloud environments to have a clear understanding of the security risks that might exist within. With that in mind, let’s explore the importance of vulnerability prevention and secure design working together to keep threat actors from gaining meaningful access to your organization’s cloud control plane.
Python is a growing language. As it evolves and expands, so do the number of tools and development strategies available for working with it. One process that’s become increasingly popular is linting — or checking code for potential problems. With linting, errors in our code will be flagged so we can correct unusual programming practices that might result in problems. Linting is performed while the source code is written and before it’s compiled.
GitOps is a popular framework for managing and securing the application development pipeline. For many who have embarked on a GitOps journey, a common question is: “how can I secure my pipeline when everything is automated?” The GitOps framework is a concept where any code commits or changes are done through Git, which then triggers an automated pipeline that builds and deploys applications on Kubernetes.
Data Transfer Objects (DTOs) in Java are objects that transport data between subsystems. It is an enterprise design pattern to aggregate data. The main purpose is to reduce the number of system calls needed between the subsystems, reducing the amount of overhead created. In this article, I will explain how DTOs are used in modern Java applications, ways your application can benefit, and how Java DTOs can help you be more secure by preventing accidental data leaks.
In a previous article, I wrote about how — and why — you might want to use the Google Open Source group’s Jib tool to build your Java application container images. Jib builds slim, JVM-based, OCI-compliant images that follow best practice guidelines without the need for a container runtime like Docker, and it removes the need to write and manage Dockerfiles. What if you are building Go applications, though?
Security has been a concern in the tech industry for years now. However, not a lot of companies follow their own protocols or guides when it comes to securing code. It’s easy to believe that security incidents are uncommon (or unlikely to happen in your own organization), but the latest issue with Uber is one of many examples to the contrary.
Red teams, blue teams, and purple teams, oh my! Many of us have heard these terms, but what exactly do they mean? And where does our individual interest and expertise place us? There are many niche roles within security, but this post will cover the basics of red, blue, and purple teams, and explain how they work together to enhance an organization’s security posture.
