Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

If you’ve been paying attention to the latest AI product releases or evaluating AI tools for your teams, you’ll probably have noticed how difficult it is to distinguish between hype and reality. Vendors are under an enormous amount of pressure to deliver AI features, and, as a result, many of these new tools feel rushed and fragile, and simply aren’t capable of solving important, real-world problems.

Before end-to-end (E2E) testing frameworks, the software development industry struggled with fragmented and inefficient testing methods. Testing was manual, labor-intensive, and prone to human error, which limited testing coverage and left many critical issues undetected until later stages of development. This manual approach relied heavily on developers and testers executing test cases by hand, leading to substantial inefficiencies and incomplete test coverage.

In a world where cybersecurity threats are ever evolving and increasingly sophisticated, businesses of all sizes need robust solutions to protect their networks. However, these solutions have traditionally been costly and complex. WatchGuard is changing that tradition with the launch of its new ThreatSync+ Network Detection and Response (NDR) solution.

Serverless functions such as AWS Lambda, Google Cloud Functions and Azure Functions are increasingly popular among DevOps teams, as these cloud-based systems allow developers to build and run applications without managing the underlying infrastructure. But for all their benefits, serverless functions can also raise cybersecurity risk.

When evaluating models or products for their ability to scan and mask Personally Identifiable Information (PII) in your data, it's crucial to follow a systematic approach. Let’s assume you have a dataset with 1,000,000 rows, and you want to scan and mask each row.

The cloud offers unparalleled flexibility and scalability, from data storage to maintaining an online presence. However, this increased reliance on cloud infrastructure also brings heightened risks, particularly from DDoS attacks. Recent incidents underscore the urgent need for robust DDoS protection. For instance, the HTTP/2-based DDoS attack peaked last August, reaching over 398 million requests per second.

AWS-Vault is an excellent open-source tool by 99Designs that enables developers to store AWS credentials in their machine keystore securely. After using it for a while at Jit, I decided to dig deeper into how it works and learned a lot along the way. In this article, I will summarize and simplify the information I learned to help others with their aws-vault adoption and lower the barrier to usage.