Now is the time to rethink how you manage data security. We’ve discussed the potential for breaches, financial ramifications, and loss of business in the past. These get your attention, but we’re well beyond that. No company is immune to these risks anymore. It’s the “how” that trips people up. How do you account for every line of code? How do you keep tabs on third parties? How do you ensure security teams aren’t in the way of developers?

I’ve heard the title of this article uttered in exasperation by more than a few CISOs. That can’t be the case though, right? Developers are some of the most paranoid cautious, security-conscious people I know. Compared to your average person, developers are far more skeptical when it comes to their personal data. Even as a CEO, those instincts from my time as a full-time dev persist.

Our core mission at Bearer has always been focused on improving the developer experience. As we’ve evolved, that drive narrowed in on enabling development teams to strengthen their data security posture, while still maintaining the pace and agility needs of modern software. In an environment where data breaches and leaks are increasing rapidly year over year, it’s vitally important to detect sensitive data risks before they happen.

Amazon’s Relational Database Service (AWS RDS) allows you to offload the responsibility of managing a database, but it also comes with the risk of another external dependency. Fortunately, AWS provides some tools and settings to help with this. When you combine your existing data security policy with the AWS tooling and the advice in this article, you'll be well on your way to managing risk more effectively. Let's dive in with 15 AWS RDS data security best practices.

Secure your apps! Protect sensitive data! Easy to say, harder to find solid answers on all the bits and pieces you need to adjust to make sure that happens. That's why we've put together this list of practical advice for securing your Ruby on Rails applications. Whether you're a Rails developer or work on any stack that relies on cloud technologies, we think you'll find something that stands out.

According to IBM's 2021 report, the average data breach cost more than $4 million worldwide in 2021. In the United States, that number rises to $8 million. That's an over 10% increase over the previous year. So, data breaches are a significant business risk. But costs aren't the only reason to tighten your security. Breaches hurt your clients and your company's reputation. You've seen data breaches in the news. Every day brings news of a fresh attack.

Modern business runs on data. Even companies that produce and sell physical products create, store, and use data. They need it to find customers, maintain relationships, sell products, and monitor costs and profits. Therefore, data is valuable. It's worth protecting, especially when you consider how often we hear about bad actors stealing it. But you can't protect something you don't know you have. You need a complete picture of what data your business is producing, storing, and using.

Software-driven organizations that process sensitive data are increasingly exposed to risks of data breaches. The IBM Cost of a Data Breach Reports reminds us that the average cost of a data breach rose from $3.86M to $4.24M (2021) and that the chance for an organization to experience a data breach within two years is 29.6% (2019).

Data breaches happen to companies across all industries, even within highly secure organizations. In fact, 45 percent of companies experienced a data breach in 2021, a figure that’s bound to increase this year. While you can’t always prevent a data breach, there are steps that you can take to mitigate the damage. It’s also possible to fortify your defenses so your organization is ready if and when the next attack occurs.

Working with data is something that requires a lot of care and precision, yet it often remains an under-scrutinized aspect of DevSecOps. This is because it requires focusing on many moving parts. You need to know exactly when data events occur, what parties are involved, and how they send and store data. In any process with more than minimal complexity, this is a huge web of events. Data flow mapping is the key to detangling that web.