In today’s cloud-based work environments, it’s all too easy for assets with sensitive data like PII, PCI, PHI, secrets, and intellectual property (IP) to be sprawled across the enterprise tech stack. With the skyrocketing costs of data breaches, one sprawled secret can cost organizations an average of $4.45 million. This is where Data Leak Prevention (DLP) solutions come in to limit secret sprawl, prevent data leaks, and ensure continuous compliance with leading standards.

When we launched cases in early 2023, we saw how teams combined automation with their established processes to respond to known threats. And we realized we were missing a place for security teams to address those new or unknown threats. Enter cases, our solution to case management. Over the past year, our cases feature has become a place where teams can collaborate, track, and report on new and existing workflows.

Data leaks are a growing concern for organizations due to the rising volume of sensitive information stored digitally. Leaks occur when sensitive data is inadvertently exposed, and they can easily lead to cyber attacks, reputational damage, and enormous financial costs. The best way to protect against them is to stop them from occurring in the first place. In this blog, we’ll delve into the common causes of leaks and best practices to bolster data security and prevent data leaks effectively. ‍

A new strain of the HardBit ransomware has emerged in the wild. It contains a protection mechanism in an attempt to prevent analysis from security researchers.

Python static analysis, also known as "linting", is a crucial aspect of software development. It involves inspecting your Python code without running it to identify potential bugs, programming errors, stylistic issues, or non-adhering patterns to predefined coding standards. It also helps identify vulnerabilities early in the development process, reducing the chances of deploying insecure code into production.

APIs can be vulnerable to a wide variety of attacks, such as poor inventory management and access controls, making them a primary target for attackers. Server-side request forgery (SSRF) is one type of attack that has become more prominent with the rising use of public clouds. This is primarily due to new development practices like using Instance Metadata Services (IMDS) to access valuable information about deployed instances, such as credentials.

Cybersecurity matters a lot today, and it touches everyone around the globe. With hackers becoming smarter, protecting information has never been more critical. Now, imagine trying to stay safe online but not understanding the warnings because they’re not in your language. That’s where multilingual cybersecurity comes into play – it breaks down language barriers so everyone can understand how to protect themselves.

There are several steps your organization must take to protect itself from potentially exploitable packages. First, you’ll need to carefully review and triage the package vulnerabilities that present risk to your organization, then you’ll need to patch each one. Patching a package may sound easy, but doing so without breaking your product can be tricky. ‍ Before patching, you may review the changelog between versions. Opening the changelog, however, could further the patch dread.

In the world of cybersecurity, AI-powered threats are creating new challenges for organizations.

APT40 rapidly exploits network vulnerabilities, CloudSorcerer APT targets Russian organizations, and Eldorado threatens Windows and Linux systems.