In the first blog in this series, we unpacked the foundational concepts of encryption at rest and introduced you to Elastic Cloud’s “bring your own key” (BYOK) feature, which allows you to do encryption at rest with encryption keys managed by the KMS service of your cloud provider. The second blog of this series dives into the technical nuances of implementing encryption at rest with AWS KMS keys.

Ignoring low-risk secrets in GitGuardian? This could be a costly mistake. Learn how to avoid the hidden dangers of prematurely closing incidents.

There's no one size fits all when it comes to setting up your organization’s first security program. Each organization has a unique set of business needs, guardrails to implement, and data it needs to protect, which is why it’s important to remember that every security program is going to look a bit different. ‍ If you’re in the process of setting up your first security program, here are some steps I recommend you take and apply to your organization's unique needs. ‍

This article provides a detailed guide on successfully integrating Swagger UI into web applications using EmberJs as the Javascript framework and Webpack as the module bundler. We will cover the step-by-step process, including any challenges encountered along the way and how we resolved them. For those unfamiliar with Ember Js or Webpack, we have included introductory sections to get you up to speed. If you’re already familiar with it, feel free to skip directly to the integration steps.

Protecting PII data has never been more crucial. In today’s digital age, personal information is constantly at risk from cyber threats. Ensuring data privacy is essential for maintaining trust and compliance with regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). PII means Personally Identifiable Information. It includes data that can identify someone, like their name, address, or social security number.

In AI and machine learning, providing accurate and timely information is crucial. However, equally important is an AI model’s ability to recognize when it doesn’t have enough information to answer a query and to gracefully decline to respond. This capability is a critical factor in maintaining the reliability and trustworthiness of the entire system.

When a new major CVE gets released, cybersecurity companies race to discover ways of detecting the new vulnerability and organizations scramble to determine if they are impacted or not. Developing high-confidence techniques to scan the public-facing Internet assets for newly published vulnerabilities can potentially take weeks or even months as vulnerability researchers discover and test various detection methods.

In the high-stakes world of cybersecurity, where threats evolve hourly and every endpoint is a potential vulnerability, rapid response can make or break an organisation's defences. A recent customer case study showcases how our Quick Actions feature is enhancing the way organisations handle cybersecurity incidents.

The idea that people are the weakest link has been a constant topic of discussion in cybersecurity conversations for years, and this may have been the case when looking at the attack landscape of the past. But we live in a new world where artificial intelligence (AI), large language models (LLMs) and deep fake technology are changing every day.

In recent weeks we’ve covered how criminals use bots to steal accounts across the web. Credential stuffing tools make this easy and quick to do. If you missed it, watch a live demo of the process in this webinar. In this post we’ll look in more detail at what happens next. How do criminals monetize stolen accounts? To answer this, we’ll use the example of streaming services – one of the quickest and easiest commodities for crooks to shift and make a quick profit.