Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Given the increasing frequency, tempo, and sophistication of cyber attacks, it's more important than ever that organizations take a proactive approach to protecting their sensitive data and assets. One of the most critical elements of effective cybersecurity is openness. An open approach to cybersecurity means being transparent, sharing knowledge, and collaborating to build more robust defenses against threats.

As digitalization becomes a norm, businesses are transitioning to cloud services for increased scalability, cost-effectiveness, and operational efficiency. But this transformation comes with a new challenge — securing the cloud.

In an era where data is often referred to as the “new oil,” the importance of data security can't be overstated. Breaches can lead to financial losses, reputational damage, and lost trust among customers and stakeholders. One primary step toward mitigating security risks is choosing a data store that has been designed with a robust security framework.

Elastic is pleased to announce that we have recently achieved the AWS Security Independent Software Vendor (ISV) Competency Partner status with specialization in Threat and Detection Response (SIEM, SOAR, and XDR). This recognition highlights our commitment to providing you, our customers, with advanced security capabilities that can help you protect your sensitive data and applications in the cloud.

As the volume and complexity of cyber threats continue to increase, security analysts face mounting pressure to protect their organizations from attack with maximum efficiency. Elastic Security 8.8 introduces features designed to help analysts digest, prioritize, and quickly respond to security incidents. These features include the following: Elastic Security 8.8 is available on Elastic Cloud — the only hosted Elasticsearch offering to include all of the new features in this latest release.

Generative AI models have a long history in artificial intelligence (AI). It all started back in the 1950s with Hidden Markov Models and Gaussian Mixture Models, and it really evolved with the advent of Deep Learning. In the past five years alone, we have gone from models with several millions of parameters to the latest being GPT-4, estimated to have over 100 trillion parameters.

I often see “EDR” used as a synonym for “industry-leading endpoint security solution.” There are times when this is accurate, but there are also times when I believe that this generalization stymies discourse around current capability gaps in the endpoint security ecosystem. In this blog post, I want to share my personal taxonomy for endpoint security products — albeit one that perhaps confusingly reuses existing terminology.