Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Elastic Security's newest features define the potential of XDR for cybersecurity teams. Our single platform brings together SIEM and endpoint security, allowing users to ingest and retain large volumes of data from diverse sources, store and search data for longer, and augment threat hunting with detections and machine learning. Security vendors are using the term “XDR” with increasing frequency, applying varied definitions to suit their respective technologies.

We are pleased to announce the general availability (GA) of Elastic 7.14, including our Elastic Enterprise Search, Observability, and Security solutions, which are built into the Elastic Stack — Elasticsearch and Kibana. Elastic 7.14 empowers organizations with the first free and open Limitless XDR, which delivers unified SIEM and endpoint security capabilities in one platform.

As we’ve shown in a previous blog, search-based detection rules and Elastic’s machine learning-based anomaly detection can be a powerful way to identify rare and unusual activity in cloud API logs. Now, as of Elastic Security 7.13, we’ve introduced a new set of unsupervised machine learning jobs for network data, and accompanying alert rules, several of which look for geographic anomalies.

The 2010 Stuxnet malicious software attack on a uranium enrichment plant in Iran had all the twists and turns of a spy thriller. The plant was air gapped (not connected to the internet) so it couldn’t be targeted directly by an outsider. Instead, the attackers infected five of the plant’s partner organizations, hoping that an engineer from one of them would unknowingly introduce the malware to the network via a thumb drive.

Detecting and preventing malicious activity such as botnet attacks is a critical area of focus for threat intel analysts, security operators, and threat hunters. Taking up the Mozi botnet as a case study, this blog post demonstrates how to use open source tools, analytical processes, and the Elastic Stack to perform analysis and enrichment of collected data irrespective of the campaign.

I’m a security analyst at Orange Business Services in Paris, and one of my current projects for the Orange Group is implementing a new SIEM based on the Elastic Stack. In this blog post, I’ll share why we chose Elastic and how we were able to integrate Elastic into our existing SIEM, resulting in faster investigations and saving our engineers’ time. So follow along.

In a previous blog, we discussed how to monitor, troubleshoot, and fix high %CPU issues. We also revealed a system API that could have an unexpected impact on CPU consumption. In this episode, we’ll discuss another time-related performance aspect that is unique to security software: application startup time. You don’t need to be a developer to benefit from this article.

Users of Elastic Security are protected through numerous layers of protections against the REvil ransomware that affected Kaseya VSA and its customers. Elastic Security’s layered protections prevented 100% of the REvil ransomware samples tested before damage and loss could occur to the business. We believe that detections and preventions must be layered, as no single protection works 100% of the time.

We’re excited to share that Elastic Security has been recognized in the 2021 Gartner Magic Quadrant for Security Information and Event Management (SIEM). Elastic Security is the latest Elastic solution to be recognized in a 2021 Gartner Magic Quadrant report, following the 2021 Magic Quadrant for Insight Engines and 2021 Magic Quadrant for Application Performance Monitoring.