Hello, security enthusiasts! This is part seven (can you believe it?) of the Elastic SIEM for home and small business blog series. If you haven’t read the first six blogs in the series, you may want to before going any further. In the prerequisite blogs we created our Elasticsearch Service deployment (part 1), secured access to our cluster by restricting privileges for users and Beats (part 2), then we created an ingest pipeline for GeoIP data and reviewed our Beats configurations (part 3).

We introduced meta engines for Elastic App Search on Elastic Cloud and self-managed versions in the 7.6 release and have been thrilled to see the response to the new feature. Meta engines provide the ability to search across multiple existing or new engines. Think of adding a new search box to a page that then goes off and searches the documents in the sub-engines of your choosing.

Logstash is an open source data processing pipeline that ingests events from one or more inputs, transforms them, and then sends each event to one or more outputs. Some Logstash implementations may have many lines of code and may process events from multiple input sources. In order to make such implementations more maintainable, I will show how to increase code reusability by creating pipelines from modular components.

Given the complexity of large enterprise environments, coupled with the diversity of the vendor landscape, there is no single, agreed-upon “best” way to buy security. The battles continue between CAPEX or OPEX, net-30 or net-90, annual or multi-year, perpetual or subscription. One thing we do know, however, is that all too often the consumer pays for something he or she does not use.

Thousands of customers call the official Elasticsearch Service (ESS) on Elastic Cloud their home for running not only Elasticsearch, but exclusive products such as Elastic Logs, Elastic APM, Elastic SIEM, and more.

As antivirus and machine learning-based malware detection have increased their effectiveness in detecting file-based attacks, adversaries have migrated to “living off the land” techniques to bypass modern security software. This involves executing system tools preinstalled with the operating system or commonly brought in by administrators to perform tasks like automating IT administrative tasks, running scripts on a regular basis, executing code on remote systems, and much more.

This blog post is one in an occasional series about how we at Elastic embrace our own technology. The Elastic InfoSec team is responsible for securing Elastic and responding to threats. We use our products everywhere we can — and for more than just logs. By harnessing the power and breadth of capabilities of the Elastic Stack, we are working on tracking risk and performance metrics, threat intelligence, our control framework, and control conformance information within Elastic.

This is the third and final post of a three-part series on understanding kernel extension frameworks for Mac systems. In part 1, we reviewed the existing kernel extension frameworks and the information that these frameworks can provide. In part 2 we covered techniques that could be used in kernel to gather even more details on system events. In this post, we will go into the new EndpointSecurity and SystemExtensions frameworks.

With almost all deployed software systems consisting of multiple moving parts, it’s hard to find arguments against centralized aggregation of log entries. Deployment technologies like lightweight virtualization, Kubernetes, and serverless computing tend to spread out the components of a system across a large number of runtime primitives. Gaining visibility into the state and history of such systems is as important as ever but can also be more difficult than ever.

For several months, the Intelligence & Analytics team at Elastic Security has tracked an ongoing adversary campaign appearing to target Ukranian government officials. Based on our monitoring, we believe Gamaredon Group, a suspected Russia-based threat group, is behind this campaign. Our observations suggest a significant overlap between tactics, techniques, and procedures (TTPs) included within this campaign and public reporting.