Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Elastic

Machine learning in cybersecurity: Detecting DGA activity in network data

In Part 1 of this blog series, we took a look at how we could use Elastic Stack machine learning to train a supervised classification model to detect malicious domains. In this second part, we will see how we can use the model we trained to enrich network data with classifications at ingest time. This will be useful for anyone who wants to detect potential DGA activity in their packetbeat data.

macOS vs. Windows - What kernels tell you about security events: Part 1

How would you compare the Windows and macOS operating systems? In what ways are they similar? Why do they each take different approaches to solving the same problem? For the last 19 years I've developed security software for Windows. Recently, I’ve started implementing similar features on macOS. Since then, people have asked me questions like this. The more experience I gained on these two operating systems, the more I realized they’re very different.

Elastic Security opens public detection rules repo

At Elastic, we believe in the power of open source and understand the importance of community. By putting the community first, we ensure that we create the best possible product for our users. With Elastic Security, two of our core objectives are to stop threats at scale and arm every analyst. Today, we’re opening up a new GitHub repository, elastic/detection-rules, to work alongside the security community, stopping threats at a greater scale.

Preventing "copy-paste compromises" (ACSC 2020-008) with Elastic Security

The Australian Cyber Security Centre (ACSC) recently published an advisory outlining tactics, techniques and procedures (TTPs) used against multiple Australian businesses in a recent campaign by a state-based actor. The campaign — dubbed ‘copy-paste compromises’ because of its heavy use of open source proof of concept exploits — was first reported on the 18th of June 2020, receiving national attention in Australia.

How to use Kibana effectively. Today: Detect possible frauds in your data

Kibana is quite powerful and versatile for visualizing data in Elasticsearch. The Elastic Stack can be used for a variety of use cases. One is the detection of frauds e.g. in Banking transaction like within Softbank Payment Service or bonus point accounts like within Miles and More. Other areas are insurance or tax return data.

Journey of Elastic SIEM Getting Started to Investigating Threats: Part 2

Calling all security enthusiasts! Many of us are now facing similar challenges working from home. Introduced in 7.2, Elastic SIEM is a great way to provide security analytics and monitoring capabilities to small businesses and homes with limited time and resources. In this three part meetup series we will take you on a journey from zero to hero - getting started with the Elastic SIEM to beginner threat hunting.

Threat Hunting with Elastic APM

Learn how APM lets you monitor the performance of applications deployed anywhere within your network. Now you can use APM data to hunt for threats and injection attacks, too. Elastic provides a common data platform so you can view HTTP data collected with your APM agents in the Elastic SIEM app. It’s seamless monitoring and protection to keep your systems up, running, and secure.

Getting started with adding a new security data source in your Elastic SIEM: Part 1

What I love about our free and open Elastic SIEM is how easy it is to add new data sources. I’ve learned how to do this firsthand, and thought it’d be helpful to share my experience getting started. Last October, I joined Elastic Security when Elastic and Endgame combined forces. Working with our awesome security community, I’ve had the opportunity to add new data sources for our users to complement our growing catalog of integrations.