In this blog, I will walk you through the process of configuring both Filebeat and Zeek (formerly known as Bro), which will enable you to perform analytics on Zeek data using Elastic Security. The default configuration for Filebeat and its modules work for many environments; however, you may find a need to customize settings specific to your environment.
OneLogin is one of the top leading Unified Access Management platforms, enabling organizations to manage and Access their cloud applications in a secure way. OneLogin makes it simpler and safer for organizations to access the apps and data they need anytime, everywhere. This post will show you how Coralogix can provide analytics and insights for your OneLogin log data – including performance and security insights.
We are excited to share that ManageEngine’s Log360 has been awarded the 2020 Fortress Cyber Security Award for Threat Detection. The Business Intelligence Group’s unique scoring system measures performance across multiple business domains.
Auth0 is one of the top leading identity management platforms in the world. It’s focused on providing solutions for application builders, specifically solutions needed for custom-built applications. Auth0 provides expertise to scale and protect identities in any application, for any audience. This post will show you how Coralogix can provide analytics and insights for your Auth0 log data – including performance and security insights.
The Slack Audit Logs API is for monitoring the audit events happening in a Slack Enterprise Grid organization to ensure continued compliance, to safeguard against any inappropriate system access, and to allow the user to audit suspicious behavior within the enterprise. This essentially means it is an API to know who did what and when in the Slack Enterprise Grid account. We are excited to announce the Slack Add-on for Splunk, that targets this API as a brand new data source for Splunk.
It's been a while since I've had the opportunity to take a break, come up for air, and write a blog for some of the amazing work the Splunk Threat Research team has done. We have kept busy by shipping new detections under security-content (via Splunk ES Content Update and our API). Also, we have improved the Attack Range project to allow us to test detections described as test unit files.
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.
