Participants will understand what threat hunting is, be utterly convinced of the need for it, know what infrastructure is required to facilitate it, and be able to start doing it with confidence within their own organizations.
Target audience: Everybody who needs to know more about what threat hunting is, why it is necessary, what is required to start doing it, and how it should be done. Appropriate roles include: CISOs, Security Managers, SOC staffers, Incident Responders, Forensic Analysts and System Administrators.
Pre-requisites: To maximize value to the attendee, prior HOHE participation is highly recommended, but not mandatory.
Contents of the course
Participants learn how to hunt hackers within our Windows and Linux lab network, using a range of highly effective threat hunting technologies and techniques, looking for real life attacks.
- Technologies used:
- Sysmon : Sysmon is the go-to solution for hunters working with Windows machines, and is the technology that Microsoft itself uses to hunt hackers within their own networks.
- Elastic stack, formerly “ELK” : The Elastic Stack is a suite of mature open source technologies that is popularly used for hunting by big name companies. The principles that are taught in this course using the Elastic Stack are also more generally applicable to other data lake products such as Splunk, Sumo and others
- Elastic Security : The Elastic Security adds SIEM and Endpoint security capabilities to Elastic stack and enables threat hunters to collect data, detect anomalies, respond to threats, analyse and correlate large number of datapoints all in one ecosystem
- Osquery : Osquery is an infrastructure monitoring framework created by Facebook. Osquery enables low-level operating system monitoring by exposing the operating system as a high-performance relational database which can be easily queried using SQL syntax.
- Hunting techniques:
- Known bad : Students will learn how to research and develop hunts for known indicators of attack.
- Known good : Students will learn how to “find evil by knowing normal”, using various processes of elimination to reduce a set of raw collected data down to “not known good”. Students will then determine through investigation whether the remaining data constitute indicators of attack or benign in nature. Benign items are labeled as “known good” so that they need not be investigated again.
- Outliers : Outlier detection is the “power technique” of threat hunting. Students will learn how to leverage statistical analysis in order to force anomalies in large-scale sets of data to become apparent, which will commonly highlight indicators of attack.
It is important to note that although this course focuses on Linux and Windows endpoints, the building-block technological capabilities and hunting principles are equally applicable on MacOS and others.
More information: read from here.