Cyber Defense Forensics Analyst 2 - Job Role Training

COURSE DESCRIPTION

Looking to become a Cyber Defense Forensics Analyst, or enhance your existing skills in the area? This package consists of hands-on labs focusing on that NIST National Initiative for Cybersecurity Education (NICE) work role. Completing these labs will help you learn the skills needed for a job in the area. The "Cyber Defense Forensics Analyst 1" package, or equivalent experience, is suggested prior to completing this package.

PREREQUISITES

Prerequisites vary by lab, but are generally: familiarity with the Unix/Linux command line and basic networking concepts (TCP/IP, DNS, etc.).

EXPECTED DURATION

16 hours, self-paced. Pause and continue at any time.

COURSE CONTENTS AND LABS

• Log Analytics with Splunk
  In this lab the student will learn how to configure and securely run the Splunk Enterprise security information collection and analysis platform. The objective of the lab is to deploy multiple instances of Splunk data forwarders through a deployment server and analyze the logs received from the servers. The student will write custom scripts to generate logs, create both visual and textual reports, organize these reports into a single dashboard, and learn to recognize malicious activity.
• Handling Potential Malware
  Students will learn to use the Cuckoo sandbox to determine if an executable or document is potential malware. If the executable is packed (compressed), they will learn to use a debugger to unpack it.
• Live Forensics using GRR
  GRR Rapid Response is an open source live forensics tool originally created by Google. GRR allows an investigator to collect data about running systems on a network, anywhere from one system to thousands. In this lab, students will perform live remote forensic investigations against running systems. Without having to take the systems offline for imaging, students will examine running processes and network connections, files and disk artifacts, and registry keys across multiple target machines in a forensically-sound manner.
• Log Analytics with Elastic Stack
  Elastic Stack is a group of services designed to take data from almost any type of source and in almost any type of format, and to search, analyze and visualize that data in real time. In this lab, Elastic Stack will be used for log analytics. Students will learn to set up and run the Elasticsearch, Logstash and Kibana components of Elastic Stack. Multiple computers in a small network will forward their logs to a central server where they will be processed by Elastic Stack. Student will use Kibana to view logs, filter them and set up dashboards. Information in the logs will be used to identify and block an on-going attack.
• Introduction to Memory Analysis with Volatility
  Analyzing a suspect system "live", before disconnecting it and imaging the disks, often yields valuable forensic evidence. Further, it can help you determine whether a crime has been committed at all, or whether the system contains evidence at all, thereby avoiding time-consuming examination of irrelevant machines. The Volatility® framework is the dominant open-source memory analysis framework, examining RAM snapshots from a large variety of operating systems in multiple formats. This lab introduces students to the process of capturing a live RAM image and analyzing it using Volatility. Students will learn about several Volatility plugins for analyzing a Windows memory image, then analyze actual RAM images, including one with active malware, and view the results.
• Conduct a Data Leak Investigation
  Get experience conducting an internal investigation on a realistic corporate network.
• Intrusion Analysis using Network Traffic
  Examine packet captures from actual intrusions and dive deeper into how attackers operate! Students will learn the details of protocols such as SMB and SSH by examining network traffic captures in Wireshark®, then will proceed to build network packets "by hand" in order to tunnel secret data in normal-looking traffic. Finally, students will learn the details of "web shell" payloads commonly used by attackers.
• Advanced Analysis of Malicious Network Traffic
  Continue your exploration into malware's behavior on the network! Students will analyze network captures containing real, malicious network traffic, both by hand and using tools such as Security Onion and Sguil. Both malware spreading methods and command and control operations will be explored. In addition, students will create web shell payloads of their own to see how they operate from the inside.

NIST NICE FRAMEWORK - JOB WORK ROLE

• Cyber Defense Forensics Analyst