Adversary Profiling

CyberDefenses Academy



Available Upon Request


Available Upon Request

Delivery Method

Classroom & Online


Certification of Completion

Audience / Level



Identifying Adversary TTPs


Laptop required, Python experience required

Course Details

Program Introduction

Organizations thrive on being able to make the best decisions possible with the best knowledge available. Advances in technology allow for more and more data to be collected inside and outside of a company. While technology has not replaced human intelligence, it has managed to augment it. With an even vaster amount of information at our disposal, the need to understand it in a meaningful way is even greater. Good analysis is the key here, with a focus on analyzing trends, creating predictive models and analyzing security information to build strong controls and mitigations to problems.

Once data collections has started, a means to gather and store the data in such a way it can be understood is critical. The process of storing and understanding data is called Data mining, usually performed via a threat intelligence platform (TIP). Data is collected in different formats and may be with or without metadata or context. Profiling the data is where intelligence is fashioned from context infused information and made available for action, the analyzed knowledge of the history and past interactions of adversaries showing what they may take as their next move.

This is a very hands-on class, where students are challenged via a series of labs to showcase their analysis and profiling skills. The labs are contained within multiple VMs and students will min, analyze and profile the data and then map it to known and suspected enemies to build a threat matrix.

Course Objectives

  • It’s designed for those with an interest in using analysis and profiling techniques to disseminate intelligence from data.
  • It conveys the necessary concepts, principles and terms to lay down a solid foundation.

Target Student

  • Individuals with experience in threat intelligence, desiring a better understanding of analysis & profiling.
  • Professionals who deal with technical issues, but feel they do not have enough background in profiling techniques.
  • Technical professionals that need to be armed with greater knowledge of incident response, profiling, analysis and their role in resolving incidents.


Monty St John
Monty St John is a computer science and information security expert, U.S. Navy and U.S. Air Force veteran, certified instructor, and author of dozens of classes for CyberDefenses. He has assisted numerous companies build and accredit laboratories, threat teams, and security operations centers. He’s also a prolific writer with two upcoming technical volumes set for 2018; Game Designer and Speaker. Learn more about Monty St John

Additional Information

  • Laptop required
  • Requires basic knowledge of computers, technology and command line interface (CLI)
    • Open and operate browsers
    • Find and use command line
    • Execute scripts
  • Requires knowledge of Linux
  • Python experience required
  • Understanding of virtual machines (VM) and how to use one.
    • Understand how to import and power on a VM

Course Outline

  • Introduction
  • Endgame for Analysis & Profiling
  • Data Science commandments
  • Case Study: Big Data-naughty or nice list
  • Mining
    • Storing strategies
    • Threat Intelligence Platforms
  • Case Study: TIP-ing data your way
  • Analysis
    • Data Preview & Selection
    • Cleansing & Preparation
    • Selecting the right SATs
  • Case Study: Faces of the Enemy
  • Profiling
    • Choosing the right time points & observations
    • Linking data to the enemy
    • Entering the (threat) matrix
  • Anomalies & issues
  • Tips and Tricks
  • Wrap-up & Close