Threat Hunting Techniques

Learn to hunt cyber threats using machine learning and real-world tools like Splunk and Jupyter Notebooks. This course covers log analysis, anomaly detection, and behavior-based threat hunting for proactive cybersecurity defense.

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Course curriculum

1. Course Intro
2. M1L1V1_Overview of Threat Hunting Concepts and Importance
3. M1L1V2-How to Plan Threat Hunt
4. M1L1V3_How to Document Threat Hunt
1. M1L2V1-Hunting Methodologies
2. M1L2V2-Telemetry and Data Sources
3. M1L2V3_Essential Tools for Threat Hunting
1. M1L3V1 - Explore MITRE ATT_CK
2. M1L3V2_How to Use MITRE Navigator_
3. M1L3V3-From ATT_CK to Action Building a Hunt Matrix for Real Threats
1. M2L1V1-Parsing and Cleaning Logs
2. M2L1V2 Techniques for Log Parsing and Cleaning Part 1
3. M2L1V3 Techniques for Log Parsing and Cleaning Part 2
1. M2 L2V3_Threat Hunting Visualization_
2. M2L2V1_Introduction to Feature Engineering_
3. M2L2V2-Visualizing Behaviors
1. M2 L3V2_Create Your Own Visualization
2. M2 L3V3_Top Security Visualizations Every Threat Hunter Should Use
3. M2L3V1 What is Security-Focused Visualization
1. M3 L1V3_Evaluating and Tuning ML Models
2. M3L1V1 - Introduction to Unsupervised ML
3. M3L1V2 - Understand Different Process of Unsupervised Learning Models
1. M3L2V1-Suspicious Login Hunting
2. M3L2V2- Graphical Representation of Anomaly
3. M3L2V3-Event Correlation
1. M3 L3V2_Different ML techniques_
2. M3L3V1_General Pitfalls in Threat Detection_
3. M3L3V3_ How to choose Best ML Model
1. M4L1V2 Log Ingestion in Splunk
2. M4L1V3_Search Operation in Splunk
3. M4LIV1_Understand Splunk Architecture
1. M4L2V1-Writing SPL for Data Prep
2. M4L2V2 - Jupyter Detection Pipeline
3. M4L2V3_Threat Hunt Notebook Example_
1. M4L3V1_Splunk and Jupyter Integration Part1
2. M4L3V2- Elastic and Jupyter Integration Part2
3. M4L3V3_Real Hunt Execution
4. Outro_Course Wrap-up Video

About this course

Free
38 lessons
4 hours of video content

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Threat Hunting Techniques

Course curriculum

Chapter 1 - What is Threat Hunting?

Chapter 2 - Hunting Methodologies

Chapter 3 - ATT&CK and Hunt Matrix

Chapter 4 - Introduction to Data Science

Chapter 5 - What is Feature Engineering in Threat Hunting

Chapter 6 - Security-focused visualization examples

Chapter 7 - Unsupervised ML Basics

Chapter 8 - Case Study: Suspicious Logins

Chapter 9 - Different use cases for ML-based Hunting

Chapter 10 - Log Ingestion in Splunk

Chapter 11 - Writing SPL for Data Preparation

Chapter 12 - Splunk and Jupyter Integration

About this course

Discover your potential, starting today