Pluralsight – Malware Detection and Analysis with Python 2022-12
Pluralsight – Malware Detection and Analysis with Python 2022-12 Downloadly IRSpace
Malware Detection and Analysis with Python is a course on malware detection, analysis, and understanding using Python-based tools and techniques published by Pluralsight Online Academy. It is a hands-on course that equips learners with the skills to detect, analyze, and understand malware using Python-based tools and techniques. Ideal for cybersecurity professionals, ethical hackers, and security enthusiasts, this course combines theoretical concepts with hands-on labs to build real-world capabilities in malware investigation.
In this course, Malware Detection and Analysis with Python, you will learn to automate malware prioritization, detection, and analysis. First, you will explore some of the core packages, such as yara-python, that facilitate prioritization and classification. Next, you will discover how to interact with third-party services to establish file status/reputation. Finally, you will learn how to extract artifacts and indicators from files to enable deeper analysis. Upon completion of this course, you will have the skills and knowledge of Python scripting and automation needed to enhance your workflows and malware detection and analysis capabilities.
What you will learn in Malware Detection and Analysis with Python:
- Detecting Malicious Files with Python
- Performing Malware Analysis with Python
- Analyzing Malicious Documents with Python
- Analyzing Compressed Executable Files
- Detecting Compressed Executable Files with Python
- And…
Course specifications
Publisher: Pluralsight
Instructors: Cristian Pascariu
Language: English
Level: Intermediate
Number of Lessons: 14
Duration: 1h and 8m
Course topics

Malware Detection and Analysis with Python Prerequisites
None
Pictures

Malware Detection and Analysis with Python introduction video
Installation guide
After Extract, watch with your favorite Player.
English subtitle
Quality: 720p
Download link
Size
122 MB
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