PentesterAcademy | Pandas for Pentesters [FCO]
- CategoryOther
- TypeTutorials
- LanguageEnglish
- Total size1.2 GB
- Uploaded BySunRiseZone
- Downloads125
- Last checkedDec. 26th '20
- Date uploadedDec. 23rd '20
- Seeders 22
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Author : Vivek Ramachandran
Language : English
Duration : 4h 21m
Course Source : https://www.pentesteracademy.com/course?id=28
Description :
We are now living in a Big Data world - billions of devices communicating over millions of networks and generating petabytes of data, both at rest and in transit! Security professionals now encounter Big Data in the form of large log files, network traffic captures, forensics of large images and exports from security tools and products. In this course, we will look at how to analyze, mangle, transform and visualize data to derive interesting insights and intelligence from it.
Pandas is a Python library which is part of SciPy scientific computing ecosystem. In simple terms, Pandas provides powerful data structures to perform data analysis. As dry as this might initially sound, due to the high level of abstraction provided by its powerful API, Pandas allows us to do really complicated analysis with just a few lines of Python code.
In this course, we will go through the basics of Numpy, a deep dive into Pandas Series and Dataframes and how to analyze data with it. The case study used is analysis of Wi-Fi networks using Airodump-NG’s output file for a relatively large network with hundreds of devices.
A non-exhaustive list of topics covered include: :
• Why Pandas for Pentesters?
• Lab Setup - Python, Anaconda, Jupyter
• Numpy basics
• Pandas Series
• Vector, Logical, String Operations
• Pandas Dataframes
• Filters, Operations, Apply
• Groupby, Split-Apply-Combine
• Aggregate, Transform, Filter
• Airodump-NG Scan Data
• Access Point Analysis
• Client Analysis
• Data Visualization
• Conclusion
About Instructor :
Vivek Ramachandran is the Founder and Chief Trainer at Pentester Academy. He discovered the Caffe Latte attack, broke WEP Cloaking - a WEP protection schema, conceptualized enterprise Wi-Fi Backdoors and created Chellam, the world's first Wi-Fi Firewall. He is also the author of multiple five star rated books which have together sold over 13,000+ copies worldwide and have been translated to multiple languages.
Vivek started SecurityTube.net in 2007, a YouTube for security which current aggregates the largest collection of security research videos on the web. SecurityTube Training and Pentester Academy now serve thousands of customers from over 90 countries worldwide. He also conducts in-person trainings in the US, Europe and Asia. Vivek's work on wireless security has been quoted in BBC online, InfoWorld, MacWorld, The Register, IT World Canada etc. places. He has spoken/trained at top conferences around the world including Black Hat USA, Europe and Abu Dhabi, Defcon, Hacktivity, Brucon, SecurityByte, SecurityZone, Nullcon, C0C0n etc.
Vivek has over a decade of experience in security and has keen interest in the areas of Wireless, Mobile, Network and Web Application Pentesting, Shellcoding, Reversing and Exploit Research. He loves programming in Python, C and Assembly.
Files:
[FreeCoursesOnline.Me] PentesterAcademy - Pandas for Pentesters 0. Websites you may like- 0. (1Hack.Us) Premium Tutorials-Guides-Articles _ Community based Forum.url (0.4 KB)
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- How you can help our Group!.txt (0.2 KB)
- Airodump-NG Scan Analysis Part 1.mp4 (134.6 MB)
- Airodump-NG Scan Analysis Part 2.mp4 (86.4 MB)
- Airodump-NG Scan Analysis Part 3.mp4 (104.8 MB)
- Airodump-NG Scan Analysis Part 4.mp4 (104.9 MB)
- Airodump-NG Scan Analysis Part 5.mp4 (180.3 MB)
- Conclusion.mp4 (46.4 MB)
- Course Introduction.mp4 (109.7 MB)
- Lab Setup.mp4 (43.4 MB)
- Numpy - Boolean Indexing.mp4 (16.3 MB)
- Numpy - Universal Functions.mp4 (19.4 MB)
- Numpy Basics.mp4 (24.1 MB)
- Numpy.mp4 (28.6 MB)
- Pandas - Series Basics.mp4 (40.6 MB)
- Pandas Dataframe - Apply Function.mp4 (25.5 MB)
- Pandas Dataframe - Basics.mp4 (46.4 MB)
- Pandas Dataframe - Logical Operations.mp4 (18.7 MB)
- Pandas Dataframe - Split, Apply, Combine, Aggregate.mp4 (21.0 MB)
- Pandas Dataframe - Split, Apply, Combine, Filter.mp4 (24.4 MB)
- Pandas Dataframe - Split, Apply, Combine, GroupBy.mp4 (31.0 MB)
- Pandas Series - Logical String Operations.mp4 (26.2 MB)
- Pandas Series - Miscellaneous Operations.mp4 (26.3 MB)
- Pandas Series - Vector Operations.mp4 (35.6 MB)
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