£700
Machine Learning for Red Teams
Enroll NOW for the online & affordable Machine Learning course specifically for Red Teamers and security professionals.
Covering a wide range of material; Python & CSharp basics, Machine Learning Theory, build SharpML from scratch taught by the co-author, build an ML Web CMS analyzer, query a model for malware static evasion, and more in the course - several years in the making.
OVERVIEW
A comprehensive Machine Learning course for security professionals
If you work in technology, Artificial Intelligence is now the THE topic being discussed. Across all segments of the corporate landscape, AI/ML will proliferate. This course will teach you the fundamentals from where you can build your own specialist knowledge.
By building practical tools, that you can use live in engagements, you will develop a strong understanding of how ML models work and how to code them. Our projects that we have built, and are building present some of what can be accomplished rapidly in cyber security:
What You Will Learn
A mixture of videos, exercises, reading, and fully fledged projects that you will build as part of the course will allow you to master the fundamentals of classical Machine Learning.
Python Basics
Many courses require knowledge of Python - we will teach you from ground-up.
Machine Learning Theory
Learn about Clutering & Classification, the maths behind it, ML theory and why not Neural Networks.
Adversarial ML
Learn about attacking Machine Learning models - here the focus is on AV & EDR engines static analysis.
Practical Tools
You will learn to build SharpML, and have two other projects to complete.
The video lessons are laid out to gradually build your knowledge from the ground up - some videos, some reading, some links, and at the end three practical courseworks that will be assessed before recieving your certificate of completion. The lesson list is below:
Chapter 1
- Introduction. Preview:
Chapter 2: Python
- Install Required Software
- Setting a Workspace
- Basic Program - Hello World
- Scalar Types
- Strings
- Variables
- Tuples
- Lists
- Sets
- Dictionaries
- Indentation
- If Elif Else
- For Loop
- While Loop
- Break Continue
- Defining a Function
- Methods
- Structure
- Using Instances
- Arguments Passing
- Mutable and Immutable
- Standard Library
- Numpy
- Scipy
- Matplotlib Pyplot
- Pandas
- I/O
Chapter 3: Machine Learning Theory and Designing an Algorithm
- Basics - Theory
- Workflow of an ML Algorithm - Theory
- (K-mean) & Distances - Theory
- Class Definition - Practical
- Normalization - Practical
- Outliers Removal - Practical
- Split Data - Training & Test Data - Practical
- Model Selection - Practical
- Score - Practical
- Plot Data - Practical
- Why Not Neural Networks - Theory
Chapter 4: Building SharpML
- SharpML Python Model Code
- Organization of SharpML Code
- Class Set Up
- Load Data
- Load Rules
- Training
- Testing
- Results
- Final Considerations
- Init
- Save Output
- Run
- Examples
- C# Code Overview
- Next Steps
Chapter 5: Build a CMS Web Analyzer
- Intro
- Further
- Instructions
Chapter 6: Build a Macaronic Obfuscator
- Intro
- Further
- Instructions
Chapter 7 (LLM BONUS) : Build an LLM Infused SAST Tool
- Intro
- Further
- Instructions
- Final Words
For a more detailed explanation of the course, don't hesitate to reach out to us and ask any questions you have.
What You Will Build
1. Main Project - SharpML:
SharpML employes C# to mine Active Directory file shares, while bundling a resource file. This resource file is a custom Machine Learning algorithm written in Python (compiled with Pyinstaller) whose logic uses Clustering and Classification to evaluate the likelihood of a User / Password pair combinations and subsequently automatically test these against a Domain Controller to assist operators in identifying passwords littered on fileshares.
A version of this tool had been open-sourced when the team were running Hunnic Cyber but further developments have been made internally by Atlan Digital and you will recieve the umcompiled Machine Learning model as part of the training. (This project was also mentioned in conjunction with DeepPass developed by the eminent Harmj0y at SpectreOps; View here).
2. Macaronic Obfuscator for Static Evasion
You will build and train your own obfuscator for static evasion.
3. LLM for Secure Code Review
As part of the course you build your own secure codre review tool using LLMs.
4. CMS Web Technologies Analyzer
Generating a dataset yourself, you will develop a model to identify web technologies in HTML pages.
Contact Us
How can we help?
Whether you represent a corporate, a consultancy, a government or an MSSP, we’d love to hear from you. To discover just how our offensive security contractors could help, get in touch.