AI/ML for security professionals and how to secure your AIML product


AI/ML for security professionals and how to secure your AIML product

Session will start from the basics of machine learning and will continue our journey of learning and practicing till we reach a level where participants are able to create a complete automated attack tool using AI/ML.

The entire training program contains plenty of practical examples, scenario based exercises, revision questions and cheat sheets to ensure that the participants won’t miss anything and able to apply them at their work after the training.


  • Cyber Security Experts
  • Penetration Testers
  • Cyber Security Analyst
  • Python Developers


  • Training Slides
  • Custom Docker images


  • Participants MUST have strong knowledge of Python Programming language and ability to code on their own
  • Knowledge of how to use PIP to install packages in python
  • Knowledge of how to use virtualenv python tool to create a virtual environment and install packages there to run the code
  • A laptop with administrative privileges
  • Minimum of 20GB of free hark disk space
  • Minimum 8GB RAM
  • Laptop should have Ethernet and WiFi capability

Topics will be covered

  • Machine Learning - Why, What & How
  • Data Processing and Feature Analysis
  • Machine Learning Algorithms & Deep Learning
  • Offensive usage of AL/ML
  • Fuzzing AI/ML product and how to secure


  • Brief history of Machine Learning
  • Data pre-processing and feature engineering techniques with hands-on exercises
  • Handle missing data
  • Feature scaling
  • Feature important test
  • Handle categorical data
  • Feature reduction

ML algorithms with hands-on

  • Regression
  • Linear
  • Logistic
  • Classification
  • Naive Bayes
  • KNN
  • Decision Tree
  • SVM
  • Random Forest
  • Clustering
  • K-Means
  • Neural Network
  • ANN
  • CNN
  • NLP

Applied ML in security domain with hands on examples

  • Defensive Case Study
  • Build a web application firewalls
  • Create an intrusion detection systems
  • Identify Fake Reviews using NLP
  • Malware detection using AI/ML
  • Offensive Case Study
  • Breaking Captcha using Neural Network
  • Trigger phishing Using AI
  • Breaking passwords using AI
  • Fuzzing ML products

What you will get from this session :

  • In-depth knowledge machine learning
  • Hands on experience to code ML algorithms in Python
  • Learn the fundamentals of deep learning and neural networks
  • Hands on experience of using ML for cyber security use cases

What Shouldn’t be expected:

  • Spoon feeding on programming basics

About Trainer :

Tamaghna Basu, CTO of neoEYED Inc. is on the mission to to build a safer world with stronger, yet very convenient authentication mechanism for companies and end-users. He is a hacker, speaker, trainer and a developer too. He has more than 15 years of experience in the cyber-security domain and worked in large enterprises like PwC, Paypal, Walmart etc. to help them secure their products. His main areas of research include application security and network pen‐testing, incident handling and cyber forensics. Being a software developer earlier, he worked in python, java, .net, ruby etc. and various domains like finance, insurance, gaming etc. He is a frequent speaker/trainer in various conferences like NULLCON, C0C0N, OWASP, ISACA etc. and member of NULL, DSCI and other communities. He also contributed to security magazines like Clubhack and ISACA journal. He has accomplished various other certifications like Cyber Crime Investigation, Diploma in Cyber Law, OSCP, GCIH etc.