RED TEAM ALCHEMY
Offensive Machine Learning
Take a deep look at using ML for offensive security. Design, build, and deploy models into real world tooling. Attack models and evade detection. Create the universal operator.
The Course
Machine learning (ML) has so far been unchecked on its way to
cyber-security domination. However, regardless of its success so far,
adversaries will ultimately decide if ML is a viable solution to help
detect and prevent modern attacks. Currently, the majority of research
is done by defensive vendors and academic researchers in lab
environments, far removed from the high pace of real-world operations.
It’s time for offensive security professionals to join the discussion.
Offensive teams might not have as many papers published, but they have
data, network access, and the right mindset to challenge ML systems in
real-world environments.
ML is changing the way organizations do business, and it is important
offensive teams develop the skills necessary to assess and secure ML
systems. In addition to protecting their clients, teams with ML skills
will create next generation of offensive tools, and give themselves an
edge in ever tightening networks. If you’re a red teamer or penetration
test and want to prepare for when ML comes for your shells, build the
hottest tools since HAL 9000, or steal models for fun and profit. This
course is for you. Otherwise, if you’re a data scientist or machine
learning engineer looking for insights into how an industry leading red
team is using ML, and/or want to come to the dark side, this course is
for you.
Learn
Explore
fundamental machine learning and red teaming concepts
Create
ML enabled tools, modules, and malware
Design
build, and automate the deployment of models
Generate
synthetic social-engineering personas and attacks
Explore
Markov Chains, Reinforcement Learning, and simulators
Codify
offensive knowledge, and teach models with historical operations data
Steal
and evade deployed ML models
