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Welcome to the workshop!

Workshop
In Progress

Welcome to Designing Secure ML Systems: A Threat Modeling and Risk Mitigation Lab

Today's icebreaker:

Security blind spots: What gets missed?

What’s one security risk you think often gets overlooked in ML systems?

Share your response in the chat!

Today's agenda:

Review:

Recap key concepts.

Demo:

Security walkthrough

Practice:

Securing the PackSure ML system.

Closing:

Key takeaways and next steps.

Today's learning objectives:

  • Analyse vulnerabilities across the ML system lifecycle, mapping them to core security principles.
  • Design secure ML workflows that address identified risks, including infrastructure, API, and model-level threats.
  • Apply threat modelling techniques to a real-world ML scenario, identifying mitigation strategies at each stage.
  • Develop basic team protocols for monitoring, incident response, and continuous security assessment.

Workshop slides

Preview or download a copy of the Workshop 1 slides:

Module 9 Workshop 1 — Designing Secure ML SystemsDownload

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In progress