tl;dr

We're excited to announce AI Security Bootcamp (AISB), a 4-week intensive program designed to bring researchers and engineers up to speed on security fundamentals for AI systems. The program will cover cybersecurity fundamentals (cryptography, networks), AI infrastructure security (GPUs, supply chain security), and more novel attacks on ML systems (dataset trojans, model extraction). This program will run in-person from 4th Aug to 29th Aug in London, UK. We will cover all expenses.

Apply here to participate in AISB before EOD AoE, 22nd June 2025.

We are also looking for instructors for parts of the program and staff to help with operations. Apply here.

Summary

We are running a 4-week program designed to equip AI safety researchers and engineers with critical security skills. We hope you'll leave the program with a well-practiced security mindset that will help you work on impactful projects and make AI systems more secure.

The curriculum includes exercises designed to help you get hands-on experience with securing AI systems, while building and practicing the security mindset. This includes a mix of pair programming exercises, lectures, reading about public vulnerabilities, and chats with experts.

This program is aimed at people who are at ~the start of their journey into security, and have working knowledge in ML (or are willing to brush up using the MLAB curriculum before the program). We encourage you to apply if you think you'll be a good fit regardless of checking all the boxes - if going on technical deep dives and trying to understand how systems work by peeling the layers of abstraction away excites you, we'd love to hear from you.

Content

The content is divided into roughly three sections - introduction to security, cybersecurity for AI infrastructure, and attacks on modern ML pipelines. The exercises are designed to give you hands-on experience with cybersecurity on both the offensive and defensive sides, as well as train your security muscles so that you are more effective at spotting and patching security holes.

Introduction to security - This includes introduction to cryptography and cryptanalysis, the basics of Linux security, and breaking network protocols.
Securing AI infrastructure - This section covers topics especially relevant to AI security - containerization, a case study on supply chain security, application security, and SecOps.
AI pi

...

Posts

Wikitag Contributions

Comments