Matthew Mittelsteadt 5/19/26 Matthew Mittelsteadt 5/19/26

Detecting Offensive Cyber Agents: A Detection-in-Depth Approach

AI agents can now orchestrate cyberattacks, dramatically altering the nature of cyber threats. To defend against these emerging threats, actors must first be able to detect them. This report outlines the AI challenge to traditional detection capabilities, introduces a framework to guide the response, and puts this into practice with actionable mechanisms.

Shaun Ee 5/23/25 Shaun Ee 5/23/25

Asymmetry by Design: Boosting Cyber Defenders with Differential Access to AI

“Differential access” is a strategy to tilt the cybersecurity balance toward defense by shaping access to advanced AI-powered cyber capabilities. We introduce three possible approaches, Promote Access, Manage Access, and Deny by Default, with one constant across all approaches — even in the most restrictive scenarios, developers should aim to advantage cyber defenders.

Shaun Ee 2/19/25 Shaun Ee 2/19/25

AI safety needs Southeast Asia’s expertise and engagement

This is a link post for an article for the Brookings Institution written by IAPS researchers Shaun Ee and Jam Kraprayoon.

Shaun Ee 10/13/23 Shaun Ee 10/13/23

Adapting Cybersecurity Frameworks to Manage Frontier AI Risks: a Defense-in-Depth Approach

The complex and evolving threat landscape of frontier AI development requires a multi-layered approach to risk management (“defense-in-depth”). By reviewing cybersecurity and AI frameworks, we outline three approaches that can help identify gaps in the management of AI-related risks.