5 citations · 14 across the 6 of their papers we have counts for
5 papers · 1 filter
Detecting Offensive Cyber Agents: A Detection-in-Depth Approach
Matt Mittelsteadt, Jam Kraprayoon, Robin Staes-Polet +4
Artificial Intelligence (AI) agents can now orchestrate cyberattacks. This development is already increasing the speed and scale of cyber attacks, decreasing attack costs, and impr…
Highly Autonomous Cyber-Capable Agents: Anticipating Capabilities, Tactics, and Strategic Implications
Jam Kraprayoon, Shaun Ee, Brianna Rosen +4
This report introduces the concept of "Highly Autonomous Cyber-Capable Agents" (HACCAs), AI systems capable of autonomously conducting multi-stage cyber campaigns at a level compar…
Adapting cybersecurity frameworks to manage frontier AI risks: A defense-in-depth approach
Shaun Ee, Joe O'Brien, Zoe Williams +3
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 fr…
Coordinated Disclosure of Dual-Use Capabilities: An Early Warning System for Advanced AI
Joe O'Brien, Shaun Ee, Jam Kraprayoon +3
Advanced AI systems may be developed which exhibit capabilities that present significant risks to public safety or security. They may also exhibit capabilities that may be applied…
Deployment Corrections: An incident response framework for frontier AI models
Joe O'Brien, Shaun Ee, Zoe Williams
A comprehensive approach to addressing catastrophic risks from AI models should cover the full model lifecycle. This paper explores contingency plans for cases where pre-deployment…