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Secure Infrastructure for Agentic Systems

Designing the underlying architectures, protocols, and trust boundaries that enable users to control and manage their agents.

Web Agent Security

Studying how web agents can be misled, hijacked, or otherwise driven toward unintended behavior via indirect prompt injection — and how to constrain them.

Defenses for Agentic Systems

Developing mitigation mechanisms against agentic attacks, such as indirect prompt injection, using security principles.

Multi-Agent Systems

Designing architectures that enable multiple agents to securely interact and collaborate in solving complex tasks.

RL Security

Attacks and defenses against reinforcement-learning agents, including training-time backdoor and poisoning threats.

Automated Cybersecurity Defenses

Using LLM agents to scale up security analyst capacity for incident response, threat investigation, and mitigation planning.