Towards Building Safe & Secure Agentic AI - Dawn Song, UC Berkeley; UC Berkeley Center for Responsible Decentralized Intelligence & Matt White, Linux Foundation/PyTorch Foundation#

Dawn Song, Professor, UC Berkeley; Co-Director, Berkeley RDI; Matt White, Global CTO of AI, The Linux Foundation / Executive Director, PyTorch Foundation

• Why: Before wiring agents into production infrastructure, you need the systematized attack-surface map — this is the heavyweight academic overview of agent security, with real incidents behind it.
• What: A system-level security landscape for agentic AI: how increasing agent flexibility expands attack surfaces (prompt injection, memory poisoning, unsafe data flows, credential leakage, unauthorized execution), illustrated with real-world incidents and CVE analyses; plus a systematic overview of end-to-end automatic red teaming and a defense-in-depth framework spanning runtime guardrails, access control, information-flow tracking, privilege separation, and secure-by-design architecture (from abstract only).
• How: Comprehensive systematization of attacks and defenses across modern agent architectures rather than a single defense.
• Where applicable: Architecture-level and general; applies to any organization deploying agents against sensitive systems — a risk-assessment checklist more than an implementation guide.