SecAppDev 2026 lecture details
AI Memory, Mapped
AI memory is not just another RAG plugin; it is a stateful, persistent attack surface. Securing it requires new threat models, new detection primitives, and architectural decisions made well before deployment.
Download handoutsMonday June 1st, 16:00 - 17:30
Room West Wing
Recording session on Tuesday June 2nd, 11:00 - 12:30
Room Heilige-Geesttafel
Abstract
Persistent memory transforms AI systems from stateless tools into context-aware systems, but it also introduces a class of risks. We will cover key risks including continuous exfiltration via prompt injection, delayed tool invocation, and negative psychosocial impacts. The second half focuses on building memory-safe systems by design: threat modeling memory, observability strategies, and runtime safety monitoring at scale (including BinaryShield, a novel privacy-preserving method for sharing textual customer content to detect coordinated spray attacks).
Key takeaway
Treat AI memory as an attack surface; design for safety and observability from day one.
Content level
Deep-dive
Target audience
Developers, architects, researchers
Prerequisites
None
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