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.

Monday June 1st, 16:00 - 17:30
Room West Wing
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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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Natalie Isak
Natalie Isak

ML Engineer, Microsoft

Expertise: AI Safety

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