As AI agents become increasingly integrated into software development, we are not only engineering models, but the harnesses around them - their tools, context, credentials, and interactions with external systems. This creates new security surfaces where sensitive data can unintentionally flow from trusted environments into model context, telemetry, logs, or external services. This lecture explores the security vulnerabilities that emerge within harness engineering, how to reason about sensitive-data flow across the agentic lifecycle, and practical best practices for reducing these risks. It will also introduce Weir, an open-source tool for deterministically testing and monitoring credential flows in AI agents.
Bio
Software Engineer from big tech (Meta), Cyber startups (Token, Ironscales) and IDF. I innovate security in Agentic Development Lifecycle.
Length
40 minutes