Please Don't Discard - Security Data
Rishabh Gupta, Hrushikesh Paralikar
BSidesSF 2024 · Day 1
This article delves into a novel approach for tackling security review challenges by systematically persisting, storing, and structuring security data. Presented by Rishabh Gupta, a Senior Security Engineer, and Hrushikesh Paralikar, a Senior Software Engineer, both from Snowflake and working on anti-abuse, the talk highlights how this methodology, combined with Natural Language Processing (NLP), can effectively identify and address complex security threats, particularly abuse scenarios. The core problem addressed is the difficulty in answering critical questions like "which systems are affected by abuse threats?" within large organizations, a task often daunting due given the multitude of systems and threat types.
AI review
This talk presents a robust, scalable approach to developer-driven security reviews by structuring and persisting threat modeling data. By combining Rapid Threat Modeling Prototyping (RTMP) with graph-based data storage and a clever LLM integration for interpreting node properties, the system automates the identification of traditional STRIDE and novel abuse threats. The ability to use SQL queries on this structured data, augmented by precise LLM interpretations, provides a powerful and actionable framework for developers to secure their features, even identifying flaws in their own data…