I built CyberMira: An AI-Powered Cybersecurity Assistant Grounded in Sanity

This project creates an AI-powered cybersecurity assistant named CyberMira specifically for developers. Traditional chatbots provide general knowledge, whereas CyberMira retrieves targeted cybersecurity information from a curated knowledge base before generating relevant answers. The knowledge base contains 36 structured entries covering topics like the OWASP Top 10, vulnerabilities, attack patterns, detection techniques, mitigations, technologies, and security references.

When a developer asks a question like "How can I prevent broken object-level authorization in a REST API?", CyberMira first identifies the relevant knowledge areas, retrieves the appropriate structured evidence from the Sanity Knowledge Base, and then feeds that evidence to the language model Gemini to create a grounded security response.

The architecture separates the retrieval of structured cybersecurity knowledge from the generation of explanations. Sanity serves as the structured knowledge layer, with a Knowledge Base ID (kbDqGgqkpnBN) and specific entries like vulnerabilities, technologies, attack patterns, detection techniques, mitigations, and OWASP categories.

The process involves selecting relevant knowledge paths based on the user's question, retrieving the corresponding evidence through Sanity Context MCP, and finally generating the answer using Gemini. The system demonstrates how structured content management systems like Sanity can be leveraged for complex reasoning tasks in specialized domains.