DiskANN is Microsoft’s vector indexing method for fast approximate nearest-neighbor search, often used in SQL-based retrieval systems for AI. Instead of matching exact keywords, it compares embedding vectors and returns the most similar items, such as documents, tickets, logs, or policy text.
In cyber security, this matters because vector search can accelerate retrieval-augmented generation, threat hunting, and investigations over large governed datasets. Defenders may use DiskANN to find similar phishing messages, malware descriptions, or incidents across a SQL-backed knowledge base. The security risk is that similarity search can expose sensitive material if indexes include data outside intended permissions or classification boundaries. Good controls include limiting index scope, enforcing row and column access rules, reviewing what data is embedded, and monitoring for poisoning or manipulated content that changes retrieval results.