
Supply Chain Poisoning in AI/ML Pipelines
NeuralStack | MS – AI Security Engineering Summary A modern ML system is assembled, not written. Training corpora are scraped or downloaded, weights are pulled from public hubs, and hundreds of trans

NeuralStack | MS – AI Security Engineering Summary A modern ML system is assembled, not written. Training corpora are scraped or downloaded, weights are pulled from public hubs, and hundreds of trans





NeuralStack | MS — AI Security Every security control eventually reduces to two questions: who is acting, and how much should they be believed. Access control answers the first question. Trust calibra

NeuralStack | MS Tech Blog – Databases & Data Engineering in AI Security Engineering, Part 4 of 4 Governance Is Not Compliance Theatre The term "data governance" carries bureaucratic connotations in

Published on NeuralStack | MS · AI Security Engineering · June 2026 Every production LLM deployment carries a category of risk that is simultaneously well-understood in theory and chronically under-e

NeuralStack | MS Tech Blog – Databases & Data Engineering in AI Security Engineering, Part 3 of 4 The Retrieval Pipeline as a Trust Boundary Retrieval-Augmented Generation (RAG) is now the dominant a

NeuralStack | MS Tech Blog – Databases & Data Engineering in AI Security Engineering, Part 2 of 4 A New Storage Primitive, A New Threat Model Vector databases emerged as a distinct infrastructure cat

NeuralStack | MS Tech Blog – Databases & Data Engineering in AI Security Engineering, Part 1 of 4 The Pipeline Is the Attack Surface In classical application security, the perimeter is relatively wel