Over 100 AI models with hidden backdoors were found on a major public repository last year. Not buggy models. Not inaccurate ones. Models designed to silently take over your machine the moment you load them. Here's what most people don't realize: an AI model file isn't just data. Certain formats can actually run code when opened. Researchers at JFrog found models on Hugging Face that exploited exactly this, giving attackers a persistent foothold inside whatever network downloaded them. And the scanning tools meant to catch this? They flag so many false positives that teams start ignoring the warnings altogether. The truly dangerous files slip right through. This is the supply chain problem nobody's talking about enough. Most companies treat AI models like trusted software packages. Download, integrate, deploy. But unlike traditional code, a poisoned model can behave perfectly in testing and only turn hostile when it encounters a specific trigger. Our team spent months mapping these threats, from serialization attacks and fine-tuning fragility to the unsanctioned "shadow AI" tools that 98% of organizations have employees using without oversight. The conclusion we kept reaching: safety can't be a filter you bolt on at the end. It has to be baked into the architecture itself. We put the full technical breakdown in our latest whitepaper (linked in the comments). Honest question for anyone building with AI right now: does your team formally vet the models you download, or is it mostly trust-and-go? #AISecurity #EnterpriseAI #SupplyChainSecurity