Gradient Poisoning in Distributed Training

When one node in an organization's training cluster is compromised and continuously injects skewed gradients; due to unmitigated control gaps, the resulting model behaves anomalously in certain contexts, triggering external stakeholder impacts and causing the organization spends considerable time investigating data and code before discovering the problem lies in the training infrastructure itself.