Sponge Examples: Energy and Latency Attacks on Neural Networks
Adversarial inputs that don't fool a model's outputs — they exhaust its compute. Sponge examples maximize inference energy and latency, enabling DoS attacks that bypass rate limits, drain edge-device batteries, and degrade shared inference infrastructure. What they are, how they work, and how to defend against them.