Spamming AI System with Chaff Data
Think of this like someone constantly pulling a fire alarm when there is no fire. The security system gets overwhelmed with fake alerts, forcing the security team to stop their real work to check every single one, which wastes their time and lets real problems slip through.
This is a form of denial-of-service or noise injection where an adversary floods an AI system with low-value or irrelevant data. This triggers a high volume of false positive detections or unnecessary human-in-the-loop requests, effectively exhausting the operational capacity of the security team tasked with reviewing these outputs.
A resource exhaustion attack targeting the human-AI feedback loop, where an adversary injects high-entropy or low-utility 'chaff' data into the input stream. This induces a state of alert fatigue by artificially inflating the false positive rate of the model's inference engine or triggering excessive auditable agentic actions, thereby degrading the victim organization's incident response efficiency and increasing the cognitive load on human analysts.