Threat actors may target the ground-based systems and data pipelines that support Space Domain Awareness (SDA), either by corrupting key data sources, manipulating tracking information, or overloading the ingestion architecture. The objective is to blind or confuse decision-makers and automated systems responsible for monitoring and responding to on-orbit activity. This includes compromising or spoofing telemetry, TLEs, sensor feeds, radar/optical returns, or orbital prediction services used by tracking centers. It also includes the enumeration and exploitation of analytic infrastructures, such as AI/ML-enhanced SDA platforms. In cases where SDA systems leverage AI/ML inference for object detection and decision support, attackers may seek to degrade model performance by flooding the data pipeline with misleading, noisy, adversarial, or low-quality sensor inputs. These disruptions aim to delay detection of threats, generate false positives, or cause resource exhaustion in SDA fusion and alerting systems. This sub-technique differs from onboard deception (e.g., sensor spoofing) by targeting the terrestrial decision support infrastructure, potentially affecting multiple spacecraft or operators simultaneously.