LiDAR sensors play a critical role in obstacle recognition and path planning within autonomous driving systems. On ROS 2-based platforms, LiDAR data is delivered through a multi-stage topic structure. While existing sensor attack research has primarily focused on physical spoofing using laser reflections, such methods require high-precision control and are subject to environmental constraints. This paper proposes two LiDAR spoofing attack scenarios that exploit the open communication architecture of ROS 2 by software-level falsification of sensor node topics, disrupting the sensor data flow. The first attack injects random data into the raw input topic, distorting the entire LiDAR processing pipeline and causing collision by preventing obstacle recognition. The second attack manipulates intermediate processed data to generate fake obstacles, leading the vehicle to stop unnecessarily. These attacks demonstrate that substantial physical impacts can be induced without directly tampering with sensor signals. This study experimentally verifies the vulnerability in the sensor data structure of a real ROS 2-based UGV environment and provides foundational insights for designing countermeasures to ensure sensor data integrity and system security.