With the advancement of offline Finding Network (OFN) technology, tracking tags are being utilized in various fields, including locating elderly individuals with dementia, caring for children, and managing lost items. Recently, however, tracking tags have been misused in stalking, surveillance, and debt collection, highlighting the growing importance of digital forensics in proving criminal acts. While there has been some research on Apple AirTag and Tile products, studies focusing on Samsung's tracking tag have been lacking. Therefore, this paper proposes digital forensic techniques for law enforcement agencies to analyze Samsung tracking tag applications to identify perpetrators and substantiate criminal activities. We analyzed six tags and three applications, recognizing tag identifiers, and confirmed that location data is stored in both plaintext and encrypted forms within SQLite databases and XML files. Additionally, we conducted experiments on five different anti-forensics scenarios: 1) deletion of a registered tracking tag, 2) deletion of location data, 3) account logout, 4) service withdrawal, and 5) application synchronization, finding meaningful results to substantiate criminal actions. Furthermore, we developed S.TASER (Smart Tag Parser) based on Python that allows for the identification of deleted tags, recovery of identification data, and visualization of collected location data per tag. S.TASER's code, experimental scenarios, and raw data are publicly available for further verification. This study aims to contribute to the global digital forensic industry by suggesting additional options for investigation and evidence gathering of crimes that make use of Network.