International shark fin trade links human demand to shark populations harvested across multiple oceans, yet monitoring origins of traded products remains challenging because fins are rarely labelled and are often highly processed, resulting in severely degraded DNA. For several shark species listed under CITES Appendix II, this limits external verification of source populations supplying global trade hubs. Here, we assess whether nuclear genomic approaches can be applied to market-derived bull shark (Carcharhinus leucas) fins to determine their population of origin. We analysed dried fin trimmings collected from retail vendors in Hong Kong SAR, one of the world’s largest dried shark fin trade hubs, using a targeted DArTcap single nucleotide polymorphism (SNP) panel, originally developed for population genomic studies of this species. Despite substantial DNA degradation, genomic libraries were successfully obtained for most samples, yielding sufficient SNP data to perform robust provenance and sex assignment. Using a Bayesian mixed-stock analysis, most fin samples were assigned to the Indo–West Pacific (71.4%), with smaller contributions from the western Atlantic (22.6%) and eastern Pacific (3.0%). Genetic sex assignment revealed twice as many males to females, although results indicated a conservative bias toward male assignment due to the limited number of X-linked markers available in degraded samples. Our results demonstrate that genome-wide targeted approaches can be effectively applied to highly processed shark fin products to infer population sources and sex composition. By identifying which bull shark populations contribute to international trade, genomic provenance approaches provide a practical tool for monitoring human use of shark resources across ocean basins. This study provides proof-of-concept for integrating genomics into shark trade monitoring, highlighting its potential to improve traceability, support CITES implementation, and inform conservation and fisheries management, particularly for species with well-resolved population structure.