The growing threat of darknet-related activities, ranging from illegal marketplaces to command-and-control infrastructures, has made the accurate identification of darknet traffic a critical concern for cybersecurity professionals. In response to the lack of high-quality, well-labeled datasets in this domain, we present a newly created darknet traffic dataset to support research and analysis efforts in network security. The dataset was developed to address data availability, consistency, and challenges with labeling accuracy. It comprises around 92 megabytes of traffic data on the first layer and 35 megabytes of traffic data on the second and third layer, including nearly 253K individual flows and 79 distinct features (source/destination IPs, ports, protocols, timestamps, etc.), Each entry is labeled according to its nature as darknet or non-darknet traffic in the first layer, and further labeled by darknet type and behavior in the second and third layers, respectively. Potential applications include threat intelligence research, network traffic analysis, and testing security tools and policies. The dataset has a comprehensive three-layered label, indicating its relevance and practical utility for understanding darknet traffic behavior in various applications.