Insect invasive alien species represent an increasing threat. Yet, eradication campaigns are costly, often inefficient and non-selective, calling for the development of biodiversity friendly traps. Recently introduced in Europe, the Asian hornet Vespa velutina spreads rapidly, putting bee populations at risk thus threatening pollination service and thereby causing huge ecological damages and economical costs to apiculture and agriculture. While researchers are attempting to set an insect semiochemical-based trap but still without success, the occurrence of natural and relatively selective carnivorous plant traps (attracting and capturing Asian hornets but not honeybees) opens new perspectives. This project aims at identifying, among unexplored olfactory cues produced by two Sarracenia carnivorous pitcher plants, a specific molecule or a combination of chemical compounds attracting the Asian hornet specifically. Finding such specific bait requires a fine-scale physiological and behavioural study in the laboratory followed by validation in the field. The aims are therefore to (1) identify the Volatile Organic Compounds (VOCs) specifically detectable by the Asian hornet in the pitcher plant odour bouquet using Gas Chromatography and Mass Spectrometry (GC-MS) and coupled Gas Chromatography and Electro-AntennoGraphy (GC-EAG), (2) test the attraction of Asian hornets and the non-attraction of honeybees to these VOCs using laboratory behavioural choice tests, and (3) test the efficiency of the most species-specific laboratory-attractant(s) in the field. This original and timely project relies on promising preliminary results, cutting-edge tools, validated protocols, and a coherent consortium of partners with complementary expertise in ecology, behaviour and chemistry of plants, bees and hornets. It will yield high-quality results easily diffused through the gained knowledge on the hornet’s understudied olfactory communication, and the promotion of an efficient and species-specific trap against this major predator of honeybees.