The vulnerability of finger vein recognition to spoofing is studied in this paper. A collection of spoofing finger vein images has been created from real finger vein samples. Finger vein images are printed using a commercial printer and then, presented at an open source finger vein sensor. Experiments are carried out using an extensible framework, which allows fair and reproducible benchmarks. Experimental results lead to a spoofing false accept rate of 86%, thus showing that finger vein biometrics is vulnerable to spoofing attacks, pointing out the importance to investigate countermeasures against this type of fraudulent actions.