Recent research efforts in the domain of fire debris analysis have been mainly oriented towards the development of innovative analytical procedures and chemometric approaches for the detection and classification of ignitable liquids in fire specimens according to the ASTM E1618. However, less attention has been brought to the question of the source inference of ignitable liquids. Infer the identity of source of ignitable liquids recovered from arson sites is still a challenging and ongoing research area. In this study, the objective is to link neat gasoline samples sharing a common source through the use of an untargeted chemometric approach applied to data acquired by automated thermodesorption (ATD)-GC-MS following passive headspace extraction onto Tenax TA tubes. To that end, 190 unique gasoline samples from 19 gas stations collected over a year were used. A general and automated chemometric methodology for data treatment involving the following main steps is proposed: feature detection, normalization by exhaustive calculation of ratios between areas of pairs of features and selection of most discriminant ratios. The ratio selection procedure used here is based on the calculation of similarity measurements between pairs of samples sharing a common source or not. The algorithm maximizes the separation of the distributions of similarity measurements for related and unrelated samples by selecting a subset of ratios maximizing the area under the Receiver Operating Characteristics curve. The approach presented here was successfully applied to neat gasoline samples in order to assess if two gasoline samples share a common source or not.