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The spatial and dynamical structure of star-forming regions can help provide insights on stellar formation patterns. The amount of data from current and upcoming surveys calls for robust and objective procedures to detect structure, so the results can be statistically analysed and different regions compared. We provide the community with a tool able to detect the small scale significant structure, above random expectation, in star-forming regions, which could be the imprint of the stellar formation process. The tool makes use of the one point correlation function and of nearest neighbour statistics to determine the parameters for the DBSCAN algorithm. The procedure successfully detects significant small scale substructures in heterogeneous regions, fulfilling the goals it was designed for, and providing very reliable structures. The analysis of regions close to complete spatial randomness ($Q \in [0.7,0.87]$) shows that, even when some structure is present and recovered, it is hardly distinguishable from spurious detection in homogeneous regions due to projection effects. Interpretation should thus be done with care. For concentrated regions, we detect a main structure surrounded by smaller ones, corresponding to the core plus some Poisson fluctuations around it. We argue that these structures do not correspond to the small compact regions we are looking for. In some realistic cases, a more complete hierarchical, multi-scale analysis would be needed to capture the complexity of the region. We have developed implementations of our procedure, and a catalogue of the NESTs (Nested Elementary STructures) detected by it in four star-forming regions (Taurus, IC 348, Upper Scorpius, and Carina), which are publicly available to the community. Implementations of the 3D, and up to 6D versions of the procedure including proper movements are in progress, and will be provided as future work.