Onshore pipelines are exposed to corrosion degradation, facilitated by the pipeline’s management and surrounding aggressive environmental conditions. Every 2 to 6 years, pipeline operators often conduct In-Line (ILI) inspections to screen for pipe damage using magnetic or ultrasonic sensors. Considering soil and fluid aggressive conditions, and the possibility of false alarms or a miss-detections from the inspection device, new defects, i.e., metal loss at either the inner or outer wall, should be expected to occur between consecutive inspections. Considering the possibility of “corrosion colonies” and their significance in the pipeline’s reliability assessment, different authors have incorporated new corrosion defects in degradation and further reliability assessments using a Homogeneous Poisson Process. This process assumes that corrosion points are evenly distributed, which can be classified as conservative. This study aims to characterize the main spatial distribution of corrosion defects using the Complete Spatial Randomness (CSR) assumption under hypothesis testing. Additionally, it assesses how is the interaction between new and old defects from a repulsion–attraction perspective, and it proposes an alternative to simulate them for further reliability analyses. The suggested approach was applied in a real case study, obtaining that corrosion defects tend to be clustered and little repelled from those already detected.