Time-varying phenomena are one of the most substantial sources of astrophysical information, and their study has led to many fundamental discoveries in modern astronomy. We have developed an automated tool to search for and analyze variable sources in the near-infrared Ks band using the data from the VISTA Variables in the Via Lactea (VVV) ESO Public Large Survey. This process relies on the characterization of variable sources using different variability indices calculated from time series generated with point-spread function (PSF) photometry of sources under analysis. In particular, we used two main indices, the total amplitude {Delta}Ks and the eta index {eta}, to identify variable sources. Once the variable objects are identified, periods are determined with generalized Lomb-Scargle periodograms and the information potential metric. Variability classes are assigned according to a compromise between comparisons with VVV templates and the period of the variability. The automated tool is applied on VVV tiles d001 and d002 and led to the discovery of 200 variable sources. We detected 70 irregular variable sources and 130 periodic ones. In addition, nine open-cluster candidates projected in the region are analyzed, and the infrared variable candidates found around these clusters are further scrutinized by cross-matching their locations against emission star candidates from VPHAS+ survey H{alpha} color cuts.