This paper provides an Extended Client Based Technique (ECBT) that performs classification on emails using the Bayessian classifier that attain in-depth defense by performing textual analysis on email messages and attachment extensions to detect and flag snooping emails. The technique was implemented using python 3.6 in a jupyter notebook. An experimental research method on a personal computer was used to validate the developed technique using different metrics. The validation results produced a high acceptable percentage rate based on the four calculated validation metrics indicating that the technique was valid. The cosine of similarity showed a high percentage rate of similarity between the validation labels indicating that there is a high rate of similarity between the known and output message labels. The direction for further study on this paper is to conduct a replica experiments, which enhances the classification and flagging of the snooped emails using an advanced classification method.