The study is an Application Programming Interface (API) which provides a secondary authentication using a facial recognition algorithm with an intruder selfie feature. The study was structured around the use of the Rapid Application Development (RAD) model wherein a total of four system iterations were created. Progression was tracked during the cutover phase through the implementation of libraries and algorithms. The sampling methodology used was the random sampling method to assure that there will be no biases towards categorizing test participants during the testing phase conducted on the 3rd iteration. After the completion of four testing phases through all iterations of the system, it has been recorded that 48 out of 50 participants with the percentage translating to a 96% successful verification and authentication rate using the enhanced API with an error rate of less than 5 percent. The conclusive remark after the successful testing development phase of the 4th iteration of the system deems the API to have followed the set objectives of the study, with the successful implementation of the anti-image spoofing algorithm, detection of natural and unnatural faces, and the intruder selfie feature.