Abstract: Systems and methods include registering use of a virtual certification number (VCN) at a secure entity by receiving, at an external gateway, a registration request comprising an external request code and a primary account number (PAN), wherein the external request code is unique to the secure entity, determining that the external request code is an unregistered external request code, receiving a tokenized PAN based on the PAN, receiving an account identifier by applying the tokenized PAN to a certification mechanism tool application programing interface (API), generating a certification mechanism reference identifier by encrypting a certification mechanism associated with the account identifier and the tokenized PAN, updating a database to associate the certification mechanism reference identifier with the external request code, and transmitting, via the external gateway, a registration authentication to an external entity, the registration authentication comprising the external request code.

Abstract: Systems and methods include providing virtual certification number (VCN) authorizations to an external entity by receiving a plurality of secure entity global authorizations comprising global VCN authorizations and global primary account number (PAN) authorizations, identifying the global VCN authorizations, identifying a subset of the global VCN authorizations, each of the subset of the global VCN authorizations corresponding to an external entity authorization, comparing the subset of global VCN authorizations to previously provided VCN authorizations, to identify an unsent VCN authorization, storing a transmittable unsent VCN authorization based on the unsent VCN authorization, providing an unsent authorization indication to the external entity, receiving, from the external entity, a request for the unsent VCN authorization based on providing the unsent authorization indication to the external entity, and providing the transmittable unsent VCN authorization to the external entity, based on storing the tran

Abstract: Methods, systems, and apparatuses for risk analysis of web pages using a machine learning model are described herein. A computing device may receive a risk detection machine learning model trained to receive input corresponding to a web page and output an indication of risk associated with the web page. The computing device may execute a web browser application and collect user activity data by monitoring user activity associated with the web browser application. The computing device may access, via the web browser application, a first web page, and collect page data associated with the first web page. The computing device may calculate a risk level of the first web page. The risk level may be calculated by processing, using the risk detection machine learning model, both the user activity data and the page data. A security recommendation may be output based on the risk level.

Abstract: Systems and methods for authorizing a source for virtual certification number (VCN) use include receiving a VCN use request from an external entity, the VCN use request including the VCN and transaction data associated with the VCN use request, determining that a VCN binding for the VCN is a strict binding, mapping the transaction data to a transaction source having a transaction source identifier based on the VCN binding being the strict binding, determining a VCN source identifier for the source associated with the VCN, based on a registration authentication of the VCN with the source, comparing the VCN source identifier to the transaction source identifier, determining that the VCN source identifier corresponds to the transaction source identifier based on comparing the VCN source identifier to the transaction source identifier, outputting an approved authorization indicating that the VCN is associated with the source and the source is the transaction source.

Abstract: Systems and methods include registering use of a virtual certification number (VCN) at a secure entity by receiving, at an external gateway, a registration request comprising an external request code and a primary account number (PAN), wherein the external request code is unique to the secure entity, determining that the external request code is an unregistered external request code, receiving a tokenized PAN based on the PAN, receiving an account identifier by applying the tokenized PAN to a certification mechanism tool application programing interface (API), generating a certification mechanism reference identifier by encrypting a certification mechanism associated with the account identifier and the tokenized PAN, updating a database to associate the certification mechanism reference identifier with the external request code, and transmitting, via the external gateway, a registration authentication to an external entity, the registration authentication comprising the external request code.

Abstract: Systems and methods for triggering a virtual certification number (VCN) generation for use at a source include receiving a VCN generation request from an external entity, the VCN generation request comprising an external request code, external risk signals, and one or more source data for the source, verifying a registration authentication of an account associated with the external request code by comparing the external request code to a database entry, identifying a certification mechanism reference identifier associated with the external request code based on verifying the registration authentication, generating a risk authentication based on a risk analysis conducted using the external risk signals and the external request code, identifying a source identifier based on the one or more source data, and generating the VCN based on the certification mechanism reference identifier and the source identifier.

Abstract: Systems and methods include providing virtual certification number (VCN) authorizations to an external entity by receiving a plurality of secure entity global authorizations comprising global VCN authorizations and global primary account number (PAN) authorizations, identifying the global VCN authorizations, identifying a subset of the global VCN authorizations, each of the subset of the global VCN authorizations corresponding to an external entity authorization, comparing the subset of global VCN authorizations to previously provided VCN authorizations, to identify an unsent VCN authorization, storing a transmittable unsent VCN authorization based on the unsent VCN authorization, providing an unsent authorization indication to the external entity, receiving, from the external entity, a request for the unsent VCN authorization based on providing the unsent authorization indication to the external entity, and providing the transmittable unsent VCN authorization to the external entity, based on storing the tran

Abstract: Disclosed are methods and systems for classifying a webpage or one or more webpage elements. For instance, a method include detecting, by a user device, that a user of the user device has navigated to the webpage using a web browser installed on the user device and classifying, by the user device, the webpage or the one or more webpage elements into a classification by inputting first input data into one or more machine learning models. The method may further include, in response to classifying the webpage or the one or more webpage elements into the classification, causing the user device to display a user interface associated with an electronic application. The user interface may include information identifying the classification of the webpage.

Abstract: Methods, systems, and apparatuses for risk analysis of web pages using a machine learning model are described herein. A computing device may receive a risk detection machine learning model trained to receive input corresponding to a web page and output an indication of risk associated with the web page. The computing device may execute a web browser application and collect user activity data by monitoring user activity associated with the web browser application. The computing device may access, via the web browser application, a first web page, and collect page data associated with the first web page. The computing device may calculate a risk level of the first web page. The risk level may be calculated by processing, using the risk detection machine learning model, both the user activity data and the page data. A security recommendation may be output based on the risk level.