Systems and methods for linking a screen capture to a user support session

1 . A system comprising:

one or more processors; and

a non-transitory memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the system to:

receive metadata from a user device, the metadata associated with a screen capture initiation request;

receive a first data object indicative of a first graphical user interface associated with the user device;

provide, to the user device, the first graphical user interface comprising a request to identify one or more first articles of sensitive information within the first graphical user interface;

track one or more inputs received from the user device indicating a position of the one or more first articles of sensitive information within the first graphical user interface;

mask the one or more first articles of sensitive information within the first graphical user interface;

identify one or more second data entries within the first data object indicative of one or more second articles of sensitive information displayed by the first graphical user interface;

mask the one or second articles of sensitive information within the first graphical user interface by modifying the one or more second data entries; and

generate a second data object indicative of a second graphical user interface, the second graphical user interface comprising the masked one or more first articles of sensitive information and the masked one or more second articles of sensitive information.

2 . The system of claim 1 , wherein the instructions, when executed by the one or more processors, are configured to cause the system to:

receive, from an agent terminal, a request for the second data object; and

provide the second data object to the agent terminal, thereby facilitating display of the second graphical user interface on the agent terminal.

3 . The system of claim 2 , wherein the metadata comprises a user identifier, a user session identifier, and a timestamp associated with the screen capture initiation request.

4 . The system of claim 1 , wherein the instructions, when executed by the one or more processors, are configured to cause the system to:

store the second data object in a data repository.

5 . The system of claim 4 , wherein identifying the one or more second articles of sensitive information displayed by the first graphical user interface further comprises implementing a trained machine learning model to identify the one or more second articles of sensitive information.

6 . The system of claim 5 , wherein the trained machine learning model is configured to identify articles of sensitive information based on or more heuristics comprising identifying data entry fields associated with one or more articles of sensitive information, identifying one or more phrases proximate to the identified data entry fields indicative of one or more articles of sensitive information, a format of one or more data entry fields indicative of one or more articles of sensitive information, and combinations thereof.

7 . The system of claim 6 , wherein the tracked one or more inputs further comprise:

an indication of one or more second articles of sensitive information identified by the trained machine learning model that should be unmasked prior to the second data object being stored in the data repository or a data entry field associated with a user support session, and

wherein an indication of the one or more first articles of sensitive information received from the user device are used to update the trained machine learning model to automatically identify the one or more first articles of sensitive information.

8 . The system of claim 1 , wherein the one or more first articles of sensitive information comprise sensitive information selected from a password, a social security number, an account number, a credit card number, and combinations thereof.

9 . The system of claim 1 , wherein the screen capture initiation request is received by an API in response to a chatbot user support session initiated by a user of the user device.

10 . A system comprising:

one or more processors; and

a non-transitory memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the system to:

receive metadata from a user device, the metadata associated with a screen capture initiation request;

receive a first data object indicative of a first graphical user interface associated with the user device;

identify one or more first data entries within the first data object indicative of one or more first articles of sensitive information displayed by the first graphical user interface;

mask the one or more first articles of sensitive information within the first graphical user interface by modifying the one or more first data entries;

provide, to the user device, a modified graphical user interface comprising the masked one or more first articles of sensitive information and a request to identify one or more second articles of sensitive information within the modified graphical user interface;

track one or more inputs indicating a position of the one or more second articles of sensitive information within the modified graphical user interface;

mask the one or more second articles of sensitive information within the modified graphical user interface; and

generate a second data object indicative of a second graphical user interface, the second graphical user interface comprising the masked one or more first articles of sensitive information and masked one or more second articles of sensitive information.

11 . The system of claim 10 , wherein identifying the one or more first articles of sensitive information displayed by the first graphical user interface further comprises implementing a trained machine learning model to identify the one or more first articles of sensitive information.

12 . The system of claim 11 , wherein the trained machine learning model is configured to identify articles of sensitive information based on or more heuristics comprising identifying data entry fields associated with one or more articles of sensitive information, identifying one or more phrases proximate to the identified data entry fields indicative of one or more articles of sensitive information, a format of one or more data entry fields indicative of one or more articles of sensitive information, and combinations thereof.

13 . The system of claim 12 , wherein the tracked one or more inputs are received from the user device and are used to update the trained machine learning model to automatically identify the one or more second articles of sensitive information.

14 . The system of claim 10 , wherein the one or more first articles of sensitive information and the one or more second articles of sensitive information comprise sensitive information selected from a password, a social security number, an account number, a credit card number, and combinations thereof.

15 . The system of claim 10 , wherein:

the one or more inputs received from the user device further indicate a data entry field associated with a support request, and

the instructions, when executed by the one or more processors, are configured to cause the system to:

provide the second data object and a user identifier to an agent terminal; and

transfer a chatbot support session to the agent terminal.

16 . A computer-implemented method comprising:

receiving metadata from a user device, the metadata associated with a screen capture initiation request;

receiving a first data object indicative of a first graphical user interface associated with the user device;

identifying one or more first data entries within the first data object indicative of one or more first articles of sensitive information displayed by the first graphical user interface;

masking the one or more first articles of sensitive information within the first graphical user interface by modifying the one or more first data entries;

generating a modified graphical user interface comprising the masked one or more first articles of sensitive information and a request to identify one or more second articles of sensitive information within the modified graphical user interface;

tracking one or more inputs indicating a position of the one or more second articles of sensitive information within the modified graphical user interface;

masking the one or more second articles of sensitive information within the modified graphical user interface; and

generating a second data object indicative of a second graphical user interface, the second graphical user interface comprising the masked one or more first articles of sensitive information and masked one or more second articles of sensitive information.

17 . The method of claim 16 , wherein identifying the one or more first articles of sensitive information displayed by the first graphical user interface further comprises implementing a trained machine learning model to identify the one or more first articles of sensitive information.

18 . The method of claim 17 , wherein the trained machine learning model is configured to identify articles of sensitive information based on or more heuristics comprising identifying data entry fields associated with one or more articles of sensitive information, identifying one or more phrases proximate to the identified data entry fields indicative of one or more articles of sensitive information, a format of one or more data entry fields indicative of one or more articles of sensitive information, and combinations thereof.

19 . The method of claim 18 , wherein the tracked one or more inputs are received from the user device and are used to update the trained machine learning model to automatically identify the one or more second articles of sensitive information.

20 . The method of claim 16 , wherein the one or more inputs received from the user device further indicate a data entry field associated with a support request.