Preventing data loss using enhanced analysis of the URLs and URIs in webpage requests
Aspects of the disclosure relate to preventing data loss using enhanced analysis of the URLs and URIs in webpage requests. A computing platform may receive a user request to access a webpage, and may determine whether the webpage is regularly accessed by the user and whether the user is permitted to access the webpage. Based on determining the user might not regularly access the website, but that the user is permitted to access the webpage, the computing platform may engage an artificial intelligence (AI) engine to parse the URL and URI from the webpage request. The AI engine may compare the URL to source code associated with the webpage to determine whether the URI was re-written. The computing platform may grant the webpage request based on determining the source code corresponds to the URL and based on determining the URI might not have been re-written.
1. A method comprising:
at a computing device including at least one or more processors and memory:
transmitting, to a proxy server, a request to access a webpage;
determining, that the webpage is not included in a baseline associated with a user;
based on determining that the webpage is not included in the baseline associated with the user, determining, using an accessibility repository, that the webpage is accessible;
based on determining that the webpage is accessible, instructing an artificial intelligence model to analyze the webpage;
parsing, by the artificial intelligence model, a uniform resource locator (URL) and a uniform resource identifier (URI) associated with the request;
determining, by the artificial intelligence model, that the URI fails to correspond to source code associated with the webpage;
based on determining that the URI fails to correspond to the source code, flagging, by the artificial intelligence model, the webpage as malicious;
transmitting, by the artificial intelligence model and to the proxy server, instructions to deny the request to access the webpage;
storing, by the artificial intelligence model, the webpage in the accessibility repository; and
transmitting a notification indicating denial of the request to access the webpage.
2. The method of claim 1 , wherein the transmitting the request to access the webpage further comprises at least one of:
transmitting the request, to an internet, across a public or private network; or
transmitting the request, using an application programming interface (API) hosted on a user computing device.
3. The method of claim 1 , wherein the baseline associated with the user indicates a plurality of webpages that the user accesses during interactions with an enterprise organization.
4. The method of claim 1 , wherein the accessibility repository is comprised of an allow list of webpages and a deny list of webpages, and wherein:
the allow list indicates a first plurality of webpages, identified by an enterprise organization, that the user is permitted to access; and
the deny list indicates a second plurality of webpages, identified by the enterprise organization, that the user is not permitted to access.
5. The method of claim 4 , wherein:
the allow list is based on at least one of:
a role, within the enterprise organization, associated with the user;
a team, within the enterprise organization, associated with the user; or
an industry associated with the enterprise organization; and
the deny list is based on crawling the Internet, by the artificial intelligence model, to identify malicious webpages.
6. A computing platform comprising:
at least one processor;
a communication interface communicatively coupled to the at least one processor; and
memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:
transmit, to a proxy server, a request to access a webpage;
determine that the webpage is not included in a baseline associated with a user;
based on determining the webpage is not included in the baseline associated with the user, determine, using an accessibility repository, that the webpage is accessible;
based on determining that the webpage is accessible, instruct an artificial intelligence model to analyze the webpage;
parse, by the artificial intelligence model, a uniform resource locator (URL) and a uniform resource identifier (URI) associated with the request;
determine, by the artificial intelligence model, that the URI fails to corresponds to source code associated with the webpage;
based on determining that the URI fails to correspond to the source code, flag, by the artificial intelligence model, the webpage as malicious;
transmit, by the artificial intelligence model and to the proxy server, instructions to deny the request to access the webpage;
store, by the artificial intelligence model, the webpage in the accessibility repository; and
transmit a notification indicating denial of the request to access the webpage.
7. The computing platform of claim 6 , wherein the transmitting the request to access the webpage further comprises at least one of:
transmitting the request, to the Internet, across a public or private network; or
transmitting the request, using an application programming interface (API) hosted on a user computing device.
8. The computing platform of claim 6 , wherein the baseline associated with the user indicates a plurality of webpages that the user accesses during interactions with an enterprise organization.
9. The computing platform of claim 6 , wherein the accessibility repository is comprised of an allow list of webpages and a deny list of webpages, and wherein:
the allow list indicates a first plurality of webpages, identified by an enterprise organization, that the user is permitted to access; and
the deny list indicates a second plurality of webpages, identified by the enterprise organization, that the user is not permitted to access.
10. The computing platform of claim 9 , wherein:
the allow list is based on at least one of:
a role, within the enterprise organization, associated with the user;
a team, within the enterprise organization, associated with the user; or
an industry associated with the enterprise organization; and
the deny list is based on crawling the Internet, by the artificial intelligence model, to identify malicious webpages.
11. One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, memory, and a communication interface, cause the computing platform to:
transmit, to a proxy server, a request to access a webpage;
determine that the webpage is not included in a baseline associated with a user;
based on determining the webpage is not included in the baseline associated with the user, determine, using an accessibility repository, that the webpage is accessible;
based on determining the webpage is accessible, instruct an artificial intelligence model to analyze the webpage;
parse, by the artificial intelligence model, a uniform resource locator (URL) and a uniform resource identifier (URI) associated with the request;
determine, by the artificial intelligence model, that the URI fails to corresponds to source code associated with the webpage;
based on determining that the URI fails to correspond to the source code, flag, by the artificial intelligence model, the webpage as malicious;
transmit, by the artificial intelligence model and to the proxy server, instructions to deny the request to access the webpage;
store, by the artificial intelligence model, the webpage in the accessibility repository; and
transmit a notification indicating denial of the request to access the webpage.
12. The one or more non-transitory computer-readable media of claim 11 , wherein the transmitting the request to access the webpage further comprises at least one of:
transmitting the request, to the Internet, across a public or private network; or
transmitting the request, using an application programming interface (API) hosted on a user computing device.
13. The one or more non-transitory computer-readable media of claim 11 , wherein the baseline associated with the user indicates a plurality of webpages that the user accesses during interactions with an enterprise organization.
14. The one or more non-transitory computer-readable media of claim 11 , wherein the accessibility repository is comprised of an allow list of webpages and a deny list of webpages, and wherein:
the allow list indicates a first plurality of webpages, identified by an enterprise organization, that the user is permitted to access; and
the deny list indicates a second plurality of webpages, identified by the enterprise organization, that the user is not permitted to access.
15. The one or more non-transitory computer-readable media of claim 14 , wherein:
the allow list is based on at least one of:
a role, within the enterprise organization, associated with the user;
a team, within the enterprise organization, associated with the user; or
an industry associated with the enterprise organization; and
the deny list is based on crawling the Internet, by the artificial intelligence model, to identify malicious webpages.