REMOTE DESKTOP SESSION RECORDING AND AUDITING USING GENERATIVE ARTIFICIAL INTELLIGENCE

1 . A method of auditing user actions performed in remote desktop (RD) sessions, the method comprising:

acquiring a first video file that visually captures a plurality of first user actions that were performed in a first RD session by a remote device hosting the first RD session in response to instructions from a client device of the first RD session;

generating a first text file describing the first user actions from the first video file, by using a generative artificial intelligence (AI) model that has been trained to generate text descriptions of user actions from video data capturing user actions in RD sessions;

searching the first text file for keywords or phrases that have been identified as being associated with prohibited or suspicious actions; and

in response to detecting one of the keywords or phrases in the first text file, terminating the first RD session.

2 . The method of claim 1 , wherein the first video file is received at a connection device separate from the remote device, that monitors RD sessions hosted by the remote device, and wherein terminating the first RD session comprises transmitting a request from the connection device to the remote device to terminate the first RD session.

3 . The method of claim 1 , wherein the first user actions include one of: accessing a prohibited website and installing or using a prohibited application, and wherein the keywords or phrases include one of: a name or uniform resource locator (URL) of the prohibited website and a name of the prohibited application.

4 . The method of claim 1 , further comprising:

training the generative AI model with a plurality of video files each visually capturing user actions performed in RD sessions and with a plurality of text descriptions corresponding to the plurality of video files.

5 . The method of claim 1 , further comprising:

acquiring a second video file that visually captures a plurality of second user actions that were performed in a second RD session;

generating a second text file describing the second user actions from the second video file, by using the generative AI model;

detecting one of the keywords or phrases in the second text file; and

in response to detecting the one of the keywords or phrases in the second text file, causing a warning message to be displayed in a graphical user interface (GUI) of the second RD session, wherein the warning message describes one of the plurality of second actions associated with the detected one of the keywords or phrases in the second text file.

6 . The method of claim 1 , further comprising:

acquiring a second video file that visually captures a plurality of second user actions that were performed in a second RD session;

generating a second text file describing the second user actions from the second video file, by using the generative AI model;

detecting one of the keywords or phrases in the second text file; and

in response to detecting the one of the keywords or phrases in the second text file, alerting an administrator of the second RD session to review the second video file.

7 . The method of claim 1 , further comprising:

acquiring a second video file that visually captures a plurality of second user actions that were performed in a second RD session;

generating a second text file describing the second user actions from the second video file, by using the generative AI model;

searching the second text file for the keywords or phrases; and

in response to determining that none of the keywords or phrases are in the second text file, deleting the second video file from memory or storage of a computer that acquired the second video file.

8 . A non-transitory computer-readable medium comprising instructions that are executable in a computer system, wherein the instructions when executed cause the computer system to carry out a method of auditing user actions performed in remote desktop (RD) sessions, wherein the method comprises:

acquiring a first video file that visually captures a plurality of first user actions that were performed in a first RD session by a remote device hosting the first RD session in response to instructions from a client device of the first RD session;

generating a first text file describing the first user actions from the first video file, by using a generative artificial intelligence (AI) model that has been trained to generate text descriptions of user actions from video data capturing user actions in RD sessions;

searching the first text file for keywords or phrases that have been identified as being associated with prohibited or suspicious actions; and

in response to detecting one of the keywords or phrases in the first text file, terminating the first RD session.

9 . The non-transitory computer-readable medium of claim 8 , wherein the first video file is received at a connection device separate from the remote device, that monitors RD sessions hosted by the remote device, and wherein terminating the first RD session comprises transmitting a request from the connection device to the remote device to terminate the first RD session.

10 . The non-transitory computer-readable medium of claim 8 , wherein the first user actions include one of: accessing a prohibited website and installing or using a prohibited application, and wherein the keywords or phrases include one of: a name or uniform resource locator (URL) of the prohibited website and a name of the prohibited application.

11 . The non-transitory computer-readable medium of claim 8 , wherein the method further comprises:

training the generative AI model with a plurality of video files each visually capturing user actions performed in RD sessions and with a plurality of text descriptions corresponding to the plurality of video files.

12 . The non-transitory computer-readable medium of claim 8 , wherein the method further comprises:

acquiring a second video file that visually captures a plurality of second user actions that were performed in a second RD session;

generating a second text file describing the second user actions from the second video file, by using the generative AI model;

detecting one of the keywords or phrases in the second text file; and

in response to detecting the one of the keywords or phrases in the second text file, causing a warning message to be displayed in a graphical user interface (GUI) of the second RD session, wherein the warning message describes one of the plurality of second actions associated with the detected one of the keywords or phrases in the second text file.

13 . The non-transitory computer-readable medium of claim 8 , wherein the method further comprises:

acquiring a second video file that visually captures a plurality of second user actions that were performed in a second RD session;

generating a second text file describing the second user actions from the second video file, by using the generative AI model;

detecting one of the keywords or phrases in the second text file; and

in response to detecting the one of the keywords or phrases in the second text file, alerting an administrator of the second RD session to review the second video file.

14 . The non-transitory computer-readable medium of claim 8 , wherein the method further comprises:

acquiring a second video file that visually captures a plurality of second user actions that were performed in a second RD session;

generating a second text file describing the second user actions from the second video file, by using the generative AI model;

searching the second text file for the keywords or phrases; and

in response to determining that none of the keywords or phrases are in the second text file, deleting the second video file from memory or storage of a computer that acquired the second video file.

15 . A computer including a processor and memory, wherein the computer is configured to use the processor to execute instructions from the memory to:

acquire a first video file that visually captures a plurality of first user actions that were performed in a first RD session by a remote device hosting the first RD session in response to instructions from a client device of the first RD session;

generate a first text file describing the first user actions from the first video file, by using a generative artificial intelligence (AI) model that has been trained to generate text descriptions of user actions from video data capturing user actions in RD sessions;

search the first text file for keywords or phrases that have been identified as being associated with prohibited or suspicious actions; and

in response to detecting one of the keywords or phrases in the first text file, terminate the first RD session.

16 . The computer of claim 15 , wherein terminating the first RD session comprises transmitting a request to the remote device to terminate the first RD session.

17 . The computer of claim 15 , further configured to use the processor to execute the instructions from the memory to:

train the generative AI model with a plurality of video files each visually capturing user actions performed in RD sessions and with a plurality of text descriptions corresponding to the plurality of video files.

18 . The computer of claim 15 , further configured to use the processor to execute the instructions from the memory to:

acquire a second video file that visually captures a plurality of second user actions that were performed in a second RD session;

generate a second text file describing the second user actions from the second video file, by using the generative AI model;

detect one of the keywords or phrases in the second text file; and

in response to detecting the one of the keywords or phrases in the second text file, cause a warning message to be displayed in a graphical user interface (GUI) of the second RD session, wherein the warning message describes one of the plurality of second actions associated with the detected one of the keywords or phrases in the second text file.

19 . The computer of claim 15 , further configured to use the processor to execute the instructions from the memory to:

acquire a second video file that visually captures a plurality of second user actions that were performed in a second RD session;

generate a second text file describing the second user actions from the second video file, by using the generative AI model;

detect one of the keywords or phrases in the second text file; and

in response to detecting the one of the keywords or phrases in the second text file, alert an administrator of the second RD session to review the second video file.

20 . The computer of claim 15 , further configured to use the processor to execute the instructions from the memory to:

acquire a second video file that visually captures a plurality of second user actions that were performed in a second RD session;

generate a second text file describing the second user actions from the second video file, by using the generative AI model;

search the second text file for the keywords or phrases; and

in response to determining that none of the keywords or phrases are in the second text file, delete the second video file from memory or storage of the computer.