SYSTEM AND METHOD FOR ELECTRONIC MESSAGING THREAT SCANNING AND DETECTION
A new approach is proposed to support electronic messaging threat scanning and detection to identify security threats missed by an existing security software of an electronic messaging system. An AI engine first retrieves an entire inventory of historical electronic messages by the users on the electronic messaging system over a certain time. The AI engine scans the retrieved inventory of historical electronic messages to identify various types of security threats to the electronic messaging system in the past. The AI engine compares the identified security threats to those that have been identified by the existing security software to identify a set of security threats that had eluded or missed by the existing security software in the past. The AI engine then removes, modifies, or quarantines electronic messages that contain the missed security threats so that none of them will trigger an attack to the electronic messaging system in the future.
1 . A system to support electronic messaging threat scanning and detection, comprising:
an artificial intelligence (AI) engine running on a host, which in operation, is configured to
retrieve an entire inventory of historical electronic messages by users of an entity on an electronic messaging system over a certain time via an application programming interface (API) call to the electronic messaging system;
scan the retrieved inventory of historical electronic messages to identify a plurality of various types of security threats to the electronic messaging system in the past;
compare the plurality of identified security threats to those that have been identified by an existing security software of the electronic messaging system to identify a set of security threats that had eluded or missed by the existing security software in the past;
remove, modify, or quarantine a set of the historical electronic messages that contain at least one of the missed security threats from the electronic messaging system so that none of the missed security threats will trigger an attack to the electronic messaging system in the future.
2 . The system of claim 1 , wherein:
the electronic messaging system is one of Office365/Outlook, Slack, LinkedIn, Facebook, Gmail, Skype, Salesforce, and any communication platform configured to send and/or receive the electronic messages to and/or from users within the entity.
3 . The system of claim 1 , wherein:
each user is either a person or a system or component configured to send and receive the electronic messages.
4 . The system of claim 1 , wherein:
the AI engine is configured to collect not only external electronic messages exchanged between the users of the entity and individual users outside of the entity, but also internal electronic messages exchanged between users within the entity.
5 . The system of claim 1 , wherein:
the AI engine is configured to collect the electronic messages from an electronic messaging server by using an installed email agent on the electronic messaging server or adopting a journaling rule to retrieve the electronic messages from the electronic messaging server.
6 . The system of claim 1 , wherein:
the various types of the plurality of identified security threats include one or more of viruses, malware, phishing emails, communication frauds and other types of impersonating attacks.
7 . The system of claim 6 , wherein:
the AI engine is configured to identify not only the communication frauds and/or other types of impersonating attacks but also the viruses and malwares by scanning the retrieved inventory of historical electronic messages.
8 . The system of claim 1 , wherein:
the AI engine is configured to save and maintain the identified set of missed security threats in an analysis database.
9 . The system of claim 1 , wherein:
the AI engine is configured to detect some of the missed security threats that still leave the entity and its users vulnerable even if they have not been triggered attack to the electronic messing system in the past.
10 . The system of claim 9 , wherein:
the AI engine is configured to detect some of the missed security threats as latent threats, which, once triggered by an attacker or a user, launch an attack to the entity via the electronic messaging system.
11 . The system of claim 1 , wherein:
the AI engine is configured to fix one or more vulnerabilities in the electronic messaging system by enforcing additional security checks for communication fraud in incoming electronic messages in real time in addition to the existing security software of the electronic messaging system.
12 . The system of claim 11 , wherein:
the AI engine is configured to enforce the additional security checks for communication fraud based on identified communication patterns of the users and/or identified high-risk individual users in the entity.
13 . A computer-implemented method to support electronic messaging threat scanning and detection, comprising:
retrieving an entire inventory of historical electronic messages by users of an entity on an electronic messaging system over a certain time via an application programming interface (API) call to the electronic messaging system;
scanning the retrieved inventory of historical electronic messages to identify a plurality of various types of security threats to the electronic messaging system in the past;
comparing the plurality of identified security threats to those that have been identified by an existing security software of the electronic messaging system to identify a set of security threats that had eluded or missed by the existing security software in the past;
removing, modifying, or quarantining a set of the historical electronic messages that contain at least one of the missed security threats from the electronic messaging system so that none of the missed security threats will trigger an attack to the electronic messaging system in the future.
14 . The computer-implemented method of claim 13 , further comprising:
collecting not only external electronic messages exchanged between the users of the entity and individual users outside of the entity, but also internal electronic messages exchanged between users within the entity.
15 . The computer-implemented method of claim 13 , further comprising:
collecting the electronic messages from an electronic messaging server by using an installed email agent on the electronic messaging server or adopting a journaling rule to retrieve the electronic messages from the electronic messaging server.
16 . The computer-implemented method of claim 13 , further comprising:
identifying not only the communication frauds and/or other types of impersonating attacks but also the viruses and malwares by scanning the retrieved inventory of historical electronic messages.
17 . The computer-implemented method of claim 13 , further comprising:
saving and maintaining the identified set of missed security threats in an analysis database.
18 . The computer-implemented method of claim 13 , further comprising:
detecting some of the missed security threats that still leave the entity and its users vulnerable even if they have not been triggered attack to the electronic messing system in the past.
19 . The computer-implemented method of claim 18 , further comprising:
detecting some of the missed security threats as latent threats, which, once triggered by an attacker or a user, launch an attack to the entity via the electronic messaging system.
20 . The computer-implemented method of claim 13 , further comprising:
fixing one or more vulnerabilities in the electronic messaging system by enforcing additional security checks for communication fraud in incoming electronic messages in real time in addition to the existing security software of the electronic messaging system.
21 . The computer-implemented method of claim 20 , further comprising:
enforcing the additional security checks for communication fraud based on identified communication patterns of the users and/or identified high-risk individual users in the entity.