Abnormal Security has a total of 36 patents globally, out of which 12 have been granted. Of these 36 patents, 30 patents are active. The United States Of America is where Abnormal Security has filed the maximum number of patents, followed by Australia and Europe. Parallelly, the United States Of America seems to be the main focused R&D centre of Abnormal Security.
Abnormal Security was founded in the year 2018 by Evan Reiser and Sanjay Jeyakumar. Company deals in email security that protects enterprises from targeted email attacks. The platform uses a data science approach to provide everything needed for comprehensive email protection, detection, and response.
Do read about some of the most popular patents of Abnormal Security which have been covered by us in this article and also you can find Abnormal Security patents information, the worldwide patent filing activity and its patent filing trend over the years, and many other stats over Abnormal Security patent portfolio.
How many patents does the founder of Abnormal Security have?
The founders, Evan Reiser and Sanjay Jeyakumar, have 24 and 50 patents respectively.
How many patents does Abnormal Security have?
Abnormal Security has a total of 36 patents globally. These patents belong to 9 unique patent families. Out of 36 patents, 30 patents are active.
How Many Patents did Abnormal Security File Every Year?
Are you wondering why there is a drop in patent filing for the last two years? It is because a patent application can take up to 18 months to get published. Certainly, it doesn’t suggest a decrease in the patent filing.
| Year of Patents Filing or Grant | Abnormal Security Applications Filed | Abnormal Security Patents Granted |
| 2022 | 5 | 9 |
| 2021 | 20 | 3 |
| 2020 | 5 | – |
| 2019 | 6 | – |
How many Abnormal Security patents are Alive/Dead?
How Many Patents did Abnormal Security File in Different Countries?
Where are Research Centres of Abnormal Security Patents Located?
The Research Centres of Abnormal Security Patents is located in United States Of America.
10 Best Abnormal Security Patents
US20200204572A1 is the most popular patent in the Abnormal Security portfolio. It has received 28 citations so far from companies like Netskope, Servicenow and Genbu Technologies.
Below is the list of 10 most cited patents of Abnormal Security :
| Publication Number | Citation Count |
| US20200204572A1 | 28 |
| US10911489B1 | 12 |
| US20210329036A1 | 10 |
| CN113474776A | 2 |
| US11032312B2 | 2 |
| WO2020132137A1 | 2 |
| US11431738B2 | 1 |
| US20220131821A1 | 1 |
| WO2021217049A1 | 1 |
| US20210297444A1 | 1 |
List of Abnormal Security Patents
| Abnormal Security Patents | Title |
| US20220368718A1 | Detection and prevention of external fraud |
| US11496505B2 | Detection and prevention of external fraud |
| US20220342966A1 | Multichannel threat detection for protecting against account compromise |
| US11483344B2 | Estimating risk posed by interacting with third parties through analysis of emails addressed to employees of multiple enterprises |
| US11477234B2 | Federated database for establishing and tracking risk of interactions with third parties |
| US11477236B2 | Approaches to creating, managing, and applying a federated database to establish risk posed by third parties |
| US11470042B2 | Discovering email account compromise through assessments of digital activities |
| US11470108B2 | Detection and prevention of external fraud |
| US11451576B2 | Investigation of threats using queryable records of behavior |
| US20220286432A1 | Discovering email account compromise through assessments of digital activities |
| EP3899769A4 | Threat detection platforms for detecting, characterizing, and remediating email-based threats in real time |
| US20220278997A1 | Multistage analysis of emails to identify security threats |
| US11431738B2 | Multistage analysis of emails to identify security threats |
| US20220272062A1 | Discovering graymail through real-time analysis of incoming email |
| US20220255961A1 | Abuse mailbox for facilitating discovery, investigation, and analysis of email-based threats |
| US20220188411A1 | Deriving and surfacing insights regarding security threats |
| US20220131821A1 | Discovering graymail through real-time analysis of incoming email |
| US11252189B2 | Abuse mailbox for facilitating discovery, investigation, and analysis of email-based threats |
| US20220030018A1 | Threat detection platforms for detecting, characterizing, and remediating email-based threats in real time |
| WO2021217049A1 | Detection and prevention of external fraud |
| US20210329036A1 | Retrospective learning of communication patterns by machine learning models for discovering abnormal behavior |
| CN113474776A | Threat detection platforms for detecting, characterizing, and remediating email-based threats in real time |
| US20210297444A1 | Programmatic discovery, retrieval, and analysis of communications to identify abnormal communication activity |
| WO2021183939A1 | Improved investigation of threats using queryable records of behavior |
| WO2021178243A1 | Abuse mailbox for facilitating discovery, investigation, and analysis of email-based threats |
| WO2021178423A1 | Multichannel threat detection for protecting against account compromise |
| WO2021174050A1 | Federated database for establishing and tracking risk of interactions with third parties |
| US20210271741A1 | Multichannel threat detection for protecting against account compromise |
| WO2021168407A1 | Discovering email account compromise through assessments of digital activities |
| US11050793B2 | Retrospective learning of communication patterns by machine learning models for discovering abnormal behavior |
| AU2019403265A1 | Threat detection platforms for detecting, characterizing, and remediating email-based threats in real time |
| US11032312B2 | Programmatic discovery, retrieval, and analysis of communications to identify abnormal communication activity |
| US10911489B1 | Discovering email account compromise through assessments of digital activities |
| US20200204572A1 | Threat detection platforms for detecting, characterizing, and remediating email-based threats in real time |
| WO2020132137A1 | Threat detection platforms for detecting, characterizing, and remediating email-based threats in real time |
| CA3120469A1 | Threat detection platforms for detecting, characterizing, and remediating email-based threats in real time |