Patents by Inventor Sanjay Jeyakumar
Sanjay Jeyakumar has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240171596Abstract: A message addressed to a user is received. A first model is applied to the message to produce a first output indicative of whether the message is representative of a non-malicious message. The first model is trained using past messages that have been verified as non-malicious messages. It is determined, based on the first output, that the message is potentially a malicious message. Responsive to determining that the message is potentially a malicious email based on the first output, apply a second model to the message to produce a second output indicative of whether the message is representative of a given type of attack. The second model is one of a plurality of models. At least one model included in the plurality of models is associated with characterizing a goal of the malicious message. An action is performed with respect to the message based on the second output.Type: ApplicationFiled: September 26, 2023Publication date: May 23, 2024Inventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan Reiser, Sanny Xiao Lang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Patent number: 11973772Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: February 22, 2022Date of Patent: April 30, 2024Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan Reiser, Sanny Xiao Lang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Patent number: 11943257Abstract: Selectively rewriting URLs is disclosed. An indication is received that a message has arrived at a user message box. A determination is made that the message includes a first link to a first resource. The first link is analyzed to determine whether the first link is classified as a non-rewrite link. In response to determining that the first link is not classified as a non-rewrite link, a first replacement link is generated for the first link.Type: GrantFiled: December 21, 2022Date of Patent: March 26, 2024Assignee: Abnormal Security CorporationInventors: Yea So Jung, Su Li Debbie Tan, Kai Jing Jiang, Fang Shuo Deng, Yu Zhou Lee, Rami F. Habal, Oz Wasserman, Sanjay Jeyakumar
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Patent number: 11831661Abstract: A plurality of features associated with a message are determined. At least one feature included in the plurality of features is associated with a payload of the message. A determination is made that supplemental analysis should be performed on the message. The determination is based at least in part on performing behavioral analysis using at least some of the features included in the plurality of features. Supplemental analysis is performed.Type: GrantFiled: June 2, 2022Date of Patent: November 28, 2023Assignee: Abnormal Security CorporationInventors: Yu Zhou Lee, Micah J. Zirn, Umut Gultepe, Jeshua Alexis Bratman, Michael Douglas Kralka, Cheng-Lin Yeh, Dmitry Chechik, Sanjay Jeyakumar
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Patent number: 11824870Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: November 4, 2019Date of Patent: November 21, 2023Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan James Reiser, Sanny Xiao Yang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Patent number: 11743294Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: June 28, 2021Date of Patent: August 29, 2023Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan James Reiser, Sanny Xiao Yang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Patent number: 11704406Abstract: Deriving and surfacing insights regarding security threats is disclosed. A plurality of features associated with a message is determined. A plurality of facet models is used to analyze the determined features. Based at least in part on the analysis, it is determined that the message poses a security threat. A prioritized set of information is determined to be provided as output that is representative of why the message was determined to pose a security threat. At least a portion of the prioritized set of information is provided as output.Type: GrantFiled: September 12, 2022Date of Patent: July 18, 2023Assignee: Abnormal Security CorporationInventors: Yu Zhou Lee, Kai Jiang, Su Li Debbie Tan, Geng Sng, Cheng-Lin Yeh, Lawrence Stockton Moore, Sanny Xiao Lang Liao, Joey Esteban Cerquera, Jeshua Alexis Bratman, Sanjay Jeyakumar, Nishant Bhalchandra Karandikar
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Patent number: 11706247Abstract: Techniques for detecting instances of external fraud by monitoring digital activities that are performed with accounts associated with an enterprise are disclosed. In one example, a threat detection platform determines the likelihood that an incoming email is indicative of external fraud based on the context and content of the incoming email. To understand the risk posed by an incoming email, the threat detection platform may seek to determine not only whether the sender normally communicates with the recipient, but also whether the topic is one normally discussed by the sender and recipient. In this way, the threat detection platform can establish whether the incoming email deviates from past emails exchanged between the sender and recipient.Type: GrantFiled: July 29, 2022Date of Patent: July 18, 2023Assignee: Abnormal Security CorporationInventors: Yu Zhou Lee, Lawrence Stockton Moore, Jeshua Alexis Bratman, Lei Xu, Sanjay Jeyakumar
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Publication number: 20230224329Abstract: Techniques for detecting instances of external fraud by monitoring digital activities that are performed with accounts associated with an enterprise are disclosed. In one example, a threat detection platform determines the likelihood that an incoming email is indicative of external fraud based on the context and content of the incoming email. To understand the risk posed by an incoming email, the threat detection platform may seek to determine not only whether the sender normally communicates with the recipient, but also whether the topic is one normally discussed by the sender and recipient. In this way, the threat detection platform can establish whether the incoming email deviates from past emails exchanged between the sender and recipient.Type: ApplicationFiled: March 15, 2023Publication date: July 13, 2023Inventors: Yu Zhou Lee, Lawrence Stockton Moore, Jeshua Alexis Bratman, Lei Xu, Sanjay Jeyakumar
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Publication number: 20230208876Abstract: Selectively rewriting URLs is disclosed. An indication is received that a message has arrived at a user message box. A determination is made that the message includes a first link to a first resource. The first link is analyzed to determine whether the first link is classified as a non-rewrite link. In response to determining that the first link is not classified as a non-rewrite link, a first replacement link is generated for the first link.Type: ApplicationFiled: December 21, 2022Publication date: June 29, 2023Inventors: Yea So Jung, Su Li Debbie Tan, Kai Jing Jiang, Fang Shuo Deng, Yu Zhou Lee, Rami F. Habal, Oz Wasserman, Sanjay Jeyakumar
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Patent number: 11687648Abstract: Deriving and surfacing insights regarding security threats is disclosed. A plurality of features associated with a message is determined. A plurality of facet models is used to analyze the determined features. Based at least in part on the analysis, it is determined that the message poses a security threat. A prioritized set of information is determined to be provided as output that is representative of why the message was determined to pose a security threat. At least a portion of the prioritized set of information is provided as output.Type: GrantFiled: December 9, 2021Date of Patent: June 27, 2023Assignee: Abnormal Security CorporationInventors: Yu Zhou Lee, Kai Jiang, Su Li Debbie Tan, Geng Sng, Cheng-Lin Yeh, Lawrence Stockton Moore, Sanny Xiao Lang Liao, Joey Esteban Cerquera, Jeshua Alexis Bratman, Sanjay Jeyakumar, Nishant Bhalchandra Karandikar
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Patent number: 11683284Abstract: Techniques for identifying and processing graymail are disclosed. An electronic message store is accessed. A determination is made that a first message included in the electronic message store represents graymail, including by accessing a profile associated with an addressee of the first message. A remedial action is taken in response to determining that the first message represents graymail.Type: GrantFiled: May 12, 2022Date of Patent: June 20, 2023Assignee: Abnormal Security CorporationInventors: Rami F. Habal, Kevin Lau, Sharan Dev Sankar, Yea So Jung, Dhruv Purushottam, Venkat Krishnamoorthi, Franklin X. Wang, Jeshua Alexis Bratman, Jocelyn Mikael Raphael Beauchesne, Abhijit Bagri, Sanjay Jeyakumar
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Publication number: 20230020623Abstract: Deriving and surfacing insights regarding security threats is disclosed. A plurality of features associated with a message is determined. A plurality of facet models is used to analyze the determined features. Based at least in part on the analysis, it is determined that the message poses a security threat. A prioritized set of information is determined to be provided as output that is representative of why the message was determined to pose a security threat. At least a portion of the prioritized set of information is provided as output.Type: ApplicationFiled: September 12, 2022Publication date: January 19, 2023Inventors: Yu Zhou Lee, Kai Jiang, Su Li Debbie Tan, Geng Sng, Cheng-Lin Yeh, Lawrence Stockton Moore, Sanny Xiao Lang Liao, Joey Esteban Cerquera, Jeshua Alexis Bratman, Sanjay Jeyakumar, Nishant Bhalchandra Karandikar
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Patent number: 11552969Abstract: Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.Type: GrantFiled: October 11, 2021Date of Patent: January 10, 2023Assignee: Abnormal Security CorporationInventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan Reiser, Sanny Xiao Lang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
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Patent number: 11528242Abstract: Techniques for identifying and processing graymail are disclosed. An electronic message store is accessed. A determination is made that a first message included in the electronic message store represents graymail, including by accessing a profile associated with an addressee of the first message. A remedial action is taken in response to determining that the first message represents graymail.Type: GrantFiled: October 25, 2021Date of Patent: December 13, 2022Assignee: Abnormal Security CorporationInventors: Rami F. Habal, Kevin Lau, Sharan Dev Sankar, Yea So Jung, Dhruv Purushottam, Venkat Krishnamoorthi, Franklin X. Wang, Jeshua Alexis Bratman, Jocelyn Mikael Raphael Beauchesne, Abhijit Bagri, Sanjay Jeyakumar
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Publication number: 20220394057Abstract: Techniques for producing records of digital activities that are performed with accounts associated with employees of enterprises are disclosed. Such techniques can be used to ensure that records are created for digital activities that are deemed unsafe and for digital activities that are deemed safe by a threat detection platform. At a high level, more comprehensively recording digital activities not only provides insight into the behavior of individual accounts, but also provides insight into the holistic behavior of employees across multiple accounts. These records may be stored in a searchable datastore to enable expedient and efficient review.Type: ApplicationFiled: August 16, 2022Publication date: December 8, 2022Inventors: Jeremy Kao, Kai Jing Jiang, Sanjay Jeyakumar, Yea So Jung, Carlos Daniel Gasperi, Justin Anthony Young
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Publication number: 20220394047Abstract: A plurality of features associated with a message are determined. At least one feature included in the plurality of features is associated with a payload of the message. A determination is made that supplemental analysis should be performed on the message. The determination is based at least in part on performing behavioral analysis using at least some of the features included in the plurality of features. Supplemental analysis is performed.Type: ApplicationFiled: June 2, 2022Publication date: December 8, 2022Inventors: Yu Zhou Lee, Micah J. Zirn, Umut Gultepe, Jeshua Alexis Bratman, Michael Douglas Kralka, Cheng-Lin Yeh, Dmitry Chechik, Sanjay Jeyakumar
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Publication number: 20220368718Abstract: Techniques for detecting instances of external fraud by monitoring digital activities that are performed with accounts associated with an enterprise are disclosed. In one example, a threat detection platform determines the likelihood that an incoming email is indicative of external fraud based on the context and content of the incoming email. To understand the risk posed by an incoming email, the threat detection platform may seek to determine not only whether the sender normally communicates with the recipient, but also whether the topic is one normally discussed by the sender and recipient. In this way, the threat detection platform can establish whether the incoming email deviates from past emails exchanged between the sender and recipient.Type: ApplicationFiled: July 29, 2022Publication date: November 17, 2022Inventors: Yu Zhou Lee, Lawrence Stockton Moore, Jeshua Alexis Bratman, Lei Xu, Sanjay Jeyakumar
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Patent number: 11496505Abstract: Techniques for detecting instances of external fraud by monitoring digital activities that are performed with accounts associated with an enterprise are disclosed. In one example, a threat detection platform determines the likelihood that an incoming email is indicative of external fraud based on the context and content of the incoming email. To understand the risk posed by an incoming email, the threat detection platform may seek to determine not only whether the sender normally communicates with the recipient, but also whether the topic is one normally discussed by the sender and recipient. In this way, the threat detection platform can establish whether the incoming email deviates from past emails exchanged between the sender and recipient.Type: GrantFiled: September 30, 2021Date of Patent: November 8, 2022Assignee: Abnormal Security CorporationInventors: Yu Zhou Lee, Lawrence Stockton Moore, Jeshua Alexis Bratman, Lei Xu, Sanjay Jeyakumar
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Patent number: 11470108Abstract: Introduced here are computer programs and computer-implemented techniques for detecting instances of external fraud by monitoring digital activities that are performed with accounts associated with an enterprise. A threat detection platform may determine the likelihood that an incoming email is indicative of external fraud based on the context and content of the incoming email. For example, to understand the risk posed by an incoming email, the threat detection platform may seek to determine not only whether the sender normally communicates with the recipient, but also whether the topic is one normally discussed by the sender and recipient. In this way, the threat detection platform can establish whether the incoming email deviates from past emails exchanged between the sender and recipient.Type: GrantFiled: April 23, 2021Date of Patent: October 11, 2022Assignee: Abnormal Security CorporationInventors: Yu Zhou Lee, Lawrence Stockton Moore, Jeshua Alexis Bratman, Lei Xu, Sanjay Jeyakumar