Paypal, Inc.

Kevin Tyers

Bradley Wardman

Nathan Robert Pratt

Blake Morgan Butler

Meethil Vijay Yadav

Eric Nunes

Nicole Harris

Todd Clausen

Nicholas Bailey

Jakub Burgis

Jakub Ceiran Burgis

Nate Robert Pratt

A method for phishing detection based on modeling of web page content is discussed. The method includes accessing suspect web page content of a suspect Uniform Resource Locator (URL). The method includes generating an exemplary model based on an exemplary configuration for an indicated domain associated with the suspect URL, where the exemplary model indicates structure and characteristics of an example web page of the indicated domain. The method includes generating a suspect web page model that indicates structure and characteristics of the suspect web page content. The method includes performing scoring functions for the potential phishing web page content based on the suspect web page model, where some of the scoring functions use the exemplary model to perform analysis to generate respective results. The method includes generating a web page content phishing score based on results from the scoring functions.

Phishing detection based on modeling of web page content

Systems and methods for providing a threat intelligence system include a system provider device that downloads, through communication over a network and from one or more targeted websites, a plurality of images of a first environment. Based on an OCR process, the system provider device may extract a set of textual data corresponding to a subset of images of the plurality of images, where the subset of images depict text. The system provider device stores the set of textual data in an indexed and searchable database. The system provider device assigns a threat assessment score to each image based on the set of textual data, and the threat assessment score may be updated based on comparison of the set of textual data with other sets of textual data. Based on the threat assessment score being greater than a threshold value, the system provider device may generate a security alert.

Threat intelligence system

Methods and systems are presented for dynamically adjusting a risk classification of a risk source based on classifications of one or more other risk sources. The risk engine may first classify a first risk source as a first risk type based on an initial analysis of the first risk source. Subsequent to classifying the first risk source as the first risk type, the risk engine may determine that a second risk source is associated with a second risk type. Based on the determination that the second risk source is associated with the second risk type, the risk engine may re-classify the first risk source as the second risk type. The risk engine may then use the reclassification of the first risk source to improve network security of an online service provider.

Multi-dimensional drift nuance intelligence threat engine

A method for phishing detection using uniform resource locators is discussed. The method includes accessing data from one or more of a monitored portion of website data and a monitored portion of emails, the data indicating a suspect Uniform Resource Locator (URL). The method includes assigning a rule score based on partial rule scores of each portion of the suspect URL, the rule score indicating a phishing potential based on URL rules. The method includes determining a uniqueness score of the suspect URL, the uniqueness score indicating a degree of uniqueness of the suspect URL from a plurality of known phishing URLs. The method also includes determining a URL phishing score based, at least in part, on the rules scores and the uniqueness score for the suspect URL.

Phishing detection using uniform resource locators

Methods and systems for assessing and evaluating vulnerabilities of a networked system are presented. A list of known vulnerabilities that have been disclosed in the public may be obtained. The networked system may be scanned from an external perspective to obtain network information of the networked system. A subset of the known vulnerabilities may be determined to be relevant to the networked system based on correlations between the vulnerabilities and the network information. The networked system may also be analyzed from an internal perspective to determine impacts of the relevant known vulnerabilities to the networked system. The impact of a vulnerability may be determined based on the type of data and/or the type of services that may be accessible in an attack that exploits the vulnerability. The vulnerabilities may then be ranked and addressed based on the impacts.

Systems and methods for analyzing vulnerabilities of networked systems

Methods, systems, and computer program products for performing passive and active identity verification in association with online communications. For example, a computer-implemented method may include receiving one or more electronic messages associated with a user account, analyzing the electronic messages based on a plurality of identity verification profiles associated with the user account, generating an identity trust score associated with the electronic messages based on the analyzing, determining whether to issue a security challenge in response to the electronic messages based on the generated identity trust score, and issuing the security challenge in response to the electronic messages based on the determining.

Passive and active identity verification for online communications

A method for using a malware and phishing detection and mediation platform is discussed. The method includes accessing data from one or more of a monitored portion of website data and a monitored portion of emails, the data indicating a respective potential malware or a suspect phishing element (e.g., Uniform Resource Locator (URL)). The method includes selecting one of a plurality of detection engines for processing the data, where the selecting is based on previous results of previous processing by one or more detection engines. Each of the plurality of detection engines can be for performing one or more respective investigation actions on the plurality of data to determine a particular issue with one of the monitored data. The method also includes determining a mediation action based on a result of processing of the detection engine and the previous processing.

Malware and phishing detection and mediation platform

A method for phishing detection using certificates associated with uniform resource locators (URLs) is discussed. The method includes accessing certificate portions of a certificate associated with a suspect URL, the certificate accessed at a database that includes certificates obtained by monitoring certificate logs. The method includes accessing a URL score for the suspect URL. The method includes assigning a certificate rule score based on partial certificate scores of certificate portions, the certificate rule score indicating a phishing potential for the certificate, each of the partial certificate scores indicating a likelihood of phishing of each portion based on certificate rules. The method includes using a machine learning model based on the URL score and the certificate to determine a uniqueness certificate score. The method also includes determining a phishing certificate score based on the certificate rule score and the uniqueness certificate score for the certificate.

Phishing detection using certificates associated with uniform resource locators

Methods and systems are presented for providing enriched technical security data to a risk engine of an online service provider, and for adjusting security settings based on the enriched data. The enriched security data may be generated by recursively deriving additional security information from an initial security data input. The initial security data input may be associated with a risk source, such as a person or a device that submits an electronic request to the online service provider. Based on the initial security data input, the risk engine may recursively derive additional security information that enriches the initial security data input. The risk engine may then use the derived security information as well as the initial security data input to assess a risk level of the risk source, and then adjust a security setting of the online service provider based on the assessed risk level of the risk source.

Deep intelligence context engine

Methods and systems for implementing keyboard linked authentication challenges are described. A visual representation of a first string of characters is provided for display on a client computing device. In response to the providing the visual representation for display, several keystrokes on the client computing device that produces a second string of characters are received. A determination that the second string of characters matches the first string of characters is made. A determination that no unauthorized keystrokes are included in the detected plurality of keystrokes is further made. Access is provided to the client computing device upon determining that the second string of characters matches the first string of characters, and determining that no unauthorized keystrokes are included in the detected plurality of keystrokes.

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Chandler, AZ, United States of America

Kevin Tyers