Abstract: Detecting and preventing phishing attacks in real-time features protection of users from feeding sensitive data to phishing sites, educating users for theft awareness, and protecting enterprise credentials. A requested document traversing a gateway is embedded with a detection module. When a user accesses the document, the embedded detection module is executed in the context of the document, checks if the document is prompting the user for sensitive information, determining if the document is part of a phishing attack, and initiates mitigation, warning, and/or education techniques.

Abstract: Actively and passively monitoring current network security threats and impact, to evaluate and maintain cyber security includes using an innovative combination of threat feed, impact assessment, client profile, security policy, and vulnerability report to determine impact of malware, evaluate and maintain security policy, decrease vulnerability, and dynamically implement solutions to prevent malware attacks. Constantly re-evaluating the customer's cyber security implementation facilitates dynamic tuning of cyber security implementation.

Abstract: Detecting and preventing phishing attacks in real-time features protection of users from feeding sensitive data to phishing sites, educating users for theft awareness, and protecting enterprise credentials. A requested document traversing a gateway is embedded with a detection module. When a user accesses the document, the embedded detection module is executed in the context of the document, checks if the document is prompting the user for sensitive information, determining if the document is part of a phishing attack, and initiates mitigation, warning, and/or education techniques.

Abstract: Detecting and preventing phishing attacks in real-time features protection of users from feeding sensitive data to phishing sites, educating users for theft awareness, and protecting enterprise credentials. A requested document traversing a gateway is embedded with a detection module. When a user accesses the document, the embedded detection module is executed in the context of the document, checks if the document is prompting the user for sensitive information, determining if the document is part of a phishing attack, and initiates mitigation, warning, and/or education techniques.

Abstract: To validate data, a plurality of strings that match a predetermined regular expression is extracted from the data. A validated subset of the strings is identified. To determine whether the validated subset has been falsely validated, it is determined whether the validated subset satisfies each of one or more predetermined criteria relative to the plurality of strings. In one embodiment, the subset is determined to be falsely validated if at least one of the criteria is satisfied. In another embodiment, the subset is determined to be falsely validated if all of the criteria are satisfied. The data are released only if the subset is determined to be falsely validated.