Abstract: A system and method for detecting phishing cyberattacks. The method involves parsing a code segment retrieved using a suspect uniform resource locator (URL) to identify any links included in the code segment. From these links, additional code segments may be recovered in accordance with a code segment recovery scheme. Thereafter, analytics are performed on the retrieved and possibly recovered code segments. The analytics include determining whether any of the code segments is correlated with a code segment associated with a known prior phishing cyberattack. Upon completing the analytics, an alert message including meta-information associated with results from the analytics is generated to identify that the URL is associated with a known prior phishing cyberattack when one or perhaps a combination of code segments associated with the URL are correlated to any code segment associated with a known prior phishing cyberattack.

Abstract: Techniques for an email-security system to detect multi-stage email scam attacks, and engage an attacker to obtain additional information. The system may analyze emails for users and identify scam emails by analyzing metadata of the emails. The system may then classify the scam emails into particular classes from among a group of scam-email classes. The system may then engage the attacker that sent the scam email. In some instances, the scam emails may be multi-stage attacks, and the system may automatically engage the attacker to move to the next stage of the scam attack. For instance, the system may send a lure email that is responsive to the particular scam class to prompt or provoke the attacker to send more sensitive information, such as a phone number, a bank account, etc. The system may then harvest this sensitive information of the attacker, and use that information for various remedial actions.

Abstract: A system and method for detecting phishing cyberattacks. The method involves parsing a code segment retrieved using a suspect uniform resource locator (URL) to identify any links included in the code segment. From these links, additional code segments may be recovered in accordance with a code segment recovery scheme. Thereafter, analytics are performed on the retrieved and possibly recovered code segments. The analytics include determining whether any of the code segments is correlated with a code segment associated with a known prior phishing cyberattack. Upon completing the analytics, an alert message including meta-information associated with results from the analytics is generated to identify that the URL is associated with a known prior phishing cyberattack when one or perhaps a combination of code segments associated with the URL are correlated to any code segment associated with a known prior phishing cyberattack.