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One of the ways in which attackers try to steal sensitive information fromcorporations is by sending spearphishing emails. This type of emails typicallyappear to be sent by one of the victim's coworkers, but have instead beencrafted by an attacker. A particularly insidious type of spearphishing emailsare the ones that do not only claim to come from a trusted party, but wereactually sent from that party's legitimate email account that was compromisedin the first place. In this paper, we propose a radical change of focus in thetechniques used for detecting such malicious emails: instead of looking forparticular features that are indicative of attack emails, we look for possibleindicators of impersonation of the legitimate owners. We presentIdentityMailer, a system that validates the authorship of emails by learningthe typical email-sending behavior of users over time, and comparing anysubsequent email sent from their accounts against this model. Our experimentson real world e-mail datasets demonstrate that our system can effectively blockadvanced email attacks sent from genuine email accounts, which traditionalprotection systems are unable to detect. Moreover, we show that it is resilientto an attacker willing to evade the system. To the best of our knowledge,IdentityMailer is the first system able to identify spearphishing emails thatare sent from within an organization, by a skilled attacker having access to acompromised email account.

That Ain't You: Detecting Spearphishing Emails Before They Are Sent