Weaponizing Data Science for Social Engineering: Automated E2E Spear Phishing on Twitter

by John Seymour, Philip Tully
Sept. 17, 2017 1 comment www.blackhat.com belen_caty Detection & Response

Social networks, especially Twitter with its access to extensive personal data, bot-friendly API, colloquial syntax and prevalence of shortened links, are the perfect venues for spreading machine-generated malicious content. We present a recurrent neural network that learns to tweet phishing posts targeting specific users. The model is trained using spear phishing pen-testing data, and in order to make a click-through more likely, it is dynamically seeded with topics extracted from timeline posts of both the target and the users they retweet or follow. We augment the model with clustering to identify high value targets based on their level of social engagement such as their number of followers and retweets, and measure success using click-rates of IP-tracked links. Taken together, these techniques enable the world's first automated end-to-end spear phishing campaign generator for Twitter.


Steven Ulm 6 months ago

Ough, just imagine the regular user of Twitter who even has no idea about these security vulnerabilities of their favorite platform...