Dragnet is a social engineering framework which aims to increase conversions on SE engagements. This is achieved by making use of previous conversion data, correlating this against open source data points collected on your previous and current targets, and then suggesting the best template, pretext or method of attack for your new target(s). As we see machine learning become more prevalent every day, the importance of strong personal privacy becomes clearer than ever.
Dragnet v0.1 has been released, and we're hard at work on the next iteration. There's plenty of work to do, but we're proud to be on the cutting edge of what we feel is an extremely important part of offensive security- leveraging the mass data that's already out there and opening the public's eyes to the dangers they face in this social day & age.
Dragnet is built on a Vue.js front end, making use of the Firebase NOSQL backend, Asterisk for VoIP, Node.js & Express for the endpoint, and Tensorflow for machine learning. Things are constantly evolving, so if you have any ideas or if you'd simply like to take Dragnet for a spin, head over to the repo at https://github.com/tevora-threat/dragnet and check it out!
If you're more of the visual type, check out our Dragnet talk at GrrCON 2018:
First, Dragnet collects dozens of OSINT data points on past and present social engineering targets. Then, using conversion data from previous engagements, Dragnet provides recommendations for use on your current targets: phishing templates, vishing scripts and physical pretexts- all to increase conversions with minimal effort. Finally, features like landing page cloning and domain registration (alongside your standard infrastructure deployment, call scheduling and email delivery) make Dragnet one hell of a catch.