Torsion: Web Reconnaissance using Open Source Intelligence

Internet technology has made surveillance widespread and access to resources at greater ease than ever before. This implied boon has countless advantages. It however makes protecting privacy more challenging for the greater masses, and for the few hacktivists, supplies anonymity. The ever-increasing frequency and scale of cyber-attacks has not only crippled private organizations but has also left Law Enforcement Agencies(LEA's) in a fix: as data depicts a surge in cases relating to cyber-bullying, ransomware attacks; and the force not having adequate manpower to tackle such cases on a more microscopic level. The need is for a tool, an automated assistant which will help the security officers cut down precious time needed in the very first phase of information gathering: reconnaissance. Confronting the surface web along with the deep and dark web is not only a tedious job but which requires documenting the digital footprint of the perpetrator and identifying any Indicators of Compromise(IOC's). TORSION which automates web reconnaissance using the Open Source Intelligence paradigm, extracts the metadata from popular indexed social sites and un-indexed dark web onion sites, provided it has some relating Intel on the target. TORSION's workflow allows account matching from various top indexed sites, generating a dossier on the target, and exporting the collected metadata to a PDF file which can later be referenced.