  In our current society, the inter-connectivity of devices provides easy
access for netizens to utilize cyberspace technology for illegal activities.
The deep web platform is a consummative ecosystem shielded by boundaries of
trust, information sharing, trade-off, and review systems. Domain knowledge is
shared among experts in hacker's forums which contain indicators of compromise
that can be explored for cyberthreat intelligence. Developing tools that can be
deployed for threat detection is integral in securing digital communication in
cyberspace. In this paper, we addressed the use of TOR relay nodes for
anonymizing communications in deep web forums. We propose a novel approach for
detecting cyberthreats using a deep learning algorithm Long Short-Term Memory
(LSTM). The developed model outperformed the experimental results of other
researchers in this problem domain with an accuracy of 94\% and precision of
90\%. Our model can be easily deployed by organizations in securing digital
communications and detection of vulnerability exposure before cyberattack.
