Advanced Hacker Forum Use Collection and Classification Methods for Preventive Cyber Threat Intelligence

The issue of cyber dangers has become a major concern for society. In response to the increasing danger of cyberattacks, businesses have started making significant investments in the creation of “Cyber Threat Intelligence (CTI)” in recent years. Reactive ‘CTI’ is essentially a data-driven process that many firms have historically produced by gathering and analyzing data from internal log files. The community of online hackers can provide a great deal of proactive CTI value by warning companies about problems they had no prior knowledge about. Among other ‘platforms’ and ‘forums’ offer the most extensive ‘metadata’ and data durability, and tens of thousands of publicly available Tools, Techniques, and Procedures (TTP). On the other hand, forums frequently use anti-crawling techniques including obfuscation, throttling, and authentication. Many researchers have been forced to use batch collections due to these restrictions. In order to collect hacker exploits continuously, this exploratory study will build a novel web crawler that is enhanced with a variety of anti-crawling countermeasures. Additionally, it will use a cutting-edge deep learning technique called ‘Recurrent neural networks’ with 'long short-term memory (LSTM)‘ and RNNs can automatically categorize exploits into pre-established groups on the fly. Lastly, it will produce interactive visualizations that researchers and “CTI” practitioners can use to review gathered vulnerabilities for prompt, proactive “CTI”. The study's findings show that compared to other sorts of exploits, system and network exploits are distributed far more frequently among other things.