Recent global events such as COVID-19 have boosted our use of technology, however, cyber security is not yet a priority for most. Meanwhile, cybercriminals profit from this situation by selling their malware and hacked information on Darknet Markets (DNMs). To date, research has tended to focus on the importance of drugs in DNMs rather than in Cyber Security-Related Products (CSRP). However, few researchers have been able to draw methods to identify CSRP in DNMs. This thesis collects data from DNMs to carry out a quantitative analysis of CSRPs. The data is collected using our own crawler called Midnight Sea (MS) and labelled using models of Natural Language Processing (NLP). Contrary to common belief, the results revealed that CSRPs are inexpensive, showing that products such as ransomware can be bought for less than 20 EUR.