Summary

In this chapter, we discussed using ML with Python and how we can apply it to the cyber security domain. There are many other wonderful applications of data science and ML in the cyber security space related to log analysis, traffic monitoring, anomaly detection, data exfiltration, URL analysis, spam detection, and so on. Modern SIEM solutions are mostly built on top of machine learning, and a big data engine is used to reduce human analysis in monitoring. Refer to the further reading section to see the various other use cases of machine learning with cyber security. It must also be noted that it is important for pen testers to have an understanding of machine learning, in order to find vulnerabilities. In the next chapter, the user is going to understand how they can use Python to automate various web application attack categories, which include SQLI, XSS, CSRF, and...