Within the first three months of 2018, around 686 cybersecurity attacks were reported, out of which almost 39 percent of the attacks accounted for unauthorized access into the system. With the increasing number of data and security breach attacks, it is evident that while modern software architecture might be adaptable, advanced, and data-intensive, it is still vulnerable when it comes to security configuration. Even though digitization and the advancement in technology have taken the digital world by storm, yet it still exposes the organizations too numerous vulnerabilities which makes their security a serious challenge.

Penetration Testing 101

Penetration testing is an essential component of the cybersecurity tool kit; it involves carrying out an attack in a controlled environment on the computer system of the organization to assess their security strengths and weaknesses. The most effective penetration testing companies assimilate vulnerability assessment, threat intelligence, and human skills to evaluate the criticality of the system’s weaknesses through simulated attacks on the information technology system. An effective pen testing strategy measures the network security protocols for its sturdiness and detects any weak spots, backdoors, and gaps in the security tools which can potentially be used as an attack vector. The severity and impact of the probable risk are calculated and the risk is prioritized accordingly.

How Artificial Intelligence Amplifies Penetration Testing?

Penetration testing companies are now integrating artificial intelligence and machine learning tools with pen testing techniques to improve the testing process and to mitigate the security risks as well. There are many ways in which artificial intelligence and machine learning can meaningfully contribute to the penetration testing procedure. The penetration testing generally collects large amounts of data for the security assessment, and artificial intelligence can be used here to substantially reduce the noise and filter the data so that it is processed more quickly. Apart from being time-efficient, this also enhances the usability of the results, and data scanning powered by artificial intelligence is much more likely to produce actionable insights. With artificial intelligence as a part of the pen testing process, it is easier for the companies to scale the testing process and make it much more consistent.

Stages of Pen-Testing that Artificial Intelligence Can Impact

– Reconnaissance stage – the success of the penetration test is directly proportional to the quantity of data that is gathered; the higher the volume of the collected data, the higher the probability of success is. Thus, using AI in this stage would not only save the time of testers in gathering and filtering data, but it would also allow them to see various details that were missed previously.

– Scanning stage – with the help of AI, the testers are able to develop comprehensive coverage in this phase and adjust the code so that the derived insights can be understood in a better light.

– Gaining and maintaining access stage – through the AI-based algorithms, the system could come up with countless password attempts to gauge the security strength and check if it’s susceptible to a breach.