AI Changing Pen Testing Game Worldwide

The need for penetration testing services arose a century back when the attacks on the systems became frequent. Lots of companies started losing their sensitive data and it affected their customers in the worst way possible.

The loss of sensitive data is exactly when (and why) the world saw another technical industry rising.

You can see one pen testing company giving way to a whole new industry of penetration testing. The company collected the best tech brains and asked them to come up with solutions to stop cybercriminals from harming organizations and individuals.

However, the field of cybercriminals and testers changes faster than any other technical field.

Cyber Criminals keep coming up with new sorts of viruses and cyber-attacks. To save people from falling into these traps, testing companies needed to evolve enough to plan for these viruses and stay one step ahead of the criminals.

Let’s dive into the history of penetration testing to see how it has evolved over time.

Penetration Testing in the Beginning

Businesses always had a reason to opt for penetration testing to stay at a great distance from malware and other viruses.

First of all, penetration testing was only designed for systems — making them secure from every angle. Soon it was discovered that a business can be targeted through phishing and social presence as well.

The multi-angled attacks forced penetration testing companies to come up with solutions for every possible cyber threat.

Most of the time, testing was done manually where a team of testers would sit together, understand the software, list down all the requirements, and build test cases.

These test cases were then run one by one and the status of every test case was recorded. In the end, a report was prepared for the developers to understand the possible loopholes present, ways to recreate them, and ideas to cover them.

Different techniques were introduced in the market to suit different requirements of the people.

However, the steps were almost always the same since it involved a team of human testers to carry out all the activities. Then came the era of more advanced technologies; ones powered by artificial intelligence and machine learning.

The Machine Learning tech was smart but was unguarded and open for the cybercriminals to attack and get hang of it.

Although every pen testing company felt it was a good idea to use manual testing for this new category of tech, IoT, they failed most of the time. The failure clearly called for new ways to be devised and used for the betterment of the organizations and individuals using AI and ML technology gadgets.

The Era of Artificial Intelligence and Machine Learning

Although testers were trying their best to fight new cyber threats with the help of manual testing, they lost the battle many times.

In the hands of criminals, Artificial intelligence started becoming more of a threat rather than being a blessing.

When AI became a threat to criminals is when the world of pen testing introduced a new turn in history.

Artificial intelligence and machine learning were made a part of penetration testing. Different AI and ML techniques and tools were developed to help catch malware and viruses present in the system.

Now, you must be wondering if artificial intelligence is so strong in the hands of criminals, should it not offer more benefits when used for pen testing?

Obviously, it should offer more benefits with pen testing — so here is how penetration testing companies are evolving with AI and ML embedded in their technologies and techniques:

Better Information Gathering

One of the most important stages of the whole pen-testing activity is gathering information. It is also known as the reconnaissance stage.

According to experts, if the testers manage to gather more data, in the beginning, the chances of their success gets even more than double.

However, it is easy to say that and a lot difficult to do. In a pen testing activity, the team has only a limited amount of time to spend on gathering data. It is hard to ensure that the quality of the gathered data is the best.

With AI as constant support, a great amount of quality data can be gathered in a limited amount of time. One can even make use of Computer Vision, Natural Language Processing, and Machine Learning to ensure a good profile of data is built with lots of details.

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