Penetration testing is a security test that involves using the vulnerabilities to discover other vulnerabilities in the system and execute malicious code. These tests are especially important for protecting against data mining and preventing security exploits.
Penetration testing includes a number of techniques used to test the security of a network. These technologies include scanning networks, firewalls, security monitoring systems, and artificial intelligence. Artificial intelligence can analyze security tests using techniques developed to reveal network vulnerabilities.
AI can enable you to achieve more comprehensive and effective results with specialized algorithms designed for use in penetration testing and automatically performed security tests.
Benefits of Using AI for Penetration Testing
Today, the rapid development of technology and the ever-increasing security requirements of users have revealed the need to use AI technologies in security tests. Using AI to improve security provides much faster and more efficient results, eliminating the need for time-consuming manpower to perform the often customized and complex security tests. AI helps in finding vulnerabilities as early as possible. It can also perform unique and complex security testing, making it easier to spot vulnerabilities.
The AI appears to be quite successful, especially when it comes to detecting and preventing an attack. To train artificial intelligence, huge data sets are required. An application with high web traffic is an advantage in this regard. Because you can treat each incoming traffic like a dataset for AI to use. Thus, you have an AI that can read and analyze web application traffic and detect threats. This is one of the simplest examples that can be given.
It can pre-detect not only web traffic but also a lot of malware for your app or device. This method has already started to be used by many firewalls.
Apart from all this, human error is one of the biggest problems in cyber security. A minor code vulnerability that goes unnoticed can lead to major irreversible security problems. Some plugins that scan for vulnerabilities in code have emerged with the development of AI, and they warn developers about such issues. So far, they have shown some success in curbing human errors.
In addition, the response time shown against a threat is also very important. During an attack, it takes time to detect an attack, plan a route to defense, and launch defense systems. But AI is very helpful in this regard.
Limitations of AI in Cyber Security
Using AI for cyber security purposes is essential to identify and analyze malicious, clean and potentially insecure applications. Even if you use a very large dataset to train the algorithm, you still cannot be sure of the result. As a result, it is not safe to rely solely on machines and AI. It is necessary to support AI technology with human intervention.
Some security appliance manufacturers claim that solutions powered by machine learning can analyze each instance. According to the manufacturers, these tools can detect malware using only mathematical methods. However, this is hardly possible.
A very good example of this is Alan Turing’s cracking of the Enigma code during World War II. Even a perfect machine cannot decide whether an unknown input is likely to cause unwanted behavior in the future. This certification can be applied in many different areas including cyber security.
Another serious limitation of machine learning applications in cyber security lies within the limits of artificial intelligence models. For example, machines have become smart enough to beat humans at chess.
But there are some rules of chess. Chess engines do not deviate from these rules. When it comes to cyber security, attackers often have no rules. The ever-changing nature of the digital landscape makes it impossible to create a single security solution that can detect and prevent all future threats.
Source Code Analysis with ChatGPT
ChatGPT developed by OpenAI has made serious inroads into our lives in many fields. As you can ask some questions and chat with ChatGPT, it also tries to help you with programming and software issues. ChatGPT also tries to do source code analysis, if you look at it from a cyber security perspective. But ChatGPT is still in its infancy and will take some time to get up and running.
To see this better, let’s test the power of ChatGPT. For example, below is a simple JavaScript code that creates an XSS vulnerability. Let’s ask ChatGPT about this code and tell it about any vulnerabilities.