Available at: http://digitalcommons.calpoly.edu/theses/1592
Date of Award
MS in Computer Science
Dr. Bruce DeBruhl
Cyber attacks are a growing concern in our modern world, making security evaluation a critical venture. Penetration testing, the process of attempting to compromise a computer network with controlled tests, is a proven method of evaluating a system's security measures. However, penetration tests, and preventive security analysis in general, require considerable investments in money, time, and labor, which can cause them to be overlooked. Alternatively, automated penetration testing programs are used to conduct a security evaluation with less user effort, lower cost, and in a shorter period of time than manual penetration tests. The trade-off is that automated penetration testing tools are not as effective as manual tests. They are not as flexible as manual testing, cannot discover every vulnerability, and can lead to a false sense of security. The development of better automated tools can help organizations quickly and frequently know the state of their security measures and can help improve the manual penetration testing process by accelerating repetitive tasks without sacrificing results.
This thesis presents Automated Network Exploitation through Penetration Testing (ANEX), an automated penetration testing system designed to infiltrate a computer network and map paths from a compromised network machine to a specified target machine. Our goal is to provide an effective security evaluation solution with minimal user involvement that is easily deployable in an existing system. ANEX demonstrates that important security information can be gathered through automated tools based solely on free-to-use programs. ANEX can also enhance the manual penetration testing process by quickly accumulating information about each machine to develop more focused testing procedures.
Our results show that we are able to successfully infiltrate multiple network levels and exploit machines not directly accessible to our testing machine with mixed success. Overall, our design shows the efficacy of utilizing automated and open-source tools for penetration testing.