In the ever-changing landscape of cyberspace, securing digital assets has become a
top priority for both businesses and individuals. Cybersecurity experts must stay one
step ahead of cyber criminals as they employ increasingly sophisticated techniques to
exploit vulnerabilities.
Enter the world of automated penetration testing, a novel approach that combines the
capabilities of cutting-edge artificial intelligence with the knowledge of cybersecurity
experts. In this new era of cyber defence, these digital fortresses not only fortify
themselves but also dynamically adapt to the onslaught of threats, ensuring robust
testing and vulnerability assessment generating. Here it is discussed how manual
penetration testing can be improved using automation to save time and effort while
maximizing the quality of the vulnerability assessment. The output of the automation
will take time, and to improve the accuracy of the result without human errors,
automation will take a lot of time because of the large variety of vulnerability
assessment techniques. To improve the efficiency of automation, this is where artificial
intelligence comes in and makes automation more effective.
KEYWORDS: cybersecurity, exploit, vulnerabilities, automated penetration testing, automation, artificial intelligence
open a terminal
sudo su
apt-get install python3-pip
pip install beautifulsoup4
pip install docopt
pip install jinja2
pip install Keras
pip install matplotlib
pip install msgpack-python
pip install numpy
pip install pandas
pip install Scrapy
pip install tensorflow
pip install urllib3
pip install protobuf
server_host : 192.168.12
server_port : 55553
msgrpc_user : admin
msgrpc_pass : admin
msfdb init
msfconsole
load msgrpc ServerHost=192.168.220.144 ServerPort=55553 User=admin Pass=admin
python3 ./javelin.py <source_ip> -m <mode>
ex: python3 ./javelin.py 192.168.1.3 -m test
I wish to express my deepest gratitude to my project supervisor, Mr. Chamindra Attanayake, for their invaluable guidance, patience, and unwavering support throughout this project. Their depth of knowledge and practical insights were instrumental in the successful completion of this work.
I am also thankful to all the faculty members in the faculty of computing at NSBM green university and the University of Plymouth for their help and support. Their teachings and encouragement provided the foundation for this project. I would like to thank the Open Worldwide Application Security Project (OWASP), the services of which were pivotal in gathering data and conducting experiments that were crucial to this project.
I would also like to acknowledge my peers for their camaraderie, constructive criticism, and intellectual discussions which helped shape this project. Lastly, my heartfelt appreciation goes to my family and friends, whose constant encouragement and moral support were invaluable. Their belief in my capabilities inspired me to push my boundaries and strive for excellence.