AutoPentest-DRL – Automated Penetration Testing Using Deep Reinforcement Learning

AutoPentest-DRL is an automated penetration testing framework based on Deep Reinforcement Learning (DRL) techniques. The framework determines the most appropriate attack path for a given network, and can be used to execute a simulated attack on that network via penetration testing tools, such as Metasploit. AutoPentest-DRL is being developed by the Cyber Range Organization andRead More