First release of AutoPentest-DRL, an automated penetration testing framework based on Deep Reinforcement Learning (DRL) techniques. The framework can determine the most appropriate attack path for a given logical network, and can also be used to execute a penetration testing attack on a real network via tools such as Nmap and Metasploit.