Abstract: Automated penetration testing can greatly reduce the cost of penetration testing by automating the process of manually finding possible attack paths.Existing methods mainly use a single agent to perform attack tasks,which leads to long execution of attack actions and low penetration efficiency.If multi-agent cooperative attack is considered,the state space scale of planning problem will grow exponentially due to the multi-dimensional local state of each agent.Aiming at the above problems,a team cooperative attack planning method based on multi-agent jointdecision is proposed.Firstly,the multi-agent cooperative attack path planning problem is transformed into the attack target assignment problem under the jointdecision constraints,and themulti-agent centralized decision-making mode is established.Secondly,the joint decision vector matrix JDVM is used to calculate the penetration attack reward based on the CDSO-CAP model,and the greedy strategy is used to search the optimal target of attack.The experimental results show that compared with the single agent planning method,the proposed method has similar algorithm convergence with shorter execution rounds.Thus it is more suitable for rapid attack planning in multi-target network scenarios.

Key words: Agent, Attack planning, Automation, Joint decision, Penetration test, Team collaboration