Automatic penetration test path planning method and system based on agent collaboration

By using an automated penetration testing path planning method based on intelligent agent collaboration, the problem of existing technologies being unable to identify cross-node and cross-security domain attack paths for complex heterogeneous systems is solved, enabling in-depth security assessment and adaptive path adjustment for complex heterogeneous systems.

CN122053178APending Publication Date: 2026-05-15BEIJING YUHONG XINAN TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202610225498.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-25
Publication Date
2026-05-15

AI Technical Summary

Technical Problem

Existing automated penetration testing techniques cannot effectively identify complex attack paths across nodes and security domains in complex heterogeneous systems, lack global attack modeling capabilities, and are difficult to meet the needs of in-depth security assessment.

Method used

An automated penetration testing path planning method based on agent collaboration is adopted. Data interaction between multiple agents is realized through a shared blackboard mechanism. The agent receives the penetration testing target range input by the user, performs information collection and matching, generates a global attack map, and provides real-time feedback on the execution results and dynamically updates the path planning.

Benefits of technology

It enables in-depth security assessment of complex heterogeneous systems, identifies attack paths across nodes and security domains, and improves the depth coverage and adaptive path adjustment capabilities of penetration testing.

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Abstract

The invention discloses an automatic penetration test path planning method and system based on agent collaboration, and relates to the technical field of network security. Performing initialization starting on the plurality of intelligent agents based on the penetration test target range; collecting the target system and writing the target system into a shared blackboard mechanism; matching the asset feature information with a preset vulnerability knowledge base according to the test strategy mode to generate vulnerability utilization conditions, and constructing a global attack graph according to the asset feature information and the vulnerability utilization conditions; generating an attack path based on the global attack map, executing an attack operation on the target system according to an attack step sequence of the attack path, when an execution result is failure, updating the global attack map according to a feedback failure result, and re-planning to generate a new attack step sequence; and when the execution result is successful, generating a penetration test report for the penetration test target range according to the success result. By implementing the method, the actual demand of deep security assessment of the complex heterogeneous system is met.
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