This invention discloses a multi-agent collaborative dynamic
scenario self-calibration
system for network ranges, belonging to the field of network ranges. It includes: a
scenario configuration module, an asset identification agent, a penetration agent, and a dynamic calibration module. The
scenario configuration module receives training targets, skill levels, and scenario parameters, generating an initial scenario configuration. The asset identification agent, based on the initial scenario configuration, identifies the actual asset status of each
virtual machine in the range in real time, generating an asset topology map and a real asset
list. The penetration agent, based on the real asset
list, simulates
vulnerability attacks and records the
verification results. The dynamic calibration module, based on the initial scenario configuration and the real asset
list, automatically adjusts the asset configuration and
vulnerability candidate set; and based on the
verification results and skill levels, dynamically adjusts the
vulnerability candidate set and triggering conditions,
synchronizing them to the scenario configuration module. This solution can improve range operation efficiency, reduce manual
verification costs, and achieve automated closed-
loop optimization.