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This invention relates to the field of network security technology and discloses a proactive threat hunting and attribution method for AI agents and honeypot-based technology. The method deploys a threat-aware agent at the network boundary to continuously capture inbound and outbound data packets, performs protocol parsing and payload feature extraction on the packets, generates network behavior fingerprints, and matches them in real-time with a known attack signature database. When the matching degree exceeds a dynamic threshold, a high-interaction honeypot environment is activated to simulate real business services, inducing attack traffic to enter and perform isolation operations. The entire operation sequence of the attack traffic within the honeypot environment is recorded, generating an attack behavior graph based on this. The attribution analysis agent extracts persistent connection points and timestamps from the graph, reconstructs the attack path, and performs correlation analysis with a threat intelligence database, outputting an attribution report. This method effectively improves network security protection capabilities and can better cope with complex and ever-changing network attack environments.