The State Grid Information and Telecommunications Center of China announced that it has successfully piloted an artificial intelligence-powered cybersecurity system, transforming its defensive operations covering its operational technology from a labor-intensive model into an automated, high-speed security network.
In a recent simulation conducted by the center’s network and data security department, technicians quoted across local Chinese media this week apparently used the new AI infrastructure to automatically build a mock cyberattack range. Within 10 minutes, the system utilized large language models to detect eight common types of web vulnerabilities and generated a detailed report mapping out nearly 50 predefined flaws. Previously, completing the exact same diagnostic process required a senior security engineer to work for an entire week.
Developed in collaboration with the State Grid Information and Telecommunications Industry Group of China, the initiative forms a dual-capability offensive and defensive AI security architecture. The framework is designed to upgrade the state-owned utility giant’s operational technology digital defenses toward autonomous intelligence.
On the offensive front, the parties claim that the system acts as a proactive mechanism to discover hidden vulnerabilities. By utilizing large language models to aggregate historical data and linking them with security monitoring hardware, the AI automatically extracts attack signatures. Throughout more than 20 rounds of automated simulation testing, the system reportedly generated over 150 valid test cases and defensive configuration recommendations. Crucially, the AI successfully identified eight deep-seated business logic flaws—vulnerabilities that are highly concealed and notoriously difficult for traditional scanning tools to catch—by analyzing the contextual logic of past breaches.
On the defensive side, the system targets automated maintenance and intelligent operations to significantly reduce manual workloads. By evaluating business traffic patterns against baseline security policies, the AI automatically generates and deploys firewall strategies. It cleans up redundant or overly permissive access rules to enforce a strict policy of least privilege, reducing the manual labor required for firewall configuration by 90%.
Furthermore, the technology tackles the challenge of parsing tens of thousands of daily security alerts culled from terabytes of logs. Relying on large model reasoning, the AI filters and analyzes massive volumes of log data to isolate genuine threats and reconstruct entire attack chains. This automated tracing cuts the average incident investigation time from approximately one hour down to just 10 minutes.
Moving forward, the State Grid tech center plans to deepen its deployment of multi-agent AI systems. The ultimate objective is to provide a round-the-clock, real-time security baseline capable of executing second-level threat responses to safeguard China's national power grid infrastructure.