The Threat Intelligence Collaborative Blocking System is equipped with dual attack detection engines. When a medium to high-risk attack is detected in a user's traffic, it instantly coordinates with the Threat Intelligence Center and network-wide threat intelligence blocking devices, achieving the effect of "one-point monitoring, network-wide blocking."

The endpoint attack intrusion clue investigation does not rely on signature matching but focuses on behavior tracking. It monitors application behavior at the memory and CPU instruction level. Using memory monitoring technology, it effectively bypasses various operating system restrictions to achieve granular monitoring of program execution. This enhances threat detection rates while reducing false positives, effectively defending against binary exploitation attacks.

A holographic database is created for all network files, IPs, and domains. Upon detecting malicious programs, analysts can conduct network-wide investigations using critical information to determine their scope and severity across other endpoints. This process helps assess whether a systemic security incident has occurred and further identifies attackers' indicators of compromise (IOCs). With the automated detection capabilities of the Threat Sample Behavior Analysis System, gray files can be automatically classified as threats, enabling network-wide threat visualization and management.

Traditional defense methods struggle to identify advanced social engineering phishing emails. To address this, targeted key technologies are used to detect and identify the attacker’s intent.