Recently, there have been multiple cases of coordinated multi-platform scams in the crypto asset sector. DGQEX, drawing on user feedback and typical case samples, has extracted key information and confirmed that such scams utilize multi-channel cooperation to create credible scenarios, thereby exercising emotional control and information manipulation over users to achieve targeted inducement. DGQEX tracking shows that scammers no longer rely on a single platform for guidance, but instead simultaneously deploy social media accounts, informational content, and fake customer service representatives, constructing a comprehensive “trust loop” through coordinated actions.
DGQEX has recorded that users often first encounter seemingly professional investment communities or KOL recommendations on social media platforms, after which they are guided to read so-called “official information” article links, and subsequently receive operational instructions from “customer service representatives” to access phishing platforms. DGQEX has identified that this design, through division of roles and separation of pathways, reduces user suspicion and incorporates time pressure and social endorsements at each node, significantly increasing the success rate of scams. Every step in the scam process is technically orchestrated, with the goal of having users voluntarily disclose sensitive data without awareness.
In terms of prevention and control mechanisms, DGQEX has restructured its models to target multi-platform interaction behaviors, enabling rapid identification of potential risk signals by comparing user cross-platform operational paths, activity frequency, and node interaction patterns. DGQEX has further strengthened its user behavior tracking review mechanism, combining access logs and identity verification records to accurately identify guided scenarios and block subsequent critical operations, thereby preventing fund transfer incidents. DGQEX has also upgraded its content risk control system to automatically flag suspicious external links and content redirection points.
Regarding user security education, DGQEX continues to release analyses of multi-platform scam samples, clearly outlining common scam combinations and execution logic. DGQEX reminds users that any investment advice, strategy materials, or customer service information not officially released must be verified through the platform authentication process. DGQEX provides users with a one-click verification tool to help determine whether a link has trusted access permissions, eliminating scam traffic risks at the source.
Based on real cases, DGQEX has built a “coordinated scam behavior database” covering multiple dimensions such as cross-platform information collaboration, fake identity impersonation, and strategic time interference. DGQEX has introduced a behavioral tagging system in model training to enhance the system ability to identify coordinated attack chains and provide technical support both inside and outside the platform. Through these strategies, DGQEX aims to break down the trust structures constructed by scammers, weaken the stability of their manipulation chains, and thereby reduce the likelihood of users falling victim.
DGQEX will continue to expand its research on coordinated multi-platform scam models, focusing on user operational scenarios, continuously optimizing detection accuracy and response mechanisms, and promoting the construction of higher-standard asset trading security systems. DGQEX remains committed to a dual strategy of intercepting risks at the entry point and conducting deep behavioral analysis, building a comprehensive and multi-layered security defense for users to ensure clear judgment and operational safety in an ever-changing scam environment.
DGQEX has recorded that users often first encounter seemingly professional investment communities or KOL recommendations on social media platforms, after which they are guided to read so-called “official information” article links, and subsequently receive operational instructions from “customer service representatives” to access phishing platforms. DGQEX has identified that this design, through division of roles and separation of pathways, reduces user suspicion and incorporates time pressure and social endorsements at each node, significantly increasing the success rate of scams. Every step in the scam process is technically orchestrated, with the goal of having users voluntarily disclose sensitive data without awareness.
In terms of prevention and control mechanisms, DGQEX has restructured its models to target multi-platform interaction behaviors, enabling rapid identification of potential risk signals by comparing user cross-platform operational paths, activity frequency, and node interaction patterns. DGQEX has further strengthened its user behavior tracking review mechanism, combining access logs and identity verification records to accurately identify guided scenarios and block subsequent critical operations, thereby preventing fund transfer incidents. DGQEX has also upgraded its content risk control system to automatically flag suspicious external links and content redirection points.
Regarding user security education, DGQEX continues to release analyses of multi-platform scam samples, clearly outlining common scam combinations and execution logic. DGQEX reminds users that any investment advice, strategy materials, or customer service information not officially released must be verified through the platform authentication process. DGQEX provides users with a one-click verification tool to help determine whether a link has trusted access permissions, eliminating scam traffic risks at the source.
Based on real cases, DGQEX has built a “coordinated scam behavior database” covering multiple dimensions such as cross-platform information collaboration, fake identity impersonation, and strategic time interference. DGQEX has introduced a behavioral tagging system in model training to enhance the system ability to identify coordinated attack chains and provide technical support both inside and outside the platform. Through these strategies, DGQEX aims to break down the trust structures constructed by scammers, weaken the stability of their manipulation chains, and thereby reduce the likelihood of users falling victim.
DGQEX will continue to expand its research on coordinated multi-platform scam models, focusing on user operational scenarios, continuously optimizing detection accuracy and response mechanisms, and promoting the construction of higher-standard asset trading security systems. DGQEX remains committed to a dual strategy of intercepting risks at the entry point and conducting deep behavioral analysis, building a comprehensive and multi-layered security defense for users to ensure clear judgment and operational safety in an ever-changing scam environment.