About SOCLabs

The cybersecurity defense field faces a unique dilemma—unlike learning attack techniques which tend to be intuitive, defensive knowledge is often abstract and difficult to grasp. Many security professionals experience their first 'real combat' only when facing an actual network attack. Prior to this, they have virtually no opportunity to encounter and identify the various tactics, techniques, and malware employed by attackers.

Defense work requires mastering extensive technical knowledge, yet suffers from scattered and unsystematic learning resources. Faced with numerous similar security products in the market, professionals struggle to identify core differences and find it even more challenging to assess their actual value from an enterprise security strategy perspective. Most critically, there are almost no channels outside the workplace to access these advanced defense tools, or professionals must spend substantial time building test environments themselves, significantly increasing the cost of learning.

Detection engineers must construct test environments and simulate attacks before writing rules, a process that's often time-consuming and labor-intensive. This learning approach, disconnected from actual enterprise scenarios, makes it difficult to ensure rules remain effective in complex and dynamic real environments. The significant differences between test data and actual production environments frequently result in rules requiring multiple adjustments after deployment.

Threat hunters are like those searching for faint attack signals in an 'ocean of data.' Without enterprise-level environments, they lack both massive real data for analysis and sufficient authentic attack samples for training, making hypothesis verification and skill improvement exceptionally difficult. In actual work situations, they often struggle to discover advanced persistent threats due to insufficient experience and accumulated knowledge.