Security-Optimized LLM Integration Technology
No matter how accurate detection may be, the process of interpreting results and deciding on response actions has traditionally remained complex and time-consuming. ClumL solves this challenge by replacing inefficient, manual reporting with an innovative application of LLMs. By analyzing detection results from the AI Clustering Engine through LLM-powered reasoning, security teams are freed from repetitive tasks, allowing them to focus on critical analysis and respond to threats quickly and accurately
Principle and Structure
ClumL utilizes diverse large-scale and up-to-date LLMs, the most comprehensive libraries of threat intelligence, to generate reports that deliver precise and actionable insights.
- Safeguards are built in to prevent unsupported reasoning (“hallucination”), ensuring the reliability of analysis.
- Integration with various Threat Intelligence (TI) sources removes low-confidence elements, strengthening both detection and analytical accuracy.
Three-Stage LLM-Integrated Automated Analysis & Reporting
What happened?
So what?
Now what?
- Summarizes the objective facts of the detected anomaly
- Includes technical details such as IP addresses, affected systems, and behavioral patterns
- Explains the security significance and potential risks of the event
- Provides correlations with known attack patterns, related cases, and possible threat scenarios
- Provides concrete response recommendations
- Distinguishes between immediate actions and areas requiring further investigation, with guidance on step-by-step response procedures
What happened?
- Summarizes the objective facts of the detected anomaly
- Includes technical details such as IP addresses, affected systems, and behavioral patterns
So what?
- Explains the security significance and potential risks of the event
- Provides correlations with known attack patterns, related cases, and possible threat scenarios
Now what?
- Provides concrete response recommendations
- Distinguishes between immediate actions and areas requiring further investigation, with guidance on step-by-step response procedures
Key Features
AI Clustering-Based LLM Integration
- Only detection results validated by AI clustering are passed to the LLM, delivering precise, security-context-optimized analysis.
Natural-Language Interpretation & Automated Reporting
- The LLM interprets detected threats in natural language and automatically generates professional security analysis reports with actionable insights.