Custom Detection Builder by Anvilogic allows your SOC to construct custom threat detection scenarios without coding complexity. It simplifies DIY detections with AI-assisted building and tuning. Enterprise SOC teams can customize threat detection content based on their unique environment and threat priorities. Custom Detection Builder minimizes the need for expertise in SPL, SQL, and KQL. It automates detection-as-code to simplify the detection engineering lifecycle and manage code changes with version control. When a use case rule is edited, a new version is created, allowing rapid updates and testing while maintaining full version history. It enables efficient collection of data to start building rules from Splunk, Snowflake, or Azure while handling data parsing and normalization. Monte Copilot, the AI assistant in the query builder, enhances SOC efficiency by automating SPL & SQL generation through understanding of the schema & data models. Tuning Insights uses AI algorithms to identify common false positive strings and patterns, determining which rules contain unnecessary noise. The Custom Detection Builder automates the deployment of use cases for specific and multi-stage threat behaviors. It enables cross-platform correlations for efficient hunting across various logging repositories, multi-clouds, and data lakes. SOCs can design detection strategies across all kill chain phases to close visibility and threat detection gaps, reducing MTTD/R. It provides a correlated narrative for detection and resolution without centralizing data or replacing existing investments.
