Venator is a flexible detection platform designed to streamline rule management and deployment, utilizing Kubernetes CronJob and Helm for its operations. It is adaptable enough to function independently or in conjunction with other job schedulers like Nomad. The platform is particularly optimized for Kubernetes environments, providing a robust detection engine that emphasizes simplicity, extensibility, and ease of maintenance. One of the primary advantages of Venator is its ability to address common challenges faced by existing threat detection solutions. Many of these solutions struggle with monitoring and managing scheduled detection rules effectively. Users often encounter difficulties in verifying the success of detection jobs, troubleshooting failures, and executing backfills or ad-hoc queries. Additionally, the integration of new detection rules or log sources can introduce unnecessary complexity. Venator aims to mitigate these issues by allowing each detection rule to operate as an independent job, which facilitates flexible query execution and result handling. The operational framework of Venator involves running detection rules as separate jobs, each utilizing a designated query engine, such as OpenSearch or BigQuery. This modular approach ensures that the failure of one rule does not affect the execution of others. Each rule is defined in YAML files, specifying its query engine and the destinations for publishing results. For instance, one rule might query logs from OpenSearch and send alerts to a PubSub system, while another could pull data from BigQuery and deliver results to Slack. To enhance the accuracy of its detections, Venator incorporates exclusion lists that filter out known benign events, thereby reducing false positives. These lists are also defined in YAML format and support various logical conditions. Furthermore, Venator integrates with Large Language Models (LLMs) to improve signal analysis, particularly for lower-confidence signals that may not warrant immediate alerts. The deployment of Venator is automated through Helm, which manages configuration files, including detection rules and exclusions, as Kubernetes ConfigMaps. This automation is integrated into a CI/CD pipeline, ensuring that any updates to detection rules or code trigger new deployments automatically, keeping the system current without manual intervention. For those interested in implementing Venator, a detailed deployment guide is available, outlining the steps necessary to set up the platform using Helm and Kubernetes. Overall, Venator represents a significant advancement in threat detection technology, offering a flexible and efficient solution for managing detection rules and enhancing security operations.