Kestrel is a rapidly evolving threat hunting language designed to accelerate cyber threat hunting by providing a layer of abstraction to build reusable, composable, and shareable hunt-flow. It brings two key innovations to the security community: (i) a composable way expressing threat hypothesis development over entity-relational data abstractions, and (ii) an open-source language runtime generating and executing repetitive hunt instructions on local hunting sites, remote data sources, and in the cloud. Kestrel significantly simplifies hunting and sharing by creating a standard way to encode a single hunt step, chain multiple hunt steps, and fork/merge hunt-flows to develop threat hypothesis. It focuses threat hunters on the reusable business logic of hunt, other than writing multiple endpoint query languages, understanding incompatible query results, and converting analytics and visualization for each specific hunt. This arsenal session will showcase the latest language development and community opportunities for Kestrel. We will start with powerful federated data retrieval using the Structured Threat Information eXpression (STIX) standard and STIX-shifter and lift the results into an entity-relational data model. Then we will showcase analytic hunt steps besides data retrieval steps, compare the new Python analytics interface with the container-based interface, and execute analytics for context enrichment, de-obfuscation, and visualization. After creating, executing, saving, and re-executing huntbooks, we will connect Kestrel with the Open Command and Control (OpenC2) standard to respond to "investigate" commands and automate huntbook execution, data gathering, false positive elimination, and comprehensive analysis. Making it ready to try by the audience, we will demonstrate live hunts in Jupyter Notebooks launched and executed in a Binder cloud sandbox as part of a purple team exercise. At the end of the session, we will introduce the kestrel-huntbook repo for people to reuse existing huntbooks and share their hunting knowledge with their colleagues and other hunters in the community.