What problem does it solve? Writing YARA rules that catch malware without flooding analysts with false positives is hard: poor string selection, unbounded regex, and missing goodware validation cause slow scans and unreliable detections. This Skill guides the authoring of high-quality YARA-X rules with proven conventions, decision trees, and validation tooling. ## Core Features & Use Cases - Rule Authoring Guidance: Covers naming conventions, string selection judgment, condition ordering for short-circuit performance, and required metadata for production rules. - Platform-Specific Detection: Provides patterns for Windows PE, macOS Mach-O, JavaScript/npm supply chain attacks, Chrome extensions (crx module), and Android apps (dex module). - Validation Scripts: Includes an atom analyzer and linter to check string quality, atom extraction efficiency, and YARA-X syntax compliance before deployment. - Use Case: You receive samples of a new LockBit variant. Use this Skill to extract candidate strings with yarGen, filter out generic API names, write a rule with proper metadata and cheap-first conditions, then validate it against a goodware corpus with zero false positives before deploying. ## Quick Start Ask the AI to write a YARA-X rule detecting a specific malware family from your samples, following the naming convention and validating it with the atom analyzer script.