Skill UI

This guide provides a comprehensive framework for minimizing cloud expenditure on Databricks. It covers identifying cost drivers via system billing tables, implementing cluster policies, utilizing spot instances for batch processing, right-sizing SQL warehouses, and automating the shutdown of idle development clusters. Use it when managing cloud spending or optimizing data platform usage.

A comprehensive guide for establishing robust, enterprise-grade access control within Databricks. Covers implementing Single Sign-On (SSO) via SCIM, leveraging Unity Catalog for fine-grained Role-Based Access Control (RBAC), defining cluster policies, and enforcing data governance measures like Row-Level Security (RLS) and column masking. Essential for large-scale, secure data platforms.

A comprehensive runbook detailing incident response procedures for failures within the Juicebox AI platform. It guides technical users through diagnosing and resolving critical issues such as API outages, data corruption, quota exhaustion, and export failures, ensuring minimal downtime for recruiting and talent intelligence workflows.

This expert skill performs non-intrusive static analysis to thoroughly audit AI skills and bundles. It identifies malicious patterns, data leaks, system stability risks, and obfuscated payloads across major operating systems (Windows, macOS, Linux/Unix) and mobile platforms (Android/iOS). Use it when verifying skill legitimacy or performing deep cross-platform security reviews.

This guide details the systematic process of creating comprehensive incident response playbooks and runbooks. It covers structured procedures, decision trees, RACI matrices, and escalation protocols for various incident types (e.g., ransomware, data breach). Designed for maturing an Incident Response (IR) program, maintaining compliance (SOC 2, HIPAA), and integrating automated workflows into SOAR platforms, aligning with NIST SP 800-61r3 standards.

This skill provides comprehensive methods for collecting and synthesizing Open-Source Intelligence (OSINT) regarding threat actors, malicious infrastructure, and attack campaigns. It utilizes public data sources, passive reconnaissance tools (like WHOIS, Certificate Transparency), and specialized platforms (Maltego, Shodan, SpiderFoot) to map adversary context and perform pre-engagement intelligence gathering for authorized red team assessments. Emphasis is placed on passive collection techniques to ensure legality and operational security.

This skill guides the advanced configuration of Windows Event Logging using Group Policy Objects (GPO) and advanced audit policies. It enables high-fidelity logging for critical security events, including process creation (Event 4688), logon/logoff activities, and object access. The process covers optimizing log sizes and implementing Windows Event Forwarding (WEF) to centralize data into SIEM platforms for effective threat detection and forensic investigation.

This skill guides SOC analysts and detection engineers on how to correlate complex, multi-stage attacks within the IBM QRadar SIEM platform. It covers advanced usage of AQL (Ariel Query Language) for deep event investigation, building custom correlation rules (Building Blocks and Offenses), and cross-source data correlation (e.g., auth failures with network flows). It is essential for reducing false positives and improving threat detection accuracy.

Deploy Zeek for passive network analysis to generate structured logs (DNS, HTTP, etc.). This tool detects behavioral anomalies like DNS tunneling or beaconing, complementing traditional signature-based IDS tools. It is ideal for threat hunting and incident response, feeding rich protocol metadata into SIEM platforms.

A specialized technique for proactive threat hunting, designed to detect adversary activity that abuses legitimate cloud services (like Azure, AWS, GCP, and SaaS platforms). It focuses on identifying 'living off the cloud' tradecraft, such as using cloud APIs for command-and-control (C2), staging data, or exfiltrating information while blending into normal network traffic.

This skill guides the implementation of Mobile Application Management (MAM) policies, enabling robust data protection for corporate assets on both managed and unmanaged mobile devices (BYOD). It covers configuring app-level controls such as Data Loss Prevention (DLP), selective wiping, and containerization using platforms like Microsoft Intune and Azure AD. Use this when enforcing data separation between personal and work environments without requiring full device enrollment.

This skill provides a comprehensive guide to implementing robust USB device control policies. It restricts unauthorized removable media access to mitigate data exfiltration risks and prevent malware introduction via USB endpoints. Learn how to deploy granular policies using Group Policy Objects (GPO), Microsoft Intune, or advanced Endpoint Detection and Response (EDR) platforms to meet strict compliance standards.