Skill UI

This SDK provides the management plane interface for provisioning and managing Azure SQL resources (like servers, databases, elastic pools, and firewall rules) within the Azure Resource Manager framework. Built for .NET developers, it allows users to programmatically handle infrastructure setup and configuration, making it ideal for DevOps automation and infrastructure-as-code workflows.

Guides AWS users through Elasticache configuration workflows, offering best-practice patterns, production-ready snippets, and validation checks whenever “elasticache config” is mentioned.

Automates elasticsearch index manager activities inside advanced DevOps workflows, offering best-practice guidance, code/configuration generation, and validation for kubernetes, terraform, ci/cd, monitoring, and IaC needs.

This skill provides a comprehensive workflow for building vendor-agnostic detection rules using the Sigma format. It empowers security operations center (SOC) engineers to translate raw threat intelligence and MITRE ATT&CK techniques into standardized, portable detection logic. The process guides users through rule validation and conversion into specific queries for major SIEM platforms, including Splunk, Elastic, and Microsoft Sentinel, ensuring robust detection coverage.

This skill facilitates the creation of real-time incident response dashboards across major SIEM platforms (Splunk, Elastic, Grafana). It provides SOC analysts and leadership with unified situational awareness by tracking affected systems, containment status, Indicators of Compromise (IOC) spread, and the entire incident response timeline, crucial for coordination and post-incident reporting.

This guide details the deployment and configuration of MISP (Malware Information Sharing Platform) using Docker. It demonstrates how to aggregate, correlate, and distribute threat intelligence from diverse sources like abuse.ch and AlienVault OTX. Learn automated feed synchronization, STIX/TAXII integration, and connecting the platform to SIEM and SOAR tools like Splunk and Elasticsearch for centralized IOC management.

A comprehensive guide and framework for detecting attacker lateral movement within enterprise networks. It details the use of network flow analysis (Zeek), authentication log review (Windows Event Logs, Kerberos), and dedicated SIEM correlation rules (Splunk, Elastic) to identify techniques like Pass-the-Hash and RDP hopping. Ideal for threat hunters and security engineers building detection pipelines.

This skill details the detection of Pass-the-Ticket (PtT) attacks, a critical credential theft technique. It instructs users on analyzing Windows Security Event IDs (4768, 4769, 4771) within SIEM platforms like Splunk or Elastic. Use cases include investigating security incidents, building advanced threat hunting queries, and validating SOC monitoring coverage for lateral movement attacks.

This skill guides the process of designing, implementing, and validating advanced security detection use cases for Security Information and Event Management (SIEM) platforms like Splunk, Elastic, and Microsoft Sentinel. It focuses on mapping organizational threat profiles to the MITRE ATT&CK framework to build formal, high-fidelity detection rules, thereby strengthening Security Operations Center (SOC) coverage and reducing blind spots.

A comprehensive toolkit for building robust, structured logging pipelines in Golang. It provides advanced modules for handler composition (slog-multi), throughput control (slog-sampling), attribute transformation (slog-formatter), and integrates with major backend logging sinks (e.g., Sentry, Loki, Datadog, Elasticsearch). Use this when building complex Go applications that require deterministic log routing, sampling, and data sanitization.

A comprehensive guide for migrating search functionality from alternatives like Elasticsearch, Typesense, or Meilisearch to Algolia. It details the necessary steps, including data migration, query translation (e.g., ES to Algolia), and implementing a zero-downtime swap using the Strangler Fig pattern.

A comprehensive technical guide detailing the process of migrating large-scale enterprise search platforms from sources like Elasticsearch or Algolia to Glean. It covers data export, schema transformation, using bulk indexing APIs, creating data sources, and validating search quality for smooth, large-scale deployment.