Skill UI

This comprehensive guide outlines the phased rollout process for DMARC (Domain-based Message Authentication, Reporting, and Conformance). It details moving from monitoring (p=none) through quarantine (p=quarantine) to full rejection (p=reject). Adopting DMARC is critical for anti-spoofing, ensuring that only authorized senders can use your domain, thereby significantly reducing phishing and unauthorized email traffic.

This guide outlines systematic methodologies for reducing false positives in Security Information and Event Management (SIEM) systems. It covers advanced techniques including threshold tuning, multi-signal correlation enhancement, behavioral baseline integration, and threat intelligence filtering. Used by SOC analysts and detection engineers to combat alert fatigue and improve true positive detection rates.

This guide details the comprehensive process of onboarding new log sources into Security Information and Event Management (SIEM) platforms. It covers critical steps including data source discovery, configuring collectors (e.g., Syslog, Splunk UF, CloudTrail), building parsers, normalizing fields to a common schema, and validating data quality. This systematic approach is essential for achieving complete security visibility and effective threat detection across the enterprise.

Leverage Eric Zimmerman's EZ Tools suite for comprehensive Windows forensic artifact analysis. This guide details how to parse critical system data, including the Master File Table (MFT), registry hives, prefetch files, and event logs. Essential for digital forensics investigators and incident responders conducting deep system analysis.

This guide provides a comprehensive workflow for recovering deleted files from forensic disk images and storage media. Utilizing PhotoRec and file signature carving techniques, it addresses scenarios where file systems are corrupted, formatted, or metadata is unavailable. The process includes setup, running the recovery tool in both interactive and command-line modes, and advanced steps for organizing, hashing, and validating file integrity.

This comprehensive guide details advanced network reconnaissance using Nmap's full capabilities. It covers sophisticated host discovery across multiple protocols, deep port scanning with timing and performance tuning, accurate service version enumeration, and OS fingerprinting. Furthermore, it teaches advanced techniques like firewall evasion (fragmentation, spoofing) and running NSE scripts for systematic vulnerability detection, crucial for authorized security assessment reports.

This tool monitors Modbus TCP communication within SCADA and ICS environments to detect security anomalies. It performs deep packet inspection, baselines normal communication patterns (e.g., typical function code distribution, register access), and applies statistical analysis to identify unauthorized register writes, reconnaissance attempts, or denial-of-service attacks targeting industrial control devices.

This advanced workflow automates the process of analyzing the operational health of specific Azure resources. It ingests and analyzes raw logs, telemetry data, and performance metrics from diverse Azure services (e.g., VMs, Web Apps, Databases). The system performs comprehensive root cause analysis, classifies issues (Critical, High, Medium), and generates actionable, step-by-step remediation plans, significantly reducing manual troubleshooting time.

This skill analyzes Azure resource groups in depth, identifying all resources, their configurations, and complex interdependencies. It maps relationships—including network connections, data flows, and managed identities—to generate comprehensive, detailed Mermaid architecture diagrams. Use this when you need a clear, structured visualization and full documentation of an Azure environment's topology.

A comprehensive guide for optimizing query latency in Qdrant. This resource explains advanced performance tuning techniques, focusing on critical resource management like RAM utilization, segment count adjustments, and HNSW parameter tuning. It details strategies for scaling, quantization, and hardware considerations (e.g., local NVMe) to ensure consistently low-latency search performance, and outlines common pitfalls to avoid.

A comprehensive guide for diagnosing production performance issues in Qdrant vector databases. Learn how to systematically check the optimizer status, analyze high memory usage (OOM crashes), and troubleshoot slow query latencies using key metrics and dedicated API endpoints. Essential for maintaining optimal operational health.

A comprehensive guide to optimizing CAST AI's core performance metrics, including node provisioning speed, autoscaler responsiveness, and API call efficiency. This skill covers techniques like configuring headroom, selecting optimal instance families, tuning evictors, and implementing caching for multi-cluster dashboards to ensure high availability and cost efficiency in cloud environments.