Skill UI

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.

This skill provides comprehensive guidance on deploying and tuning Web Application Firewall (WAF) rules across major cloud platforms, including AWS, Azure, and Cloudflare. It details strategies to protect cloud-hosted applications against OWASP Top 10 attacks, implement rate limiting for brute force protection, configure geo-blocking, and refine rules to minimize false positives.

This guide provides a systematic, step-by-step workflow for Security Operations Center (SOC) analysts to perform alert triage using Elastic Security SIEM. It covers initial alert assessment, context gathering using advanced ES|QL queries, threat intelligence enrichment, and final classification decisions (True Positive, False Positive, etc.) to rapidly determine genuine security threats and prioritize incident response actions.

This guide details authenticated (credentialed) vulnerability scanning, which uses valid system credentials (SSH keys, domain passwords, etc.) to log into target hosts. Unlike external scanning, credentialed methods allow deep inspection of installed patches, local configurations, registry keys, and system files across diverse platforms (Linux, Windows, Network Devices). This significantly increases vulnerability detection rates and reduces false positives for comprehensive security assessments.

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.

A structured guide for SOC Tier 1 analysts to triage security alerts within Splunk Enterprise Security (ES). It provides a systematic workflow for classifying severity, investigating notable events, correlating evidence across diverse data sources (proxy, firewall, logs), and making clear disposition decisions (True Positive, False Positive) required for escalation or closure.

This skill details the deployment of various canary tokens (DNS, HTTP, AWS API Keys) across enterprise network infrastructure. It establishes digital tripwires that detect behavioral anomalies, such as unauthorized access, credential leakage, or lateral movement. Tokens are configured with webhook alerts (Slack, SIEM) for real-time, low-false-positive notification, significantly enhancing traditional IDS/IPS capabilities.

A comprehensive guide to deploying cloud-native deception across AWS, Azure, and GCP. This skill utilizes decoy resources—such as canary IAM keys, honey object storage buckets, and decoy secrets—whose sole purpose is to generate high-fidelity alerts the instant they are interacted with by an attacker. It detects cloud reconnaissance, credential theft, and lateral movement by wiring detection through native logging services (CloudTrail, Sentinel, Cloud Audit Logs), ensuring near-zero false positives for the SOC.