Skill UI

This skill guides users on fine-tuning CodeRabbit's review quality. It teaches the AI agent team preferences through PR feedback, integrates custom code guidelines (e.g., security policies), allows customization of the review tone, and implements path filters to drastically reduce false positives and noise. This ensures that all code feedback is highly relevant, actionable, and aligns with specific team standards.

Guides writing high-quality YARA-X detection rules for malware hunting, covering naming conventions, string selection, performance tuning, migrations from legacy YARA, and reducing false positives when authoring, reviewing, or debugging signatures.

Systematically verifies suspected security bugs to eliminate false positives and document evidence, guiding each finding through the standard or deep verification path and producing TRUE POSITIVE or FALSE POSITIVE verdicts.

This skill provides a comprehensive guide for creating production-quality custom Semgrep rules. It teaches best practices for detecting security vulnerabilities, enforcing robust coding standards, and identifying specific bug patterns. By emphasizing a test-first approach and utilizing advanced techniques like taint mode, users can write highly accurate static analysis rules that drastically reduce false positives.

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 a structured methodology for mitigating alert fatigue within Security Operations Centers (SOCs). It guides users through advanced techniques, including implementing Risk-Based Alerting (RBA) to replace high-volume, low-fidelity alerts with consolidated risk scores. It emphasizes quantifying alert quality by analyzing True Positive (TP) and False Positive (FP) rates, and systematically tuning detection rules to maintain analyst effectiveness.

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.

Systematically optimizes Security Information and Event Management (SIEM) detection rules in platforms like Splunk and Elastic. This process involves analyzing historical alert volumes, establishing environmental baselines, creating context-aware whitelists, and statistically adjusting detection thresholds to significantly reduce false positives, improving overall security efficacy.

A comprehensive guide to configuring ModSecurity WAF with OWASP Core Rule Set (CRS). It covers establishing robust web application logging, tuning rules to minimize false positives, and implementing custom SecRules for advanced threat detection. Essential for security audits, compliance, and architectural hardening.

This skill guides developers through integrating Static Application Security Testing (SAST) tools like CodeQL and Semgrep into GitHub Actions CI/CD pipelines. It covers automating code scanning on pull requests and pushes, tuning rules to reduce false positives, uploading SARIF results, and establishing quality gates to prevent vulnerable code from merging into production.

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.