Skill UI

This skill provides comprehensive security hardening guidelines for serverless compute platforms like AWS Lambda, Azure Functions, and Google Cloud Functions. It covers essential security pillars including enforcing least privilege IAM roles, integrating robust secrets management (e.g., AWS Secrets Manager), automating dependency vulnerability scanning within CI/CD pipelines, and implementing strict input validation to mitigate risks such as injection and credential theft. Ideal for DevSecOps practitioners and security architects.

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.

An advanced debugging skill designed for AI agents. It utilizes gdb-cli to provide intelligent assistance for C/C++ programs, enabling the analysis of core dumps, debugging live processes, and investigating complex issues like crashes, deadlocks, and memory corruption. It correlates runtime state inspection with source code context for deeper insights.

A comprehensive guide detailing proven patterns for building robust and scalable SwiftUI applications. Covers modern state management (@State, @Observable), advanced navigation (Sheets, NavigationStack), handling asynchronous data flows, and adhering to architectural best practices to create maintainable, performant UIs.

A comprehensive framework for advanced forensic analysis of UEFI firmware and boot process integrity. It details methods to detect firmware implants in SPI flash, audit UEFI variables (PK, KEK, DB), inspect the EFI System Partition (ESP) for unauthorized components, and analyze boot chain anomalies. Ideal for investigating advanced persistent threats (APTs) and verifying system security posture against rootkits and bootkit techniques.

This skill detects AI-generated deepfake audio used in voice phishing (vishing) attacks. It functions by extracting critical spectral features (including MFCCs, spectral centroid, and zero-crossing rate) and passing them through advanced machine learning models (like Random Forest and Gradient Boosting). The system supports batch forensic analysis, provides confidence scores, and generates detailed reports to verify the authenticity of recorded voice calls, making it essential for cybersecurity incident response and fraud investigation.

This guide details how to analyze comprehensive Zeek network logs (conn.log, smb_files.log, ntlm.log, dce_rpc.log, etc.) to detect advanced attacker techniques. It specifically targets indicators of compromise related to lateral movement, such as SMB admin share access, NTLM account spraying, and remote service execution (DCE/RPC patterns). It is a critical network forensics tool for post-incident investigation.

This skill focuses on detecting and mitigating sophisticated code injection and privilege escalation attacks across the entire serverless ecosystem (AWS Lambda, Azure, GCP). It combines static analysis of dangerous code sinks (e.g., eval, exec) with continuous monitoring of event sources (S3, SQS, API Gateway) and rigorous IAM auditing. It provides a comprehensive framework to secure the expanding serverless attack surface.

A comprehensive guide and technical framework for detecting and mitigating ransomware kill switch mechanisms. It details methods for analyzing mutex guards, domain-based communication, and registry checks. Learn how to deploy proactive mutex vaccination and use Sysmon/DNS monitoring to prevent malware execution during incident response and analysis.

This skill provides a comprehensive guide and structured SQL templates for performing deep forensic investigations on AWS cloud logs. It utilizes AWS Athena to query massive datasets from CloudTrail, VPC Flow Logs, S3 access logs, and ALB logs. Ideal for detecting unauthorized access, data exfiltration, and privilege escalation during security incident response.

This skill detects malicious Command and Control (C2) communications tunneled through the DNS protocol. It analyzes DNS query logs for indicators such as DNS tunneling tools (Iodine, dnscat2), Domain Generation Algorithms (DGA), and encoded payloads within TXT/CNAME records. Techniques include Shannon entropy analysis of subdomains, statistical anomaly detection, and machine learning classification. Ideal for network security analysts conducting deep threat hunting and forensic investigations.

A comprehensive operational guide for support teams to manage complex customer billing workflows. It assists operators in diagnosing billing anomalies, processing refunds, triaging charges, and recovering customer portals. Use this when investigating billing discrepancies, assessing churn risk, or ensuring accurate subscription state and revenue management.