Skill UI

This framework defines a comprehensive, context-driven matrix for managing security incidents within a Security Operations Center (SOC). It details tiered escalation paths, response Service Level Agreements (SLAs), and notification procedures based not only on severity (P1-P4) but also on business risk, asset criticality, and data sensitivity. It guides analysts through triage, investigation, and timely escalation to management (CISO/Legal) to ensure rapid containment and appropriate organizational response during a breach.

A comprehensive guide for collecting volatile forensic evidence from a compromised host while adhering to the order of volatility. This process captures critical data—including memory dumps, network connections, running processes, and system state—before the host is isolated or powered down. Essential for root cause analysis, fileless malware investigation, and maintaining a defensible chain of custody for legal proceedings.

A comprehensive guide for responding to security incidents across major cloud providers (AWS, Azure, GCP). It details detection methods using cloud-native logs, containment strategies for compromising identities, evidence preservation techniques, and investigation steps for common cloud attack patterns.

This guide details the comprehensive workflow for conducting memory forensics using Volatility 3. It covers the entire incident response lifecycle, from acquiring raw RAM dumps to analyzing processes, detecting rootkits, investigating network connections, and extracting sensitive artifacts like credentials and injected code. Essential for live memory analysis in cybersecurity investigations.

This skill guides the advanced configuration of Windows Event Logging using Group Policy Objects (GPO) and advanced audit policies. It enables high-fidelity logging for critical security events, including process creation (Event 4688), logon/logoff activities, and object access. The process covers optimizing log sizes and implementing Windows Event Forwarding (WEF) to centralize data into SIEM platforms for effective threat detection and forensic investigation.

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 details methods and SIEM rules to detect API enumeration attacks, including BOLA and IDOR. It identifies patterns such as sequential ID iteration, parameter tampering, and mixed authorization failure responses (401/403). Use this guide for threat hunting, security incident investigation, and hardening API access control monitoring.

This skill analyzes AWS CloudTrail logs to detect suspicious API call patterns, such as new event sources, geographic anomalies, or high-frequency usage. It establishes a statistical baseline of normal activity and flags deviations indicative of compromised credentials, privilege escalation, or insider threats, providing a detailed JSON report for security investigation and threat hunting.

This skill analyzes AWS IAM policies using boto3 and Cloudsplaining principles to detect potential privilege escalation paths in AWS accounts. It identifies overly permissive policies, dangerous permission combinations (such as combining role passing and resource creation), and violations of least-privilege principles. It is designed for security incident investigation, threat hunting, and validating overall cloud security posture.

This script performs statistical analysis on Zeek connection logs (conn.log) to detect Command and Control (C2) beaconing patterns. It leverages the ZAT library to load data into Pandas DataFrames, calculates inter-arrival time statistics, and flags connections with low standard deviation relative to the mean. This technique is crucial for network threat hunting and security incident investigation when identifying malicious, periodic callbacks.

Detects and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and LOLBins. Use for fileless threat detection, in-memory malware investigation, LOLBin abuse analysis, or WMI persistence examination.

This skill provides a structured method for analyzing Windows Security Event Logs (EVTX) to detect brute force attacks targeting RDP endpoints. It involves parsing failed logon events (Event ID 4625) and correlating them with successful logons (Event ID 4624), while also analyzing source IP frequency and NLA bypass attempts. Ideal for security incident investigation, blue-team threat hunting, and building SIEM detection rules.