Skill UI

This guide teaches security teams how to deploy and operationalize Amazon GuardDuty for continuous, comprehensive threat detection across entire AWS accounts and workloads. It covers enabling protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting various finding severity levels, and building robust, automated incident response playbooks using EventBridge and AWS Lambda for immediate containment actions.

This skill provides comprehensive detection methods for credential dumping techniques, a critical post-exploitation phase in cyber attacks. It targets the extraction of sensitive credentials from LSASS memory, SAM registry hives, and NTDS.dit using advanced security visibility. Detection relies on analyzing Sysmon Event ID 10 (ProcessAccess), Windows Security logs, and complex SIEM correlation rules, making it essential for SOC analysts and threat hunters investigating advanced persistent threats (APTs).

This skill provides a comprehensive framework for detecting data exfiltration attempts that utilize DNS tunneling. It analyzes DNS logs for anomalies such as high Shannon entropy in subdomains, excessive query volume, abnormal query lengths, and misuse of TXT/CNAME records. It is ideal for SOC analysts and security engineers building advanced threat detection rules and performing threat hunting.

This skill provides comprehensive detection rules for advanced defense evasion techniques used by adversaries, including log tampering (T1070), timestomping, process injection (T1055), and disabling security tools (T1562). It is ideal for threat hunting, building detection rules, and investigating stealthy attacker activity using Sysmon and SIEM data.

This skill provides comprehensive guidance and detection rules for identifying fileless malware, in-memory attacks, and living-off-the-land techniques. It covers detecting PowerShell exploitation, reflective DLL injection, WMI abuse, and registry-resident threats, enabling security teams to build robust detections when traditional antivirus fails.

This script detects and analyzes sophisticated fileless malware techniques that operate entirely in system memory. It specializes in identifying threats that utilize Living Off the Land Binaries (LOLBins), WMI event subscriptions, and registry-resident payloads, bypassing traditional file-based security controls. It is ideal for forensic investigations, threat hunting, and building advanced detection rules in modern enterprise environments.

This skill guides the detection of Golden Ticket attacks within Active Directory by analyzing Kerberos logs (Event IDs 4768, 4769, 4771). It hunts for critical anomalies, such as mismatched encryption types (e.g., RC4 in AES environments), impossible ticket lifetimes, or service tickets appearing without a prior ticket grant request. This is essential for post-breach assessment and advanced threat hunting in domain environments.

This skill provides structured procedures and Python examples for detecting internal data exfiltration. It analyzes endpoint, cloud, and email logs by establishing behavioral baselines and performing statistical anomaly detection. Use cases include investigating insider threats, monitoring DLP policy violations, and building robust User and Entity Behavior Analytics (UEBA) rules for SOC teams.

This guide details methodologies for proactively hunting and detecting various insider threat indicators. It focuses on identifying unusual data access patterns, off-hours activity, mass file exfiltration, and unauthorized privilege abuse. By correlating data from EDR and SIEM platforms, security teams can scope compromises, simulate attack chains, and significantly enhance proactive threat detection capabilities.

A comprehensive guide and framework for detecting attacker lateral movement within enterprise networks. It details the use of network flow analysis (Zeek), authentication log review (Windows Event Logs, Kerberos), and dedicated SIEM correlation rules (Splunk, Elastic) to identify techniques like Pass-the-Hash and RDP hopping. Ideal for threat hunters and security engineers building detection pipelines.

This skill focuses on advanced threat detection techniques used to identify the abuse of legitimate Windows binaries (LOLBins) for malicious purposes. It requires monitoring process creation, command-line arguments, and network activity to pinpoint fileless and living-off-the-land attacks. Ideal for building SIEM/EDR detection rules, threat hunting, and hardening endpoint security policies.

This skill provides a comprehensive framework for detecting Living Off the Land Binaries (LOLBAS) abuse, such as misuse of certutil, regsvr32, and mshta. It leverages process telemetry from Sysmon and Windows Event Logs, combined with advanced Sigma rule-based detection and parent-child process anomaly analysis. Ideal for SOC analysts and threat hunters investigating sophisticated adversaries aiming to evade traditional security controls.