Skill UI

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 a methodology to detect data exfiltration attempts hidden within DNS queries. By analyzing Zeek dns.log files, the agent computes Shannon entropy of subdomains, flags unusually long labels, and monitors unique subdomain counts per parent domain. This technique is crucial for identifying malicious tunneling tools like dnscat2 or iodine that bypass traditional security controls.

This skill provides structured procedures for detecting Golden Ticket attacks, a severe threat involving forging Kerberos Tickets in Active Directory. It analyzes Windows Event ID 4769 for indicators such as RC4 encryption downgrades, abnormal ticket lifetimes, and inconsistencies in TGS/TGT requests. Designed for SOC analysts and threat hunters using SIEM platforms (Splunk/Elastic) to enhance security monitoring coverage against credential theft.

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 skill implements User and Entity Behavior Analytics (UEBA) to detect sophisticated insider threats. It builds behavioral baselines from diverse log sources (authentication, file access, network) using Elasticsearch/OpenSearch. It calculates anomaly scores and performs peer group analysis to identify deviations indicative of data exfiltration, privilege abuse, or unauthorized access patterns.

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.

This skill analyzes Windows Security Event Logs (EVTX) to detect RDP brute force attacks. It parses failed logon events (ID 4625) and correlates them with successful logons (ID 4624), performing source IP frequency analysis to identify attack patterns, username spraying, and potential account compromises. This is critical for SOC analysts and threat hunters investigating lateral movement or credential stuffing attempts.

This skill analyzes network logs, including proxy access logs, DNS query logs, and netflow data, to detect unauthorized Software as a Service (SaaS) applications and cloud services (Shadow IT). It classifies domains against known catalogs, measures data exfiltration volumes, calculates risk scores, and generates comprehensive reports for security and compliance teams.

This guide details how to detect WMI event subscription persistence, a common attacker technique (T1546.003). It focuses on analyzing suspicious Sysmon Event IDs 19, 20, and 21 to identify malicious EventFilters, EventConsumers, and Bindings. Essential for incident response and threat hunting in Windows environments.

This skill provides structured methods for detecting credential stuffing attacks by analyzing authentication logs. It focuses on identifying complex patterns such as login velocity anomalies, high IP diversity, password spray techniques, and suspicious geographical distributions of failed logins. It is essential for SOC analysts conducting threat hunting or building robust detection rules against account takeover attempts.

This capability provides advanced threat hunting by analyzing network telemetry (DNS, proxy, connection logs) to detect Command and Control (C2) beaconing patterns. It uses statistical analysis, frequency detection, and jitter analysis to identify compromised endpoints communicating with adversary infrastructure, crucial for proactive threat detection and incident response.

This skill detects WMI-based lateral movement by analyzing key Windows Security Event ID 4688 and Sysmon Event ID 1 logs. It focuses on identifying suspicious process execution patterns, such as WmiPrvSE.exe spawning unauthorized child processes (cmd.exe, powershell.exe), suspicious command lines, and WMI event subscriptions used for persistence. Ideal for security incident response and threat detection.