Skill UI

This skill correlates disparate security incidents, Indicators of Compromise (IOCs), and adversary behaviors across time and organizations. It systematically identifies unified threat campaigns, attributes them to common threat actors, and extracts shared indicators for significantly improved detection capabilities. Ideal for cross-organizational threat intelligence sharing and building comprehensive campaign reports.

This system deploys advanced AI, NLP, and behavioral analytics to detect sophisticated Business Email Compromise (BEC) attacks. Unlike traditional filters that rely on malicious links, this solution analyzes writing style, tone, grammatical patterns, and contextual anomalies to identify pure social engineering impersonation, providing a robust defense layer against advanced phishing and fraud.

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 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 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 provides a structured methodology for detecting process injection techniques (MITRE ATT&CK T1055), which adversaries use for defense evasion and privilege escalation. It analyzes granular security logs, specifically utilizing Sysmon Event IDs 8 (CreateRemoteThread) and 10 (ProcessAccess), alongside source-target process relationship mapping to identify suspicious malicious behavior over general system activity.

This guide details a structured threat hunting methodology designed to proactively detect sophisticated spearphishing campaigns. It instructs users on correlating indicators across email logs, endpoint telemetry (EDR), and network data (SIEM) to identify targeted threats, supporting incident response and security posture improvement.

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.