Skill UI

Timesketch is a collaborative, open-source platform for security teams to analyze and reconstruct complex forensic timelines. It ingests and normalizes multi-source security data (logs, artifacts) using methods like Plaso, CSV, and JSONL. Users can visualize event chronology, track attack chains, and utilize advanced built-in analyzers (e.g., Sigma, Chain of Events) for comprehensive incident investigation and documentation.

This skill provides comprehensive tracking and visualization for Security Operations Center (SOC) performance. It calculates critical metrics such as Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), and alert quality ratios using SIEM data. Ideal for SOC leadership, compliance auditing, and continuous process improvement initiatives needing quantifiable security posture reporting.

This skill provides a systematic methodology for building comprehensive threat actor profiles using Open-Source Intelligence (OSINT). It involves gathering, correlating, and analyzing publicly available data from diverse sources (e.g., vendor reports, dark web forums, code repositories). Users can map adversary TTPs to MITRE ATT&CK, assess motivations, and build structured dossiers for proactive defensive strategies and attribution assessments.

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.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

A comprehensive guide to deploying and configuring osquery across diverse endpoints (Windows, macOS, Linux). This tool allows security teams to gather deep, SQL-based insights into endpoint state, including running processes, network connections, system configuration, and installed software. It is essential for threat hunting, compliance auditing, and building centralized fleet visibility.

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.

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.