Skill UI

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 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 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 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.

This tool conducts comprehensive, sector-specific threat landscape assessments by analyzing designated threat actor patterns (e.g., APT groups, cybercriminals), common attack vectors, and industry-specific vulnerabilities. It is designed to provide actionable intelligence for risk management, security investment prioritization, and executive reporting across critical sectors like finance, healthcare, and energy.

This skill performs User and Entity Behavior Analytics (UEBA) to identify anomalous user activities such as impossible travel, unusual access patterns, and privilege abuse. It establishes behavioral baselines using SIEM logs and statistical analysis, helping SOC teams detect insider threats and compromised accounts by flagging deviations from normal user behavior. Use when monitoring security hygiene and suspicious activity is critical.

The Stock Analyzer Skill provides comprehensive technical analysis for stocks and ETFs. It utilizes industry-standard indicators like RSI, MACD, and Bollinger Bands to generate actionable trading signals. Users can perform advanced technical comparisons, monitor portfolio strength, and identify chart patterns through natural language queries, eliminating the need for manual indicator calculation.

A comprehensive automation toolkit for Mixpanel product analytics, accessible via Rube MCP. Automate key data tasks including event aggregation, detailed segmentation, conversion funnel analysis, user profile management, cohort tracking, and running custom JQL queries. Ideal for data analysts and product managers needing to deeply analyze user behavior patterns.