Skill UI

This SDK provides a dedicated Python interface for securely sending custom logs to Azure Monitor Log Analytics workspace. It utilizes the Logs Ingestion API, supporting features like batch compression, advanced error handling, asynchronous uploads, and compatibility with various authentication models, including sovereign clouds.

This library serves as a low-level exporter for Python applications, enabling the reliable transfer of comprehensive OpenTelemetry telemetry data—including traces, metrics, and logs—to Azure Application Insights. It provides robust configuration options, including connection string setup, Azure AD authentication, custom sampling, and offline storage management, ensuring complete and reliable observability.

This utility collects comprehensive debug information for troubleshooting complex issues related to Clerk authentication. It generates an environment report, runtime health checks, client-side debug panel data, and middleware logs. Use this tool when preparing detailed support tickets or diagnosing intermittent, hard-to-reproduce bugs.

Comprehensive digital forensic analysis guide for Linux systems. It covers the collection and examination of critical artifacts such as authentication logs, shell histories, user configurations, system files (passwd, shadow), and persistence mechanisms to effectively detect security compromises, unauthorized access, and malicious activity.

A comprehensive toolkit using Splunk's SPL language to analyze Windows Security, System, and Sysmon event logs. It maps advanced detection queries to specific MITRE ATT&CK techniques, enabling SOC analysts to investigate authentication attacks (e.g., brute force, password spraying), detect privilege escalation, locate persistence mechanisms, and trace lateral movement for detailed forensic timeline analysis.

Utilizes User and Entity Behavior Analytics (UEBA), statistical baselines, and machine learning models to monitor authentication logs. This skill identifies sophisticated security threats such as impossible travel, credential stuffing, brute force attacks, and compromised accounts in real-time. Essential for security operations and identity access management.

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 guide outlines a comprehensive threat hunting methodology for detecting adversary lateral movement within a network environment. It utilizes Splunk SPL queries against rich Windows event data, including authentication logs (4624, 4625), SMB traffic, and Sysmon telemetry. By correlating source-to-destination activity and identifying unusual logon types (RDP, WinRM, SMB), users can proactively track an attacker's path after initial system compromise, fulfilling MITRE ATT&CK T1021 techniques.

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 skill provides advanced threat hunting capabilities to detect NTLM relay attacks within Active Directory environments. It analyzes critical Windows Security Event 4624 logs, specifically focusing on logon type 3 using NTLMSSP authentication. The detection logic identifies suspicious patterns, including IP-to-hostname mismatches, rapid multi-host authentications, and lack of SMB signing enforcement, helping SOC analysts pinpoint unauthorized credential access attempts.

This guide details how to implement advanced SIEM correlation rules to detect sophisticated Advanced Persistent Threats (APTs). By chaining multiple event types—including Windows authentication events, process execution telemetry, and network connection logs—across hosts, users can surface complex attack sequences that are invisible to single-event detections. It utilizes Splunk SPL and Sigma rule formats for robust security posture enhancement.

This script gathers comprehensive diagnostic evidence for troubleshooting Intercom integrations. It systematically checks API authentication status, rate limits, platform status, SDK versions, and collects redacted logs. Use this utility when encountering persistent bugs or preparing detailed technical support tickets for Intercom support.