Skill UI

A comprehensive, step-by-step guide for security professionals to perform deep-dive malware analysis. It covers methodologies for static analysis (disassemblers, imports), dynamic execution (sandboxing, monitoring), identifying Indicators of Compromise (IOCs), and structuring professional threat reports. Essential for incident response and threat intelligence.

A comprehensive guide for digital forensics professionals to investigate compromised Docker containers. It covers best practices for preserving container state, analyzing image layers, reviewing runtime logs, and examining host system artifacts to identify evidence of malicious activity, container escapes, or misconfigurations.

A comprehensive guide for digital forensics analysts to investigate compromised Linux systems. This workflow details the collection and analysis of critical system artifacts, including authentication logs, shell histories, SSH keys, and system configurations. Use this methodology during incident response to detect rootkits, unauthorized persistence mechanisms, and reconstruct full attacker activity.

A comprehensive guide for deep packet inspection and network forensics using Wireshark and tshark. This skill is critical for incident response, where it allows users to capture, filter, and analyze network packet data to identify malicious command-and-control traffic, diagnose complex protocol issues, extract indicators of compromise (IOCs), and reconstruct data exfiltration paths. Use it for validating security rules and understanding network anomalies.

This skill provides a structured methodology and tools for investigating sophisticated supply chain attacks. It focuses on detecting trojanized software updates, compromised build pipelines, and hidden dependencies by performing deep binary comparison, code signing verification, and anomaly detection. Use it during incident response to map out intrusion vectors and assess the full scope of a security breach.

A comprehensive system for systematically collecting, categorizing, and enriching Indicators of Compromise (IOCs) from various sources (network logs, memory dumps, email, etc.). It supports the entire incident response lifecycle, ensuring structured data representation using STIX/TAXII formats for robust threat intelligence sharing and defensive system automation.

A specialized Python detector designed to monitor Operational Technology (OT) historian servers (such as OSIsoft PI, Ignition, etc.). It identifies critical indicators of compromise (IOCs), including unauthorized network connections, data manipulation attempts, and lateral movement activities that bridge IT and OT zones. Use this skill when validating data integrity and investigating potential cyber breaches in industrial environments.

A comprehensive guide for deploying and operationalizing Amazon GuardDuty. It provides continuous, intelligent threat detection across core AWS services including S3, EKS, and EC2 runtime monitoring. Use this skill to investigate suspicious activity, detect compromised credentials, or build automated incident response playbooks using EventBridge and Lambda for proactive security.

This skill detects compromised cloud credentials by analyzing anomalous API activity, impossible travel patterns, and unauthorized access indicators across AWS, Azure, and GCP. It integrates findings from GuardDuty, Defender for Identity, and Security Command Center to provide comprehensive threat visibility and assist in incident response and scope assessment.

A comprehensive guide and analysis framework for detecting compromised Office 365 or Google Workspace email accounts. It focuses on analyzing unified audit logs and Azure AD sign-in logs to identify indicators of account takeover (ATO) or Business Email Compromise (BEC). Detection methods include monitoring impossible travel events, identifying malicious inbox rules (e.g., external forwarding or deletion rules), and analyzing suspicious Microsoft Graph API access patterns.

This guide is designed for threat hunting, helping security teams proactively detect persistent unauthorized access methods. It focuses on identifying malicious inbox/mail-flow forwarding rules that adversaries establish after a compromise to maintain access to corporate communications, often associated with Business Email Compromise (BEC) or T1114 techniques. Use during incident response and proactive security assessments.

A comprehensive guide and workflow for detecting Mimikatz and similar credential-dumping activities. It utilizes command-line pattern matching, LSASS memory access signatures, binary indicators, and in-memory analysis. Ideal for threat hunting, scoping compromises during incident response, or validating detection coverage in purple team exercises using EDR/SIEM data.