Skill UI

Auto-activating skill that guides analysts through forensics data collector operations, aligning advanced security practices with compliance frameworks while generating validated code and configurations for enterprise deployments.

Walks through analyzing RAM dumps with Volatility 3/2 to uncover injected code, hidden processes, network activity, and credentials when responding to compromised hosts.

This skill outlines the comprehensive process of memory forensics on compromised Linux systems. It guides users through acquiring volatile memory using the LiME kernel module and analyzing the resulting image with the Volatility 3 framework. Key artifacts extracted include process lists, network connections, bash history, and loaded kernel modules, making it an essential technique for incident response, threat hunting, and security investigations.

This tool provides comprehensive forensic analysis for Microsoft Outlook PST and OST files. It extracts critical evidence such as message content, detailed headers, attachments, and deleted items using open-source libraries like libpff and Python, supporting legal investigations and incident response.

A comprehensive digital forensics technique used to investigate removable media usage. It parses artifacts from Windows registry (USBSTOR, MountedDevices), Event Logs, and SetupAPI logs to track which USB devices were connected, when they were used, and establishing a timeline for potential data exfiltration or insider threat activity.

This comprehensive forensic workflow guides investigators through the extraction and detailed analysis of Windows Registry hives (SAM, SYSTEM, SOFTWARE, etc.). It is used during incident response to uncover critical artifacts, including user activity history, malware persistence mechanisms (autorun keys), installed software records, and evidence of system compromise.

A comprehensive guide and methodology for detecting process hollowing (T1055.012). It involves advanced memory forensics, analyzing memory-mapped sections, and correlating parent-child process anomalies using EDR and Sysmon data to identify fileless and in-memory malware threats.

A comprehensive skill for detecting advanced malware techniques, including DLL injection, process hollowing, APC injection, and thread hijacking. Utilizes memory forensics (Volatility), API monitoring (Sysmon), and behavioral analysis to identify malicious code artifacts and suspicious process activities in a deep defense context.

This skill details the deployment and advanced querying techniques for Arkime (Moloch), enabling comprehensive full packet capture network traffic analysis. Users can leverage the Arkime API v3 to search connections, download PCAPs, detect sophisticated C2 beaconing, and analyze connection patterns and anomalies across DNS, HTTP, and TLS traffic. Essential for security monitoring and network forensics.

This automated toolkit streamlines memory forensics using the Volatility3 framework. It is designed to analyze raw memory dumps from Windows, Linux, and macOS, revealing complex threats such as process injection, hidden rootkits, malicious code artifacts, and illicit network connections that traditional disk-based methods cannot detect. Essential for real-time incident response and deep security auditing.

This comprehensive guide details a multi-step workflow for detecting and extracting covert data hidden within images, audio, and video files. It covers initial metadata analysis, running advanced steganalysis tools (like zsteg, binwalk, stegoveritas), and performing low-level analysis such as Least Significant Bit (LSB) analysis to uncover hidden communication channels used in digital forensics and cybersecurity investigations.

This skill provides a comprehensive guide and structured SQL templates for performing deep forensic investigations on AWS cloud logs. It utilizes AWS Athena to query massive datasets from CloudTrail, VPC Flow Logs, S3 access logs, and ALB logs. Ideal for detecting unauthorized access, data exfiltration, and privilege escalation during security incident response.