Skill UI

A comprehensive guide to detecting sophisticated rootkit activity and persistent threats that evade standard security tools (like Task Manager or EDR). Techniques include cross-view process analysis, identifying System Service Descriptor Table (SSDT) hooks, kernel module analysis, and network connection forensics using tools like Volatility. Use this when standard monitoring fails, and deep system integrity checks are required.

This tool discovers and inventories 'shadow APIs'—endpoints that operate outside documented specifications (OpenAPI/Swagger). It utilizes advanced traffic analysis against API gateways (e.g., Kong, AWS API Gateway), cloud configuration scanning, and source code mining. Essential for assessing the complete API attack surface, auditing forgotten services, or establishing robust API governance policies.

A comprehensive guide for threat hunters and incident responders to detect WMI-based persistence mechanisms (MITRE T1546.003). It details the analysis of Sysmon Event IDs 19, 20, and 21, cross-referencing these events with root\subscription namespaces and using tools like Autoruns and SIEM analysis for robust detection.

Executes authorized, advanced attack simulations against Active Directory environments to identify critical misconfigurations, weak credentials, and exploitable trust relationships. Utilizing industry tools like BloodHound, Mimikatz, and Impacket, this process simulates complex attacks such as Kerberoasting, Golden Ticket forging, and domain compromise path analysis, helping organizations validate their security posture against real-world threats.

Structures completed intrusion investigations with the Diamond Model by documenting adversaries, capabilities, infrastructure, and victims plus their relationships, metadata, and pivots to cluster incidents and support campaign attribution, confidence scoring, and analytic write-ups.

This utility performs comprehensive forensic analysis on memory dumps. It leverages industry-standard tools like Volatility and Mimikatz to extract sensitive information, including cached credentials, NTLM/LM hashes, Kerberos tickets, and authentication tokens. It is crucial for incident response, assessing the scope of credential compromise, and investigating lateral movement attacks.

A comprehensive toolkit designed to automatically extract Indicators of Compromise (IOCs) from malware samples. It harvests critical artifacts including file hashes (MD5, SHA256), network indicators (IPs, domains, URLs), and host artifacts (registry keys, mutexes) using static, dynamic, and PCAP analysis. Essential for threat intelligence, building defense rules (YARA, Snort), and incident response.

This tool leverages the Rekall memory forensics framework to conduct deep analysis of memory dumps. It is designed to detect sophisticated threats such as process hollowing, injected code via VAD anomalies, hidden operating system processes, and rootkit presence. It applies key forensic plugins (pslist, malfind, vadinfo) essential for rigorous incident response and malware analysis.

This skill provides a systematic methodology for detecting Command and Control (C2) beaconing patterns in network traffic. It utilizes advanced statistical techniques, including Coefficient of Variation (CV) and jitter analysis, applied to network flow logs (Zeek, proxy, firewall). It is crucial for proactive threat hunting and incident response to identify compromised endpoints communicating periodically with malicious infrastructure.

This skill provides comprehensive methods to detect Cobalt Strike beacon command-and-control (C2) traffic. It uses advanced network forensics techniques, including analyzing default TLS certificates (e.g., serial 8BB00EE), JA3/JA3S fingerprints, HTTP malleable profiles, and beacon interval jitter, leveraging Zeek logs, Suricata rules, and Python PCAP analysis. It is essential for threat hunters and SOC analysts investigating sophisticated C2 communications.

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 anti-forensic timestomping by analyzing NTFS Master File Table (MFT) entries. It compares timestamps from the $STANDARD_INFORMATION attribute (user-modifiable) against the $FILE_NAME attribute (kernel-protected). Discrepancies, such as SI Created < FN Created, strongly indicate malicious manipulation and defense evasion. This methodology is crucial for advanced threat hunting and digital forensic investigations.