Skill UI

This tool detects abnormal access patterns across major cloud storage services (AWS S3, GCS, Azure Blob Storage). By analyzing audit logs like CloudTrail, it uses statistical baselines and time-series anomaly detection to identify suspicious activities such as after-hours bulk downloads, access from new IPs, or unusual API call spikes. It is crucial for investigating potential data exfiltration incidents or building robust cloud security detection rules.

This skill analyzes DNS query logs to detect sophisticated threats such as data exfiltration via DNS tunneling, Domain Generation Algorithm (DGA) usage, and covert Command and Control (C2) channels. It utilizes advanced techniques like entropy analysis, query volume anomaly detection, and subdomain length analysis within SIEM platforms, helping SOC teams identify threats that bypass traditional network security controls.

This tool analyzes network packet captures (PCAP) to detect covert communication channels used by malware for Command and Control (C2) and data exfiltration. It specifically focuses on identifying indicators of DNS tunneling, ICMP tunneling, and protocol abuse patterns, providing scoring and detailed reasons for suspicious activity. Useful for threat hunting and security incident investigation.

This tool parses NetFlow v9 and IPFIX records to conduct deep network security analysis. It is crucial for investigating security incidents by building traffic baselines and applying statistical methods. Key detection capabilities include identifying port scanning, data exfiltration attempts, command and control (C2) beaconing patterns, and general volumetric anomalies in network traffic.

Examines packet captures, Zeek logs, and NetFlow data to uncover C2 channels, lateral movement, and exfiltration during security incidents, guiding analysts through capture, filtering, and IOC extraction workflows.

A comprehensive guide for analyzing PCAP files captured during malware execution. It demonstrates advanced techniques using Wireshark, Zeek, Suricata, and Python (scapy) to identify Command and Control (C2) communications, data exfiltration channels, Domain Generation Algorithms (DGA), and periodic beaconing patterns. Essential for malware reverse engineering and network threat detection.

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 comprehensive skill analyzes Zeek conn.log and NetFlow data to proactively detect advanced indicators of ransomware activity. It identifies critical threats such as Command and Control (C2) beaconing patterns, connections to TOR exit nodes, large-scale data exfiltration flows, and suspicious DNS anomalies. It is essential for threat hunting and complex security incident response.

This guide details how to write advanced correlation searches using Splunk's Search Processing Language (SPL). It covers techniques like threshold-based detection, sequence analysis, and anomaly detection to identify sophisticated security threats (e.g., brute force, data exfiltration, lateral movement) in a Security Operations Center (SOC) environment. Mastery of SPL is essential for closing SIEM detection gaps and ensuring compliance.

Simulates advanced persistent threat (APT) activity across the entire cyber kill chain, from reconnaissance to data exfiltration. It evaluates an organization's detection, prevention, and response capabilities using MITRE ATT&CK-aligned techniques, moving beyond typical vulnerability scanning. Ideal for objective-based assessments and purple teaming.

This skill provides methods for detecting covert data exfiltration channels using DNS tunneling. It analyzes DNS query patterns, including subdomain entropy, query volume anomalies, oversized TXT/CNAME records, and unusual query types, to identify potential data leakage attempts from compromised networks. Ideal for threat hunting and building advanced passive DNS monitoring capabilities.

This skill detects DNS-based data exfiltration by analyzing Zeek dns.log files. It identifies indicators such as high Shannon entropy subdomains, oversized TXT/NULL records, and abnormal query volumes. Use it when investigating suspected DNS tunneling or covert C2 channels to enhance threat detection capabilities.