Skill UI

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.

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 skill analyzes network logs, including proxy access logs, DNS query logs, and netflow data, to detect unauthorized Software as a Service (SaaS) applications and cloud services (Shadow IT). It classifies domains against known catalogs, measures data exfiltration volumes, calculates risk scores, and generates comprehensive reports for security and compliance teams.

This skill guides the implementation of network traffic baselining using historical NetFlow/IPFIX data. It leverages Python's pandas library to compute detailed statistical profiles, including hourly/daily distributions, per-host metrics, and protocol ratios. Anomalies are robustly detected using z-score and Interquartile Range (IQR) methods, assisting SOC analysts in identifying unusual activities like data exfiltration or beaconing.