Skill UI

This skill provides a methodology to detect data exfiltration attempts hidden within DNS queries. By analyzing Zeek dns.log files, the agent computes Shannon entropy of subdomains, flags unusually long labels, and monitors unique subdomain counts per parent domain. This technique is crucial for identifying malicious tunneling tools like dnscat2 or iodine that bypass traditional security controls.

This skill implements User and Entity Behavior Analytics (UEBA) to detect sophisticated insider threats. It builds behavioral baselines from diverse log sources (authentication, file access, network) using Elasticsearch/OpenSearch. It calculates anomaly scores and performs peer group analysis to identify deviations indicative of data exfiltration, privilege abuse, or unauthorized access patterns.

A comprehensive guide and framework for detecting attacker lateral movement within enterprise networks. It details the use of network flow analysis (Zeek), authentication log review (Windows Event Logs, Kerberos), and dedicated SIEM correlation rules (Splunk, Elastic) to identify techniques like Pass-the-Hash and RDP hopping. Ideal for threat hunters and security engineers building detection pipelines.

This skill provides a comprehensive framework for detecting Living Off the Land Binaries (LOLBAS) abuse, such as misuse of certutil, regsvr32, and mshta. It leverages process telemetry from Sysmon and Windows Event Logs, combined with advanced Sigma rule-based detection and parent-child process anomaly analysis. Ideal for SOC analysts and threat hunters investigating sophisticated adversaries aiming to evade traditional security controls.

This skill provides a comprehensive guide to deploying Zeek (formerly Bro) for passive network security monitoring. It details how to generate structured logs (DNS, HTTP, SSL, etc.) and write custom Zeek scripts to detect sophisticated anomalies like DNS tunneling and beaconing. Ideal for threat hunting, security incident response, and complementing traditional IDS solutions.

This skill analyzes Windows Security Event Logs (EVTX) to detect RDP brute force attacks. It parses failed logon events (ID 4625) and correlates them with successful logons (ID 4624), performing source IP frequency analysis to identify attack patterns, username spraying, and potential account compromises. This is critical for SOC analysts and threat hunters investigating lateral movement or credential stuffing attempts.

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 guides threat hunters in detecting Cobalt Strike Command and Control (C2) beacons. It utilizes advanced network forensic techniques, including analyzing default TLS certificate serials, JA3/JA3S/JARM fingerprints, beacon jitter, and HTTP profile matching. Detection is achieved by correlating data from Zeek logs, Suricata rules, and Python PCAP analysis to identify suspicious outbound 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.

A comprehensive guide on implementing AWS CloudTrail log analysis for robust security monitoring, threat detection, and forensic investigation. Learn how to configure CloudTrail, use Amazon Athena for SQL querying, and leverage CloudWatch Logs Insights and SIEM integration to identify unauthorized access, privilege escalation, and suspicious API activity across AWS services.

A comprehensive guide and tool for implementing secure network segmentation in Operational Technology (OT) environments. It utilizes the Purdue Model and traffic baseline analysis to design secure zones using VLANs, industrial firewalls, and data diodes, ensuring migration from flat networks without operational disruption. Ideal for achieving IEC 62443 compliance and securing IT/OT convergence points.