Skill UI

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.

This skill provides structured procedures and Python examples for detecting internal data exfiltration. It analyzes endpoint, cloud, and email logs by establishing behavioral baselines and performing statistical anomaly detection. Use cases include investigating insider threats, monitoring DLP policy violations, and building robust User and Entity Behavior Analytics (UEBA) rules for SOC teams.

This skill implements User and Entity Behavior Analytics (UEBA) using Elasticsearch/OpenSearch. It goes beyond static rules to build behavioral baselines (e.g., login times, data volume) for users and entities. By calculating anomaly scores and performing peer group analysis, it detects suspicious activities such as data exfiltration, privilege abuse, and unauthorized access, allowing organizations to proactively identify high-risk insider threats.

A comprehensive skill designed for advanced security analysis, detecting malicious behaviors across mobile applications (Android/iOS). It performs multi-layered analysis, including static indicator checks (permissions, manifest), dynamic instrumentation via Frida, network traffic monitoring (C2 communication, exfiltration), and automated scanning (MobSF). Use this when investigating suspicious apps, detecting trojans, or performing malware triage.

A comprehensive guide and workflow for detecting unauthorized data exfiltration from AWS S3 buckets. It details how to leverage multiple AWS services—including CloudTrail, GuardDuty, Amazon Macie, and Athena—to analyze access patterns, identify bulk downloads, and detect cross-account data transfers, ensuring robust cloud compliance and security monitoring.

Execute deep, stealthy red team exercises that emulate real-world sophisticated adversaries. This process maps attacks to the MITRE ATT&CK framework, testing an organization's entire security posture—including detection, incident response, and containment capabilities (Blue Team). It is designed for simulating full attack lifecycles (initial access, lateral movement, exfiltration) to validate security investments and meet regulatory requirements (TIBER-EU, CBEST). Requires executive authorization and defined Rules of Engagement.

This tool automates the extraction of embedded configuration details from Agent Tesla Remote Access Trojan (RAT) samples. It is designed to recover crucial exfiltration credentials (SMTP, FTP, Telegram), keylogger settings, and Command and Control (C2) endpoints by analyzing and deobfuscating the .NET assembly structure. Essential for threat intelligence, incident response, and malware reverse engineering.

A comprehensive guide for security professionals to detect data exfiltration by analyzing network telemetry (Zeek, Suricata) and logs. Techniques include identifying DNS tunneling, unusual cloud uploads, and detecting large/abusive data flows across various channels during incident response and proactive threat hunting.

Detects data-staging activity (MITRE ATT&CK T1074) by analyzing EDR/Sysmon process-creation and file-system telemetry. This skill monitors for archive creation (7-Zip, RAR, tar), unusual file consolidation from multiple directories, and suspicious activity in temporary or hidden paths. It is essential for threat hunting, building robust detection rules, and validating security monitoring coverage against data exfiltration attempts.

A comprehensive guide to identifying covert data exfiltration channels using Zeek logs. This technique analyzes DNS traffic for high-entropy subdomains, unusually long query lengths, abnormal record types (TXT/NULL), and excessive query volume, which are key indicators of malicious DNS tunneling or command-and-control (C2) activity.

This advanced skill guides users on hunting for Living Off the Land Binaries (LOLBins) abuse by analyzing endpoint process creation logs. It focuses on detecting malicious use of legitimate Windows binaries (like certutil or mshta) for defense evasion or data exfiltration, mapping techniques to MITRE T1218. Ideal for threat hunters and security teams building advanced detection rules.