Skill UI

This tool provides comprehensive on-chain analysis for DeFi protocols, allowing users to track metrics like Total Value Locked (TVL), fee revenue, DEX volumes, and yield opportunities. It is essential for DeFi researchers, protocol analysts, and yield farmers who require programmatic access to deep blockchain insights using the DeFiLlama API.

This tool provides comprehensive on-chain analysis for DeFi protocols, allowing users to track metrics like Total Value Locked (TVL), fee revenue, DEX volumes, and yield opportunities. It is essential for DeFi researchers, protocol analysts, and yield farmers who require programmatic access to deep blockchain insights using the DeFiLlama API.

A comprehensive skill for analyzing AWS spending patterns and identifying areas of waste. It provides actionable strategies to reduce cloud costs by detecting idle resources (like unattached EBS volumes or unused Elastic IPs), recommending Reserved Instances, and generating reports using AWS CLI and Cost Explorer data.

A comprehensive system for implementing policy guardrails in data enrichment pipelines. It enforces critical controls including credit spending limits, blocks the enrichment of sensitive PII (e.g., SSN, bank details), and validates input data quality. Essential for maintaining compliance (GDPR/CCPA) and managing costs when processing large volumes of personal and business data.

Access aggregated OFR hedge fund time series and metadata without auth, covering Form PF stats, repo volumes, futures trader positioning, and leverage/counterparty metrics for risk monitoring or research.

Analyzes comprehensive fitness logs to track quantitative trends in volume, intensity, and frequency. It tracks progress across multiple disciplines (running, strength) and correlates exercise metrics with vital health indicators like blood pressure and weight, providing personalized, science-backed training and recovery advice.

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 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 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.

This skill analyzes proxy access logs, DNS query logs, and network flow data to identify unauthorized SaaS and cloud services (Shadow IT). It uses Python and pandas to aggregate traffic, classify domains against known SaaS categories, and calculate risk scores based on data volume and user count. Ideal for conducting thorough security audits and generating actionable remediation reports.

This skill establishes normal network communication patterns by analyzing historical NetFlow/IPFIX data. Utilizing Python pandas, it computes hourly/daily volume distributions, per-host statistics, and top-talker profiles. Anomalies are detected using sophisticated statistical methods like z-score and IQR, allowing SOC analysts to quickly identify deviations such as data exfiltration spikes, persistent beaconing, or unusual port usage.