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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 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.

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.

Audits a domain’s email authentication by querying SPF, DKIM, and DMARC DNS records using dnspython, validating syntax/counts, flagging common spoofing risks, and producing remediation guidance.

This skill detects covert data exfiltration occurring over DNS tunnels. It analyzes DNS query names by computing Shannon entropy, examining query length distributions, and identifying high subdomain cardinality. It is essential for security operations, incident response, and proactive threat hunting when suspicious or encoded DNS activity is suspected.

A comprehensive solution for performing Operational Technology (OT) vulnerability assessments using the Claroty xDome platform. It automatically discovers assets, correlates vulnerabilities using CVE and ICS-CERT advisories, and calculates risk scores. This method is designed for compliance requirements (e.g., IEC 62443, NERC CIP) and initial asset risk profiling, relying on passive monitoring and safe querying rather than active scanning or penetration testing.

bdistill transforms AI interactions into a structured, queryable knowledge base. It extracts, structures, and quality-scores domain knowledge from both closed-source AI models (in-session) and local open-source models (via Ollama). Users can build comprehensive reference datasets, Q&A pairs, or generate structured training data for traditional machine learning, ensuring validated and exportable domain expertise.

This tool monitors Certificate Transparency (CT) logs to detect unauthorized certificate issuance for owned domains, discover hidden subdomains, and track suspicious certificate activity. By querying public CT logs and APIs (like crt.sh), it helps build continuous security pipelines, identify potential phishing infrastructure, and map the external attack surface for comprehensive threat intelligence.

This bundle provides comprehensive debugging guidance for Veeva Vault, covering REST API interactions, advanced VQL querying, and utilizing the VAPIL Java SDK. It helps developers manage document lifecycles, authenticate sessions, and resolve common operational and data access errors within the life sciences domain.

Provides expert guidance for connecting to Power BI Desktop's local tabular model using the Tabular Object Model (TOM) and ADOMD.NET via PowerShell. This skill covers model enumeration, executing DAX queries, metadata modification (tables, measures, relationships), query tracing, and model refreshing. It is specifically designed for managing the underlying data model structure when external tools like Tabular Editor CLI are unavailable.

This skill implements an advanced reference pattern for integrating with Monitoring Control Platform (MCP) servers. It ensures accurate data retrieval by first reading a domain-specific 'gotchas' reference file, mitigating query failures caused by complex server behaviors, pagination limits, or subtle API quirks. It analyzes issue data, groups errors by root cause, and generates a structured, actionable markdown report for improved system health visibility.