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This skill automates the entire phishing incident response workflow using the Splunk SOAR REST API. It parses suspicious emails, creates incident containers, attaches artifacts (URLs, IPs, headers), triggers automated investigation playbooks, and compiles a comprehensive security verdict. It is designed for security operations teams building robust, automated incident response capabilities.

This skill details the process of generating comprehensive forensic super-timelines using Plaso's log2timeline tools. It fuses diverse artifacts—including file-system MACB times, registry data, EVTX, and browser histories—into a single, normalized chronological view. This is critical for reconstructing the full sequence of events on compromised or forensically imaged systems during Digital Forensics and Incident Response (DFIR) investigations, helping analysts detect anti-forensic activity.

Velociraptor is a powerful open-source platform for endpoint visibility and digital forensics. It allows users to deploy agents across thousands of endpoints and execute sophisticated VQL (Velociraptor Query Language) queries. This enables large-scale, on-demand forensic artifact collection, TTP hunting, and continuous monitoring during incident response, even on air-gapped or unmanaged systems.

Hayabusa is a specialized threat-hunting and fast-forensics tool designed to analyze Windows EVTX event logs. It applies a comprehensive library of Sigma detection rules to raw log data, generating a single, prioritized, chronological timeline. The output includes severity levels, MITRE ATT&CK mappings, and detailed metrics, enabling analysts to perform rapid, SIEM-free incident triage and export results for collaborative analysis.

This guide details the process of parsing core Windows forensic artifacts, including MFT, Prefetch, Registry hives, ShellBags, and Amcache. Utilizing Eric Zimmerman's specialized EZ Tools, raw evidence is converted into standardized CSV/JSON formats. This process is crucial for Digital Forensics and Incident Response (DFIR) investigations, enabling analysts to reconstruct program execution, file access history, and persistence mechanisms, which can then be loaded into Timeline Explorer for unified analysis.

KAPE (Kroll Artifact Parser and Extractor) is a specialized, rapid triage tool for incident response. It collects specific, volatile forensic artifacts (like registry hives, event logs, and browser data) from compromised Windows systems. It is designed for remote, at-scale artifact collection when full disk imaging is impractical, enabling analysts to quickly build a defensible, parseable dataset for initial investigation and containment.

This skill provides building blocks and workflows to programmatically design, test, and deploy automated triage agents for Monte Carlo alerts. Users can fetch, score, and troubleshoot alerts interactively or set up scheduled, reusable workflows, moving from manual review to fully automated incident response.

A systematic skill designed to investigate data incidents, including freshness delays, volume anomalies, schema changes, and ETL failures. It guides the agent through a comprehensive process using Monte Carlo's observability metadata and optional direct data querying to pinpoint the root cause.

This skill guides users through the complete lifecycle of data quality incident management using Monte Carlo MCP tools. It performs detailed investigation, including root cause analysis and blast radius assessment. It then coordinates various external tools (APIs, CLI) to propose and execute appropriate remediation actions, ensuring all data incidents are resolved with full context.

A structured presentation deck designed for rigorous review of safety incidents, security risks, and policy compliance. It utilizes distinct visual cues, including hazard stripes, L1/L2/L3 severity tiers, and dedicated code blocks for policy review (e.g., YAML). Ideal for red team exercises, post-incident reviews, and high-stakes technical briefings.

A comprehensive, single-page runbook designed specifically for engineering on-call teams. It consolidates crucial information needed during incidents, including service topology, critical alerts tables, dashboard links, common operational commands, on-call rotation schedules, and incident response checklists, ensuring fast and efficient response.

A comprehensive set of reusable patterns for structured incident triage in AWS environments. Includes pre-built Logs Insights queries for detecting errors, latency spikes, cold starts, and OOM events. Also provides systematic correlation methods linking CloudWatch alarms to deployment events, and a decision tree to narrow the blast radius scope from account to resource.