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Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service abuse.

日本語の概要は準備中です。原文の説明を表示しています。

Detect Pass-the-Hash attacks by analyzing NTLM authentication patterns, identifying Type 3 logons with NTLM where Kerberos is expected, and correlating with credential dumping.

日本語の概要は準備中です。原文の説明を表示しています。

Detect abuse of service accounts through anomalous interactive logons, privilege escalation, lateral movement, and unauthorized access patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.

日本語の概要は準備中です。原文の説明を表示しています。

Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests targeting service accounts with SPNs for offline password cracking.

日本語の概要は準備中です。原文の説明を表示しています。

Detect Mimikatz execution through command-line patterns, LSASS access signatures, binary indicators, and in-memory detection of known modules.

日本語の概要は準備中です。原文の説明を表示しています。

Detect DCSync attacks where adversaries abuse Active Directory replication privileges to extract password hashes by monitoring for non-domain-controller accounts requesting directory replication via DsGetNCChanges.

日本語の概要は準備中です。原文の説明を表示しています。

Detect DLL side-loading attacks where adversaries place malicious DLLs alongside legitimate applications to hijack execution flow for defense evasion.

日本語の概要は準備中です。原文の説明を表示しています。

Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

日本語の概要は準備中です。原文の説明を表示しています。

This skill covers deploying Microsoft Sentinel as a cloud-native SIEM and SOAR platform for centralized security operations. It details configuring data connectors for multi-cloud log ingestion, writing KQL detection queries, building automated response playbooks with Logic Apps, and leveraging the Sentinel data lake for petabyte-scale threat hunting across AWS, Azure, and GCP security telemetry.

日本語の概要は準備中です。原文の説明を表示しています。

Detect PowerShell Empire framework artifacts in Windows event logs by identifying Base64 encoded launcher patterns, default user agents, staging URL structures, stager IOCs, and known Empire module signatures in Script Block Logging events.

日本語の概要は準備中です。原文の説明を表示しています。

Detect and analyze Linux persistence mechanisms including crontab entries, systemd service units, LD_PRELOAD hijacking, bashrc modifications, and authorized_keys backdoors using auditd and file integrity monitoring

日本語の概要は準備中です。原文の説明を表示しています。

Extract and analyze Cobalt Strike beacon configuration from PE files and memory dumps to identify C2 infrastructure, malleable profiles, and operator tradecraft.

日本語の概要は準備中です。原文の説明を表示しています。

Parse and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike and pyMalleableC2 to extract C2 indicators, detect evasion techniques, and generate network detection signatures.

日本語の概要は準備中です。原文の説明を表示しています。

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.

日本語の概要は準備中です。原文の説明を表示しています。

Turn vague preferences about employers into criteria that can actually be used to choose between them: for each one, what would have to be seen to confirm it, whether it comes from firsthand experience or from an untested assumption, whether it is a must, a nice-to-have, or something to avoid, and which pairs of criteria pull against each other while both being treated as required, then test the set against real candidates. Use when a new graduate is working out what to select employers on, when someone who has decided to move needs criteria for where to apply, or when a stated axis like "a place I can grow" needs to be made checkable; do not use to recommend an industry, job, or employer, to score or rank candidates, or to judge someone's stated preferences.

日本語の概要は準備中です。原文の説明を表示しています。

Hunt for adversary techniques in telemetry you are authorized to query. Hypothesis-driven, evidence-first, no live offensive operations.

日本語の概要は準備中です。原文の説明を表示しています。

Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.

日本語の概要は準備中です。原文の説明を表示しています。

Proactively search for security threats, vulnerabilities, and suspicious patterns in applications and infrastructure before they cause damage. Use when conducting security audits, identifying vulnerabilities, analyzing security logs, detecting suspicious patterns, investigating potential breaches, performing penetration testing, or implementing security monitoring.

日本語の概要は準備中です。原文の説明を表示しています。

Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.

日本語の概要は準備中です。原文の説明を表示しています。

Entry point and shared rules for structural changes to the live Matrx database. Use before any DDL: dropping, merging, or renaming a table, changing a function, RPC, trigger, or policy, hunting straggler tables, or starting a deprecated, schema move, or canonicalization (it routes to those skills).

日本語の概要は準備中です。原文の説明を表示しています。

Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.

日本語の概要は準備中です。原文の説明を表示しています。

MCP server for scraping Italian rental/sale property listings from multiple real estate portals (Immobiliare.it, Casa.it, and extensible to others) using Camoufox (anti-detection browser) and BeautifulSoup. Plugin architecture — each site is a self-contained adapter with its own URL templates, query param mappings, and CSS selector chains. Use this skill whenever the user wants to search for apartments, houses, or properties in Italy, scrape real estate listings, compare rental prices across Italian cities, or extract property data from Italian portals. Triggers on mentions of immobiliare, casa.it, Italian rentals, affitto, vendita, apartment hunting in Italy, or property scraping.

日本語の概要は準備中です。原文の説明を表示しています。

Expert malware analyst specializing in defensive malware research, threat intelligence, and incident response. Masters sandbox analysis, behavioral analysis, and malware family identification. Handles static/dynamic analysis, unpacking, and IOC extraction. Use PROACTIVELY for malware triage, threat hunting, incident response, or security research.

日本語の概要は準備中です。原文の説明を表示しています。