「kql」の検索結果

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。

Offensive methodology for attacking GraphQL APIs during penetration tests and bug bounty engagements. Covers the full attack lifecycle: endpoint discovery, introspection abuse and blind schema reconstruction when introspection is disabled, authentication and authorization bypass through Relay node IDs and nested object traversal, injection via variables and directives, query batching for brute force and OTP bypass, denial of service through depth bombs and alias amplification, WebSocket subscription hijacking, information disclosure through verbose errors and field suggestion oracles, and file upload abuse via the multipart GraphQL specification. Includes tool-specific guidance for InQL, graphql-cop, CrackQL, BatchQL, Altair, GraphQL Voyager, and clairvoyance. Trigger on: GraphQL, graphql, introspection query, batching attack, query depth, GraphQL injection, GraphQL IDOR, field suggestion, GraphQL auth bypass, GraphQL DoS, GraphQL security, graphql-cop, InQL, CrackQL, BatchQL, Relay node, alias amplificat...

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Detect Golden Ticket attacks in Active Directory using Splunk and KQL queries against domain controller event logs, looking for Kerberos TGT anomalies such as mismatched encryption types, impossible ticket lifetimes, non-existent accounts, and forged PAC signatures. Use when hunting for Kerberos ticket forgery or krbtgt-based persistence (MITRE T1558.001) in AD environments.

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 Azure service principal abuse in Microsoft Entra ID using KQL detection queries (Sentinel/Splunk) against Azure AD Audit and Sign-in Logs, covering added credentials, privileged role assignment, admin consent bypass, and service principal enumeration. Use when investigating suspected privilege escalation or persistence via service principals, or building threat-hunting queries for Entra ID identity 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。

Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.

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。

Compose IRQL (Incident Response Query Language) queries for Kusto cybersecurity investigations. Translates natural language hunting questions into composable IRQL pipelines using Get_*, Extract_*, and Enrich_* functions. WHEN: IRQL query, security hunt, threat hunting KQL, incident response query, compose hunting pipeline, failed logins, phishing investigation, lateral movement, process execution, file creation 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。

Build and query Kusto graphs from natural language. Covers transient graphs (make-graph), persistent graph models/snapshots, pattern matching (graph-match), shortest paths, connected components, and graph-to-table export. Generates the edges-first thinking: define edges, define node lookups, union, make-graph. WHEN: make-graph, graph-match, graph-shortest-paths, graph-to-table, graph-mark-components, persistent graph, graph model, graph snapshot, build a graph from data, find paths between nodes, pattern matching in graph, connected components, transient graph, Kusto graph, KQL graph.

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。

Compose IRQL (Incident Response Query Language) queries for Kusto cybersecurity investigations. Translates natural language hunting questions into composable IRQL pipelines using Get_*, Extract_*, and Enrich_* functions. WHEN: IRQL query, security hunt, threat hunting KQL, incident response query, compose hunting pipeline, failed logins, phishing investigation, lateral movement, process execution, file creation 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。

Build and query Kusto graphs from natural language. Covers transient graphs (make-graph), persistent graph models/snapshots, pattern matching (graph-match), shortest paths, connected components, and graph-to-table export. Generates the edges-first thinking: define edges, define node lookups, union, make-graph. WHEN: make-graph, graph-match, graph-shortest-paths, graph-to-table, graph-mark-components, persistent graph, graph model, graph snapshot, build a graph from data, find paths between nodes, pattern matching in graph, connected components, transient graph, Kusto graph, KQL graph.

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。

Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.

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。

Manages Fabric Spark work, including notebook cell code with %%configure, %%sql, PySpark and notebookutils, named notebook runs, Livy sessions, triage of failed or OOM notebook and pipeline Spark runs, and the Materialized Lake View (MLV) lifecycle. Load it before writing MLV SQL, since CREATE MATERIALIZED LAKE VIEW and its CONSTRAINT clause are Fabric-only. KQL materialized views belong to eventhouse-cli.

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 knowledge for Azure Sentinel development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring data connectors, KQL analytics rules, Logic Apps playbooks, data lake jobs, or SAP integration, and other Azure Sentinel related development tasks. Not for Azure Defender For Cloud (use azure-defender-for-cloud), Azure Security (use azure-security), Azure Monitor (use azure-monitor), Azure External Attack Surface Management (use azure-external-attack-surface-management).

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 knowledge for Azure Sre Agent development including troubleshooting, best practices, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when wiring SRE Agent to DevOps/GitHub, KQL telemetry, AKS Java apps, IaC deployments, or DR architectures, and other Azure Sre Agent related development tasks. Not for Azure Monitor (use azure-monitor), Azure Reliability (use azure-reliability), Azure Resiliency (use azure-resiliency), Azure Service Health (use azure-service-health).

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 knowledge for Azure Monitor development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring AMA/DCRs, Log Analytics workspaces, Application Insights, alerts, or Kusto (KQL) queries, and other Azure Monitor related development tasks. Not for Azure Network Watcher (use azure-network-watcher), Azure Resource Graph (use azure-resource-graph), Azure Service Health (use azure-service-health), Azure Defender For Cloud (use azure-defender-for-cloud).

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。

Detection engineering skill for writing, testing, and tuning Sigma, YARA, YARA-L, Suricata, Snort, Zeek, KQL, SPL, EQL, Chronicle, and Elastic detection rules. Covers ATT&CK coverage mapping, telemetry gap analysis, false-positive tuning, detection-as-code pipelines, and validation with Atomic Red Team and Caldera. Use to design durable detections backed by tests.

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Hunt AADGraphActivityLogs and MicrosoftGraphActivityLogs in Microsoft Sentinel/Log Analytics for fingerprints of offensive Entra ID tools such as ROADtools, AADInternals, and AzureHound.

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。