「mission analysis」の検索結果

Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.

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。

Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.

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。

Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.

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。

Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.

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。

Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.

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。

Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.

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 comprehensive preflight validation of Bicep deployments to Azure, including template syntax validation, what-if analysis, and permission checks. Use this skill before any deployment to Azure to preview changes, identify potential issues, and ensure the deployment will succeed. Activate when users mention deploying to Azure, validating Bicep files, checking deployment permissions, previewing infrastructure changes, running what-if, or preparing for azd provision.

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。

Detects and prevents privilege escalation inside Kubernetes pods by combining admission control (OPA policies), runtime monitoring (Falco), and audit log analysis of security contexts, Linux capabilities, and syscall patterns. Use when investigating a pod running as root or privileged, hardening workloads against in-pod escalation, or hunting for containers exceeding their intended scope. Keywords: allowPrivilegeEscalation, runAsRoot, capabilities, securityContext, OPA, Falco, audit log. Do not use for escalation through RBAC and service-account permissions - use auditing-kubernetes-rbac-privilege-escalation.

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 risky OAuth application consent grants in Azure AD / Microsoft Entra ID using Microsoft Graph API, audit logs, and permission analysis to identify illicit consent grant attacks.

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 AWS IAM privilege escalation paths using boto3 and Cloudsplaining policy analysis to identify overly permissive policies, dangerous permission combinations, and least-privilege violations

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。

Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

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。

Zigbee, Thread, and Matter mesh-protocol attack methodology — IEEE 802.15.4 sniffing with TI CC2531 / CC2540 / Sonoff Zigbee Dongle E, KillerBee toolkit, Touchlink commissioning abuse with the well-known transport key, replay/injection attacks, Zigbee Cluster Library command abuse for door locks and bulbs, Thread network credential theft, Matter commissioning chain analysis, and 6LoWPAN/IPv6 routing exploitation. Use when targeting smart-home or commercial mesh deployments, Zigbee-based door locks, lighting, or sensor networks.

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。

Comprehensive OSINT methodology for external red-team operations and authorized attack-surface assessments. Covers the 5-stage recon pipeline (seed discovery, asset expansion, enrichment, exposure analysis, reporting), asset-graph discipline with 29 asset types, severity rubric (CRITICAL/HIGH/MEDIUM/LOW/INFO), confidence upgrade workflows, time budgeting, asset-level triage rules, scale-based tactics, identity-fabric mapping (Entra/Okta/ADFS/Google/SAML/M365 Teams+SharePoint+OAuth), API and auth-map methodology, JavaScript deep analysis, mobile attack surface, cloud attack surface, breach×identity correlation, detectability tagging, detection-aware probing (back-off, persona rotation), read-only validator discipline, WAF/CDN bypass + origin discovery, vulnerability prioritization (CVE/EPSS/KEV), phishing infrastructure planning + pretext development, bug bounty submission templates, client deliverable templates with risk translation, threat-actor investigation (incl. RU/CN pivots), cryptocurrency tracing, image/video forensics, chronolocation. Use when planning or executing reconnaissance against authorized targets, mapping an organization's external attack surface, investigating a person/entity, tracing crypto flows, geolocating media, or performing attribution work.

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。

Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.

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。

DC power flow analysis for power systems. Use when computing power flows using DC approximation, building susceptance matrices, calculating line flows and loading percentages, or performing sensitivity analysis on transmission networks.

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。

Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.

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。

Use when building exhibits for an American Anthropologist (AA) manuscript — photographs, maps, site plans, artifact images, kinship diagrams, transcripts, evidence tables, and multimodal media — so they are self-contained, accessible (alt text), ethically cleared (consent, permissions), and count toward the word budget. Designs exhibits; it does not run analysis or clear permissions for you.

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。

Use when an Accounting, Organizations and Society (AOS) revise-and-resubmit arrives — planning revisions that may include recoding field data, new experimental conditions, or deepened theorizing, and drafting the point-by-point response to an interdisciplinary reviewer panel. Drafts the response; it does not run new analysis (aos-data-analysis) or the final preflight (aos-submission).

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。

Reads, validates, and prepares CDISC SDTM and ADaM clinical trial data for analysis. Covers SDTM domain joins (DM, AE, EX, VS, LB, DS), ADaM architecture (ADSL, BDS, OCCDS, ADTTE) with traceability, treatment-emergent AE conventions, baseline derivation, SUPPQUAL/NSV handling, Define-XML 2.1, and Pinnacle 21 / CORE validation. Use when working with clinical trial datasets in CDISC SDTM/ADaM format, preparing analysis-ready data, or validating for regulatory submission.

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。

Dielectric substrates, metal conductors, multi-layer stackups, and loss models (FR4, Rogers, Teflon) for RF PCB simulation. TRIGGER: user asks to set up a substrate, define dielectric properties, create a stackup, select a PCB material (FR4, Rogers, Teflon, etc.), or configure metal conductors. Invoke BEFORE writing dielectric() or metal() code — the API for named vs custom materials differs significantly. SKIP: PCB layout assembly (use matlab-assemble-pcb-layout), transmission line design (use matlab-design-pcb-transmission-line), EM analysis (use matlab-analyze-em), importing a PCB file (use matlab-read-pcb-layout).

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。

Spiral inductors, interdigital capacitors, baluns, resonators, phase shifters for impedance matching, DC blocking, and bias tees. TRIGGER: user asks to design or create a spiral inductor, interdigital capacitor, balun, resonator, phase shifter, or other passive RF component. Invoke BEFORE writing code — class names and property patterns are non-obvious. SKIP: filter design (use matlab-design-pcb-filter), coupler/splitter design (use matlab-design-pcb-coupler), transmission line design (use matlab-design-pcb-transmission-line), EM analysis (use matlab-analyze-em), material setup only (use matlab-manage-pcb-material).

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。

Via modeling: pads, antipads, ground return vias, GRV placement, and signal integrity for high-speed layer transitions. TRIGGER: user asks to model a via, design a via transition, place ground return vias, analyze via performance, or check signal integrity through layer transitions. Invoke BEFORE writing code — only viaSingleEnded exists (no viaDifferential), and the location format is non-obvious. SKIP: general signal integrity without vias (use matlab-analyze-em), transmission line design (use matlab-design-pcb-transmission-line), PDN analysis (use matlab-analyze-pcb-pdn), material/stackup setup only (use matlab-manage-pcb-material).

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。

Supply Chain Bottleneck Analyzer for TikTok Shop sellers. Diagnose cash flow, inventory turnover, affiliate commissions, and return rates. Includes FBT cost analysis, influencer payout optimization, and viral product lifecycle management. No API key required for basic analysis.

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。

Analyse student work against criteria to identify specific gaps between current performance and learning objectives. Use when reviewing submissions, planning feedback, or diagnosing learning needs.

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。