284 件 ・ 関連度順
概要と使いどころ
Detecting compromised cloud credentials across AWS, Azure, and GCP by analyzing anomalous API activity, impossible travel patterns, unauthorized resource provisioning, and credential abuse indicators using GuardDuty, Defender for Identity, and SCC Event Threat Detection.
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Container escape is a critical attack technique where an adversary breaks out of container isolation to access the host system or other containers. Detection involves monitoring for escape indicators
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Responds to phishing incidents by analyzing reported emails, extracting indicators, assessing credential compromise, quarantining malicious messages across the organization, and remediating affected accounts. Covers email header analysis, URL/attachment sandboxing, and mailbox-wide purge operations. Activates for requests involving phishing response, email incident, credential phishing, spear phishing investigation, or phishing remediation.
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MISP (Malware Information Sharing Platform) is an open-source threat intelligence platform for gathering, sharing, storing, and correlating Indicators of Compromise (IOCs) of targeted attacks, threat
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Automates the enrichment of raw indicators of compromise with multi-source threat intelligence context using SOAR platforms, Python pipelines, or TIP playbooks to reduce analyst triage time and standardize enrichment outputs. Use when building automated enrichment workflows integrated with SIEM alerts, email submission pipelines, or bulk IOC processing from threat feeds. Activates for requests involving SOAR enrichment, Cortex XSOAR, Splunk SOAR, TheHive, Python enrichment pipelines, or automated IOC processing.
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Build an automated pipeline to defang indicators of compromise (URLs, IPs, domains, emails) for safe sharing and distribute them in STIX format through TAXII feeds and threat intelligence platforms.
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Parse Office 365 Unified Audit Logs via Microsoft Graph API to detect email forwarding rule creation, inbox delegation, suspicious OAuth app grants, and other indicators of account compromise.
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Analyzes structured and unstructured threat intelligence feeds to extract actionable indicators, adversary tactics, and campaign context. Use when ingesting commercial or open-source CTI feeds, evaluating feed quality, normalizing data into STIX 2.1 format, or enriching existing IOCs with campaign attribution. Activates for requests involving ThreatConnect, Recorded Future, Mandiant Advantage, MISP, AlienVault OTX, or automated feed aggregation pipelines.
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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。
Knowledge base from the Expanded Guidance for NASA Systems Engineering (NASA/SP-2016-6105-SUPPL, Volume 1, March 2016) — the practitioner-depth supplement to the NASA SE Handbook. Use for the load-bearing mechanics the handbook compresses: the SE Engine's per-phase cadence and the iterative-vs-recursive distinction, the AS9100 crosswalk, life-cycle tailoring vs. customization and the Compliance Matrix, the recursive system-design consistency loop (ConOps vs. Operations Concept, requirement flow/type/ownership, successive refinement), product realization (verify/qualify/accept/certify cardinality, protoflight, 'test the way we fly' coverage, two-form transition), and the crosscutting technical-management procedures (six-step scheduling, cost-estimating method selection, JCL, interface document family, RIDM/CRM, CM baselines, EVM arithmetic, MOE/MOP/KPP/TPM, the three required leading indicators, and the decision-analysis method catalog). This is the DEPTH layer — it deliberately does NOT restate the base definitions; pair it with the nasa-se-handbook pack. Scope: NASA space-flight SE practice (Vol 1 Practices); thin on the Vol 2 process-appendix detail, on non-NASA/commercial life cycles, and on software-engineering methodology.
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。
Knowledge base from the FAA Human Factors Design Standard (HF-STD-001B, 2016) — the FAA's consolidated human-factors / human-systems-integration design criteria for systems it manages, operates, or maintains. Use for requirement-level design rules on: general human-factors design principles; automation and function allocation; designing equipment for maintenance; displays, controls, and visual indicators; alarms, audio, and voice communications; the computer-human interface (information presentation, coding, interaction styles, windows, dialogue); keyboards, input devices, and workstation/workplace ergonomics; system security, personnel safety, environment, anthropometry, and user documentation; plus intended-use and tailoring guidance. It is a quantified, source-attributed synthesis (heavily citing MIL-STD-1472G, MIL-HDBK-759C, DOD-HFDG-ATCCS, NUREG-0700, NASA-STD-3000, ANSI, OSHA, ISO 9241). Complements nasa-hsi as a parallel HSI tradition from the civil-aviation domain. Scope limits: it is design criteria, NOT an HSI lifecycle/process model (use nasa-hsi, nasa-npr-7123, or dau-se-guidebook for process); it does NOT reproduce the third-party standards it cites; it is FAA-acquisition-oriented (ATC, towers, TRACONs, airway facilities), not a general consumer-UX guide; and it is thin on modern touchscreen/mobile, web, and AI-driven interface patterns and on quantitative human-reliability 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。
Knowledge base from the DoD Systems Engineering Guidebook (OUSD R&E, February 2022). Use for the DoD SE process model — the 16 SE processes (8 technical management + 8 technical) mapped to ISO/IEC/IEEE 15288, the event-driven technical reviews and audits across the Major Capability Acquisition life cycle (ASR, SRR, SFR, PDR, CDR, SVR/FCA, PRR, PCA), the Systems Engineering Plan (SEP), risk/issue/opportunity management, TPMs and leading indicators, system-of-systems and digital engineering, and the 24 design considerations (RAM, system safety, HSI, system security engineering, MOSA, supportability, etc.). Acquisition-program oriented: thin on detailed cost estimating, contracting law, and non-DoD or commercial life cycles.
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Search the live web and 36+ specialised data sources including SEC filings, PubMed, ChEMBL, clinical trials, FRED economic indicators, and patent databases. Use when current, authoritative, or paywalled data is required.
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Define and implement Service Level Indicators (SLIs) and Service Level Objectives (SLOs) with error budgets and alerting. Use when establishing reliability targets, implementing SRE practices, or measuring service performance.
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CDC open data and WHO global health indicators. 3 tools for public health intelligence.
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Use when working with Bigpanda — bigPanda AIOps platform management covering event correlation, root cause analysis, incident management, alert enrichment, topology-based correlation, environment management, and analytics. Use when configuring BigPanda correlation patterns, investigating correlated incidents, tuning noise reduction, or analyzing alert topology and root cause indicators.
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Guide for modernizing and migrating MSBuild project files to SDK-style format. Only activate in MSBuild/.NET build context. USE FOR: converting legacy .csproj/.vbproj with verbose XML to SDK-style, migrating packages.config to PackageReference, removing Properties/AssemblyInfo.cs in favor of auto-generation, eliminating explicit <Compile Include> lists via implicit globbing, consolidating shared settings into Directory.Build.props. Indicators of legacy projects: ToolsVersion attribute, <Import Project="$(MSBuildToolsPath)">, .csproj files > 50 lines for simple projects. DO NOT USE FOR: projects already in SDK-style format, non-.NET build systems (npm, Maven, CMake), .NET Framework projects that cannot move to SDK-style. INVOKES: dotnet try-convert, upgrade-assistant tools.
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。
Container escape is a critical attack technique where an adversary breaks out of container isolation to access the host system or other containers. Tespit involves monitoring for escape indicators
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。
Tespit etme compromised cloud credentials across AWS, Azure, and GCP by analyzing anomalous API activity, impossible travel patterns, unauthorized resource provisioning, and credential abuse indicators using GuardDuty, Defender for Identity, and SCC Event Threat Tespit.
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 Office 365 Unified Audit Logs via Microsoft Graph API to tespit etmeemail forwarding rule creation, inbox delegation, suspicious OAuth app grants, and other indicators of account compromise.
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。
bu skill teaches security teams how to tespit etmeand respond to unauthorized cryptocurrency mining operations in cloud environments. It covers identifying cryptomining indicators through compute usage anomalies, network traffic patterns to mining pools, GuardDuty CryptoCurrency Bul:ings, and runtime process monitoring on EC2, ECS, EKS, and Azure Automation workloads.
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Legal-firm radar App-in-Skill (Busabase-backed) dashboard for anonymized casebase analytics, practice-area mix, case-quality indicators, lawyer capability profiles, brand proof points, and approval-gated management reports. Use when the user invokes $kelly-legal-firm-radar, mentions 律师画像, 律所经营分析, 业务布局分析, 案件质量评估, 专业人才梯队, 律师全息品牌, casebase analytics, law-firm management dashboard, or wants a Busabase-backed desk where partners review agent-prepared management insights before export.
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 process hollowing (T1055.012) by analyzing memory-mapped sections, hollowed process indicators, and parent-child process anomalies in EDR 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 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。