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「across」の検索結果

4,750 件 ・ 関連度順

概要と使いどころ

Deploys and configures osquery for real-time endpoint monitoring using SQL-based queries to inspect running processes, open ports, installed software, and system configuration. Use when building visibility into endpoint state, threat hunting across fleet, or implementing compliance monitoring. Activates for requests involving osquery deployment, endpoint visibility, fleet management, or SQL-based endpoint querying.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Configure AWS Verified Access to provide VPN-less zero trust network access to internal apps, combining identity trust providers (IAM Identity Center, Okta/OIDC), device posture providers (CrowdStrike, Jamf), Cedar policy authoring, and Terraform deployment. Use when replacing VPN access with ZTNA, writing Cedar access policies, or deploying Verified Access instances, groups, and endpoints across AWS accounts.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Deploys Cisco Duo multi-factor authentication across enterprise applications, VPN, RDP, and SSH access points, covering Duo Authentication Proxy setup, adaptive authentication policies, device trust assessment, and phishing-resistant WebAuthn/FIDO2 deployment aligned with NIST 800-63B AAL2/AAL3. Use when adding or hardening MFA for remote access, VPN, or privileged logins with Duo.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Correlates disparate security incidents, IOCs, and adversary behaviors across time and organizations to identify unified threat campaigns, attribute them to common threat actors, and extract shared indicators for improved detection. Use when multiple incidents exhibit overlapping indicators, when sector-wide attack campaigns require cross-organizational analysis, or when building campaign-level intelligence products. Activates for requests involving campaign analysis, incident clustering, cross-organizational IOC correlation, or MISP correlation engine.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Correlates security events in IBM QRadar SIEM using AQL (Ariel Query Language), custom rules, building blocks, and offense management to detect multi-stage attacks across network, endpoint, and application log sources. Use when SOC analysts need to investigate QRadar offenses, build correlation rules, or tune detection logic for reducing false positives.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Builds vendor-agnostic detection rules using the Sigma rule format for threat detection across SIEM platforms including Splunk, Elastic, and Microsoft Sentinel. Use when creating portable detection logic from threat intelligence, mapping rules to MITRE ATT&CK techniques, or converting community Sigma rules into platform-specific queries using sigmac or pySigma backends.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Builds a structured vulnerability scanning workflow using tools like Nessus, Qualys, and OpenVAS to discover, prioritize, and track remediation of security vulnerabilities across infrastructure. Use when SOC teams need to establish recurring vulnerability assessment processes, integrate scan results with SIEM alerting, and build remediation tracking dashboards.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Respond to malware infections across enterprise endpoints by identifying the malware family, determining infection vectors, assessing spread, and executing containment, analysis, eradication, and recovery procedures aligned to MITRE ATT&CK. Use when responding to a confirmed or suspected malware infection, including trojan/worm/ransomware outbreaks, malware triage, or infected endpoint remediation.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Build a structured SOC escalation matrix defining severity tiers, response SLAs, tiered escalation paths, and notification procedures for security incidents, using context-driven criteria that combine business risk, asset criticality, and data sensitivity. Use when designing or revising how a SOC triages and escalates incidents across analyst tiers.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Design and deploy a Threat Intelligence Platform (TIP) by integrating open-source CTI tools (MISP, OpenCTI, TheHive, Cortex) into a unified system with feed ingestion pipelines, enrichment workflows, STIX/TAXII interoperability, and analyst dashboards. Use when architecting or standing up a centralized CTI platform to collect, analyze, and disseminate threat intelligence across a security team.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Systematically map threat actor behavior and observed IOCs to the MITRE ATT&CK framework, build technique coverage heatmaps with the ATT&CK Navigator, identify detection gaps, and produce actionable threat intelligence reports across the Enterprise, Mobile, and ICS matrices. Use when analyzing threat actor TTPs, correlating IOCs to specific ATT&CK techniques, or assessing defensive detection coverage against adversary behavior.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Run OAuth 2.0 device-code and illicit-consent phishing attacks against Microsoft Entra ID, using TokenTactics-style tooling to steal access and refresh tokens, bypass MFA, and pivot across Microsoft 365 services. Use for authorized red-team engagements simulating device-code or consent-grant phishing against a tenant you have explicit written permission to test.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Build an automated adversary infrastructure tracking system in Python (dnspython, python-whois, shodan, networkx) that pivots across passive DNS, certificate transparency logs, WHOIS records, and IP enrichment to map threat-actor C2 networks and flag newly registered domains matching known patterns. Use when pivoting from known indicators to discover related C2 infrastructure or maintaining a continuously updated map of a threat actor's network.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Drive the AADInternals PowerShell toolkit to perform Microsoft Entra ID tenant reconnaissance, access-token acquisition across Microsoft APIs, and federation/AD FS backdoor testing (Golden SAML, T1606.002) for defensive validation. Use during an authorized Entra ID/Microsoft 365 red-team assessment to map external attack surface or verify AD FS signing certs resist Golden SAML.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Use Sysinternals Autoruns to systematically enumerate and analyze malware persistence mechanisms across Windows registry run keys, scheduled tasks, services, drivers, and startup locations. Use when hunting for persistence during Windows incident response, triaging a compromised endpoint, or validating that malware autostart entries have been fully identified and removed.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Prepare a defense-contractor environment for CMMC Level 2 certification: scope CUI and FCI, implement the 110 NIST SP 800-171 Rev 2 security requirements across 14 families, compute the SPRS score with the DoD Assessment Methodology, manage a compliant POA&M, and ready the organization for a C3PAO assessment. Use when an organization handles Controlled Unclassified Information (CUI) under a DoD contract, when a contract carries DFARS clause 252.204-7012/7019/7020/7021, when preparing for or responding to a CMMC assessment, when computing or improving an SPRS score, when building a System Security Plan or POA&M for 800-171, or when scoping which systems are in the CUI boundary. Keywords: CMMC, CMMC Level 2, NIST 800-171, SP 800-171 Rev 2, CUI, FCI, SPRS, DFARS 7012, C3PAO, POA&M, System Security Plan, DoD Assessment Methodology, 110 controls, defense industrial base, DIB, FedRAMP equivalency.

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。

mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Master database schema and data migrations across ORMs (Sequelize, TypeORM, Prisma), including rollback strategies and zero-downtime deployments.

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。

davila7/claude-code-templates3.3万2026年10月15日 更新

SEOAgent

無料

Persistent SEO workflow for Claude Code — run a technical SEO audit, build a hub-and-spoke keyword strategy, write page-type-aware content briefs, and draft SEO-optimized articles, persisting every artifact to a .seoagent/ workspace so the work compounds across sessions. Use when auditing a site's technical SEO, planning a keyword/content strategy, writing content briefs, drafting SEO articles with structured data, or resuming SEO work started in a previous session.

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。

davila7/claude-code-templates3.3万2026年10月15日 更新

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

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。

davila7/claude-code-templates3.3万2026年10月15日 更新

loki-mode

無料

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

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。

davila7/claude-code-templates3.3万2026年10月15日 更新

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

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。

davila7/claude-code-templates3.3万2026年10月15日 更新

Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.

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。

davila7/claude-code-templates3.3万2026年10月15日 更新

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.

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。

davila7/claude-code-templates3.3万2026年10月15日 更新

Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing multi-language support, or measuring code generation quality. Industry standard from BigCode Project used by HuggingFace leaderboards.

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。

davila7/claude-code-templates3.3万2026年10月15日 更新