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cccskills

「threat-intelligence」の検索結果

114 件 ・ 関連度順

概要と使いどころ

Deploy MISP via Docker and configure feeds from sources like abuse.ch, AlienVault OTX, and CIRCL to aggregate, correlate, and distribute threat intelligence, including automated feed synchronization and STIX/TAXII-based integration with Splunk, Elasticsearch, and SOAR platforms. Use when standing up centralized IOC management or wiring multi-source threat feeds into a SIEM.

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-Skills3.4万2026年8月31日 更新

Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.

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-Skills3.4万2026年8月31日 更新

Collects and synthesizes open-source intelligence (OSINT) about threat actors, malicious infrastructure, and attack campaigns using publicly available data sources, passive reconnaissance tools, and dark web monitoring. Use when investigating external threat actor infrastructure, performing pre-engagement reconnaissance for authorized red team assessments, or enriching CTI reports with publicly available adversary context. Activates for requests involving Maltego, Shodan, OSINT framework, SpiderFoot, or infrastructure reconnaissance.

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-Skills3.4万2026年8月31日 更新

Parse cyber threat intelligence reports (Mandiant, CrowdStrike, Talos, Microsoft) with stix2, mitreattack-python, and spaCy to extract adversary behaviors, map them to MITRE ATT&CK technique IDs, and build a searchable STIX 2.1 attack-pattern library with detection templates. Use when cataloging attack patterns from CTI reports for threat-informed detection engineering, or generating Sigma/YARA templates from documented behaviors.

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-Skills3.4万2026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-Skills3.4万2026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-Skills3.4万2026年8月31日 更新

Safely monitor ransomware group Tor-hosted data leak sites (DLS) to collect and extract structured victim posting data, track group activity trends over time, and produce sector- and geography-specific ransomware risk assessments. Use when performing threat intelligence gathering on active ransomware groups or building proactive defense reporting from double-extortion leak-site activity.

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-Skills3.4万2026年8月31日 更新

Map advanced persistent threat (APT) group TTPs to the MITRE ATT&CK framework using the attackcti Python library to query STIX/TAXII data for group-technique associations, then generate ATT&CK Navigator layer files to visualize and compare defensive coverage against adversary profiles. Use when profiling an APT group's techniques, building Navigator coverage heatmaps, or assessing technique coverage gaps against a specific threat actor.

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-Skills3.4万2026年8月31日 更新

Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs, identifying wallet clusters and tracking fund movement through mixers and exchanges to support law enforcement attribution. Use when tracing ransomware bitcoin payments, performing cryptocurrency wallet forensics, or gathering blockchain threat intelligence on extortion payments.

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-Skills3.4万2026年8月31日 更新

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.

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-Skills3.4万2026年8月31日 更新

Query a MISP (Malware Information Sharing Platform) instance via PyMISP to compute event statistics, IOC type breakdowns, threat actor galaxy clusters, and tag trends, and generate threat landscape reports with temporal trends. Use when asked to analyze threat intelligence data, summarize top threat actors or malware families, or produce a CTI landscape report from MISP 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。

mukul975/Anthropic-Cybersecurity-Skills3.4万2026年8月31日 更新

Generate domain permutations with dnstwist and check DNS resolution to detect typosquatting, homograph phishing, and brand impersonation domains registered against your organization. Use when asked to monitor for lookalike domains, investigate a phishing domain, or assess brand-impersonation risk.

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-Skills3.4万2026年8月31日 更新

Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.

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-Skills3.4万2026年8月31日 更新

Query the Malpedia API to look up malware family aliases and naming (platform.family_name), pull community/vendor YARA rules, link families to threat actors, and map family relationships such as loader-payload chains and shared authorship. Use when researching a malware family's aliases, lineage, or actor attribution, or when sourcing YARA rules for 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。

mukul975/Anthropic-Cybersecurity-Skills3.4万2026年8月31日 更新

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

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-Skills3.4万2026年8月31日 更新

Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.

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-Skills3.4万2026年8月31日 更新

Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups' TTPs for detection-gap analysis. Use to compare threat-actor technique coverage, find gaps in detection engineering, or produce Navigator visualizations for threat-intel reporting.

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-Skills3.4万2026年8月31日 更新

URLScan.io is a free service for scanning and analyzing suspicious URLs. It captures screenshots, DOM content, HTTP transactions, JavaScript behavior, and network connections of web pages in an isolat

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-Skills3.4万2026年8月31日 更新

Delegate threat-intelligence research and updates to AgentSec, then validate the guide and landing mirrors.

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。

FlorianBruniaux/claude-code-ultimate-guide6,1492026年10月11日 更新

IOC extraction, threat intelligence correlation, MITRE ATT&CK mapping, hunt hypothesis generation, and detection rule creation

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。

Masriyan/Claude-Code-CyberSecurity-Skill4722026年9月8日 更新

Cyber threat intelligence production — the intelligence cycle, IOC extraction/normalization/enrichment, STIX/TAXII and MISP, structured analytic models (Diamond, Kill Chain, ATT&CK), source scoring, actor/campaign tracking, and finished intelligence reporting

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。

Masriyan/Claude-Code-CyberSecurity-Skill4722026年9月8日 更新

Threat actor infrastructure tracking involves monitoring and mapping adversary-controlled assets including command-and-control (C2) servers, phishing domains, exploit kit hosts, bulletproof hosting, a

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。

galyarderlabs/galyarder-framework252026年10月11日 更新

Operationalizes a threat intelligence report into hunts: extracting IOCs and TTPs, mapping behaviors to ATT&CK and available telemetry, prioritizing durable behavioral indicators over volatile atomic ones, and producing concrete hunt queries. Activates for requests to hunt from a threat report, operationalize CTI, or turn an intel report into 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。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Plan, run, and measure an adversary engagement operation using the MITRE Engage framework so that deployed deception is driven by strategy instead of deployed ad hoc. Covers the Engage Matrix (Prepare, Expose, Affect, Elicit, Understand), the 10-Step Operational Process, mapping engagement Activities to the ATT&CK techniques they expose, and defining measurable Goals and Operational Objectives. Use when a team has honeypots, honeytokens, or canary tokens but no coordinating strategy, when leadership asks "should we engage attackers and how", when building a deception/denial program, when writing an adversary engagement operation plan, or when deciding which deception Activities to deploy against a specific threat actor. Keywords: MITRE Engage, adversary engagement, cyber deception strategy, denial and deception, Engage Matrix, EAC, EGO, Expose Affect Elicit, deception program, honeypot strategy, engagement operation.

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。

andycungkrinx91/konoha92026年10月9日 更新