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MISP 위협 환경 분석

PyMISP를 통해 MISP(Malware Information Sharing Platform) 인스턴스를 질의하여 위협 환경을 분석합니다.

MISP 위협 환경 분석란 무엇인가요?

이 스킬은 MISP(Malware Information Sharing Platform) 인스턴스와 통합하여 위협 인텔리전스 데이터를 체계적으로 분석하는 기능을 제공합니다. 보안 담당자가 위협 수준별 이벤트 통계, 속성 유형(IP, 도메인, 해시, URL) 분포, MITRE ATT&CK 기술 식별, 위협 행위자 활동 추적, IOC 제출 시계열 분석을 자동화할 수 있습니다. Python 기반의 PyMISP 라이브러리를 사용하며, CLI 명령어를 통해 손쉽게 실행할 수 있습니다. SOC 분석가, 위협 인텔리전스 팀, 보안 엔지니어가 침해 사고 조사, 탐지 규칙 구축, 위협 헌팅 및 보안 모니터링 적용 범위 검증 시 특히 유용합니다.

지원 대상~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-threat-landscape-with-misp
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이 에이전트 스킬이 미리 로드된 새 채팅을 엽니다.

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문서

MISP를 통한 위협 환경 분석

사용 시점

  • 위협 환경을 misp로 분석해야 하는 보안 인시던트 조사 시
  • 이 도메인에 대한 탐지 규칙 또는 위협 헌팅 쿼리 구축 시
  • SOC 분석가가 이 분석 유형에 대한 체계적인 절차를 필요로 할 때
  • 관련 공격 기술에 대한 보안 모니터링 적용 범위 검증 시

사전 요구 사항

  • 위협 인텔리전스 개념 및 도구에 대한 이해
  • 안전한 실행을 위한 테스트 또는 랩 환경 접근 권한
  • Python 3.8+ 및 필요한 종속성 설치
  • 모든 테스트 활동에 대한 적절한 권한

지침

  1. 종속성 설치: pip install pymisp
  2. MISP URL 및 API 키를 구성합니다.
  3. 에이전트를 실행하여 위협 환경 분석을 생성합니다:
    • 위협 수준 및 날짜 범위별 이벤트 통계 수집
    • 속성 유형 분포 분석(IP, 도메인, 해시, URL)
    • 이벤트 태그로부터 상위 MITRE ATT&CK 기술 식별
    • 은하 클러스터를 통한 위협 행위자 활동 추적
    • IOC 제출 시계열 추세 분석 생성
python scripts/agent.py --misp-url https://misp.local --api-key YOUR_KEY --days 90 --output landscape_report.json

예시

위협 환경 요약

기간: 최근 90일
분석된 이벤트: 1,247개
최고 위협 수준: 높음(43%)
최고 속성 유형: ip-dst(31%), 도메인(22%), sha256(18%)
최고 MITRE 기술: T1566 피싱(89개 이벤트)
최고 위협 행위자: APT28(34개 이벤트)

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

abusing-dpapi-for-credential-access

Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket

abusing-shadow-credentials-for-privesc

Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target

achieving-cmmc-level-2-compliance

>-

acquiring-disk-image-with-dd-and-dcfldd

Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.

analyzing-active-directory-acl-abuse

Detect dangerous ACL misconfigurations in Active Directory using ldap3

analyzing-android-malware-with-apktool

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.

analyzing-api-gateway-access-logs

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect

analyzing-apt-group-with-mitre-navigator

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

analyzing-azure-activity-logs-for-threats

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query

analyzing-bootkit-and-rootkit-samples

Analyzes bootkit and advanced rootkit malware infecting the Master

analyzing-browser-forensics-with-hindsight

Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user

analyzing-campaign-attribution-evidence

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.

analyzing-certificate-transparency-for-phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to

analyzing-cloud-storage-access-patterns

Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules.

analyzing-cobalt-strike-beacon-configuration

Extract and analyze Cobalt Strike beacon configuration from PE files

analyzing-cobaltstrike-malleable-c2-profiles

Parse and analyze Cobalt Strike Malleable C2 profiles with dissect.cobaltstrike (profiles and beacon-payload configs) and pyMalleableC2 (AST parsing) to extract HTTP/DNS transforms, URIs, headers, sleep/jitter, and injection behavior, then generate network detection signatures. Use when reverse-engineering a captured malleable profile or building detections against Cobalt Strike Beacon traffic.

analyzing-command-and-control-communication

Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom

analyzing-cyber-kill-chain

Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain

analyzing-disk-image-with-autopsy

Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.

analyzing-dns-logs-for-exfiltration

Analyzes DNS query logs to detect data exfiltration via DNS tunneling,

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