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Office 365 감사 로그 분석을 통한 침해 탐지

Microsoft Graph API를 통해 Office 365 통합 감사 로그를 파싱하여 비즈니스 이메일 침해(BEC) 공격의 흔적을 탐지합니다.

Office 365 감사 로그 분석을 통한 침해 탐지란 무엇인가요?

이 스킬은 Microsoft Graph API를 사용하여 Office 365 통합 감사 로그를 쿼리하고, 의심스러운 받은 편지함 규칙 생성, 외부 주소로의 이메일 전달 설정, 사서함 위임 변경, 승인되지 않은 OAuth 애플리케이션 동의 부여 등 Business Email Compromise(BEC) 공격의 주요 징후를 식별합니다. 보안 운영 센터(SOC) 분석가가 침해 사고를 조사하거나 탐지 규칙을 구축할 때 유용하며, 사전 정의된 단계별 절차를 통해 체계적인 분석을 지원합니다. Azure AD 앱 등록(AuditLog.Read.All, MailboxSettings.Read, Mail.Read 권한 필요)과 Python 3.9+ 환경에서 msal 및 requests 라이브러리를 사용하여 동작하며, 최종적으로 위험 점수와 타임라인이 포함된 JSON 보고서를 생성합니다. 이 스킬은 다양한 AI 에이전트 플랫폼(예: Claude Code, Cursor, Codex)과 호환되며, Microsoft Graph API를 통한 실시간 감사 로그 분석을 자동화하여 보안 모니터링 커버리지를 강화합니다.

지원 대상~Claude Code~Codex CLI~Cursor
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문서

Office 365 감사 로그 분석을 통한 침해 탐지은(는) 무엇을 하나요?

개요

BEC(Business Email Compromise) 공격은 Office 365 감사 로그에 의심스러운 받은 편지함 규칙 생성, 외부 주소로의 이메일 전달, 사서함 위임 변경, 승인되지 않은 OAuth 애플리케이션 동의 부여 등의 흔적을 남깁니다. 이 스킬은 Microsoft Graph API를 사용하여 통합 감사 로그를 쿼리하고, 사서함별 받은 편지함 규칙을 열거하며, 전달 구성을 탐지하고, 손상된 계정 지표를 식별합니다.

사용 시기

  • Office 365 감사 로그 분석을 통한 침해 탐지가 필요한 보안 사고를 조사할 때
  • 이 도메인에 대한 탐지 규칙 또는 위협 헌팅 쿼리를 구축할 때
  • SOC 분석가가 이 분석 유형에 대한 구조화된 절차가 필요할 때
  • 관련 공격 기술에 대한 보안 모니터링 커버리지를 검증할 때

사전 요구 사항

  • AuditLog.Read.All, MailboxSettings.Read, Mail.Read (애플리케이션 권한)이 있는 Azure AD 앱 등록
  • Python 3.9+ 및 msal, requests
  • 인증을 위한 클라이언트 암호 또는 인증서
  • 전역 읽기 권한자 또는 보안 읽기 권한자 역할

단계

  1. MSAL 클라이언트 자격 증명 흐름을 사용하여 Microsoft Graph 인증
  2. 의심스러운 작업(Set-Mailbox, New-InboxRule)에 대한 통합 감사 로그 쿼리
  3. 사서함별 받은 편지함 규칙 열거 및 전달 규칙 플래그 지정
  4. 사서함 위임 변경(Add-MailboxPermission) 탐지
  5. 의심스러운 애플리케이션에 대한 OAuth 동의 부여 식별
  6. 감사 로그에서 의심스러운 로그인 패턴 확인
  7. 타임라인이 포함된 침해 지표 보고서 생성

예상 출력

  • 전달 규칙, 위임 변경, OAuth 동의 부여, 위험 점수가 포함된 의심스러운 감사 이벤트를 나열하는 JSON 보고서
  • 영향을 받은 사서함과 함께 침해 지표의 타임라인

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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