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análise-de-logs-de-auditoria-do-office365-para-comprometimento

Analisar logs de auditoria unificada do Office 365 por meio da API do Microsoft Graph para detectar comprometimento de e-mail corporativo (BEC).

O que é análise-de-logs-de-auditoria-do-office365-para-comprometimento?

Esta skill capacita agentes de IA a investigar incidentes de segurança envolvendo comprometimento de e-mail corporativo (BEC) no Office 365. Ela utiliza a API do Microsoft Graph para consultar o Log de Auditoria Unificada, enumerar regras de caixa de entrada em várias caixas postais, detectar configurações de encaminhamento suspeitas e identificar mudanças de delegação de caixa postal e concessões de consentimento de aplicativos OAuth não autorizadas. É útil para analistas de SOC criarem regras de detecção, realizarem caça a ameaças e validarem a cobertura de monitoramento de segurança. A skill exige uma conta de serviço com permissões de aplicativo para 'AuditLog.Read.All', 'MailboxSettings.Read' e 'Mail.Read', além de Python 3.9+ com as bibliotecas 'msal' e 'requests'. No final, gera um relatório JSON contendo uma linha do tempo dos indicadores de comprometimento, regras de encaminhamento, mudanças de delegação e concessões OAuth, cada um com pontuações de risco.

Funciona com~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-office365-audit-logs-for-compromise
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Documentação

Analisando Logs de Auditoria do Office 365 para Comprometimento

Visão Geral

Ataques de Comprometimento de E-mail Corporativo (BEC) frequentemente deixam rastros nos logs de auditoria do Office 365: criação suspeita de regras de caixa de entrada, encaminhamento de e-mail para endereços externos, alterações de delegação de caixa postal e concessões de consentimento de aplicativos OAuth não autorizadas. Esta skill usa a API do Microsoft Graph para consultar o Log de Auditoria Unificada, enumerar regras de caixa de entrada em várias caixas postais, detectar configurações de encaminhamento e identificar indicadores de contas comprometidas.

Quando Usar

  • Ao investigar incidentes de segurança que exigem a análise de logs de auditoria do Office 365 para comprometimento
  • Ao construir regras de detecção ou consultas de caça a ameaças para este domínio
  • Quando analistas de SOC precisam de procedimentos estruturados para este tipo de análise
  • Ao validar a cobertura de monitoramento de segurança para técnicas de ataque relacionadas

Pré-requisitos

  • Registro de aplicativo do Azure AD com permissões AuditLog.Read.All, MailboxSettings.Read, Mail.Read (permissões de aplicativo)
  • Python 3.9+ com msal, requests
  • Segredo do cliente ou certificado para autenticação
  • Função de Leitor Global ou Leitor de Segurança

Passos

  1. Autenticar no Microsoft Graph usando o fluxo de credenciais do cliente MSAL
  2. Consultar o Log de Auditoria Unificada para operações suspeitas (Set-Mailbox, New-InboxRule)
  3. Enumerar regras de caixa de entrada em várias caixas postais e sinalizar regras de encaminhamento
  4. Detectar alterações de delegação de caixa postal (Add-MailboxPermission)
  5. Identificar concessões de consentimento OAuth para aplicativos suspeitos
  6. Verificar padrões de login suspeitos nos logs de auditoria
  7. Gerar relatório de indicadores de comprometimento com linha do tempo

Saída Esperada

  • Relatório JSON listando regras de encaminhamento, alterações de delegação, concessões OAuth e eventos de auditoria suspeitos com pontuações de risco
  • Linha do tempo dos indicadores de comprometimento com as caixas postais afetadas

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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