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Analizando Registros de Auditoría de Office 365 en Busca de Com…

Analiza los Registros de Auditoría Unificados de Office 365 a través de la API de Microsoft Graph para detectar compromisos de correo electrónico empresarial.

¿Qué es Analizando Registros de Auditoría de Office 365 en Busca de Com…?

Esta habilidad permite a los agentes de IA analizar los Registros de Auditoría Unificados de Office 365 mediante la API de Microsoft Graph para detectar señales de compromiso de correo electrónico empresarial (BEC). Está diseñada para investigadores de seguridad, analistas SOC y desarrolladores que construyen reglas de detección o realizan caza de amenazas. La habilidad identifica actividades sospechosas como creación de reglas de bandeja de entrada, reenvío de correo a direcciones externas, cambios en delegaciones de buzones y concesiones de consentimiento de aplicaciones OAuth no autorizadas. Funciona en plataformas donde se puede ejecutar código Python con las dependencias `msal` y `requests`, siempre que se tenga una aplicación registrada en Azure AD con los permisos adecuados. El resultado es un informe JSON detallado que incluye una línea de tiempo de los indicadores de compromiso y puntuaciones de riesgo para cada buzón afectado.

Compatible con~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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Documentación

Analizando Registros de Auditoría de Office 365 en Busca de Compromiso

Descripción General

Los ataques de Compromiso de Correo Electrónico Empresarial (BEC) a menudo dejan rastros en los registros de auditoría de Office 365: creación sospechosa de reglas de bandeja de entrada, reenvío de correo a direcciones externas, cambios en delegaciones de buzones y concesiones de consentimiento no autorizadas para aplicaciones OAuth. Esta habilidad utiliza la API de Microsoft Graph para consultar el Registro de Auditoría Unificado, enumerar las reglas de bandeja de entrada en los buzones, detectar configuraciones de reenvío e identificar indicadores de cuentas comprometidas.

Cuándo Usar

Al investigar incidentes de seguridad que requieren analizar registros de auditoría de Office 365 en busca de compromiso
Al construir reglas de detección o consultas de caza de amenazas para este dominio
Cuando los analistas SOC necesitan procedimientos estructurados para este tipo de análisis
Al validar la cobertura de monitoreo de seguridad para técnicas de ataque relacionadas

Prerrequisitos

Registro de aplicación en Azure AD con permisos AuditLog.Read.All, MailboxSettings.Read, Mail.Read (permisos de aplicación)
Python 3.9+ con msal, requests
Secreto de cliente o certificado para autenticación
Rol de Lector Global o Lector de Seguridad

Pasos

Autenticarse en Microsoft Graph usando el flujo de credenciales de cliente de MSAL
Consultar el Registro de Auditoría Unificado en busca de operaciones sospechosas (Set-Mailbox, New-InboxRule)
Enumerar las reglas de bandeja de entrada en los buzones y marcar las reglas de reenvío
Detectar cambios en delegaciones de buzones (Add-MailboxPermission)
Identificar concesiones de consentimiento OAuth a aplicaciones sospechosas
Verificar patrones de inicio de sesión sospechosos desde los registros de auditoría
Generar un informe de indicadores de compromiso con línea de tiempo

Salida Esperada

Informe JSON que enumera reglas de reenvío, cambios en delegaciones, concesiones OAuth y eventos de auditoría sospechosos con puntuaciones de riesgo
Línea de tiempo de indicadores de compromiso con los buzones afectados

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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