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Análisis de Registros de Actividad de Azure para Amenazas

Consulta los registros de actividad de Azure Monitor y los registros de inicio de sesión mediante azure-monitor-query.

¿Qué es Análisis de Registros de Actividad de Azure para Amenazas?

Esta habilidad permite a los agentes de IA, como Claude Code, ejecutar análisis de seguridad contra los registros de actividad de Azure (Azure Activity Logs) para identificar amenazas potenciales, como cambios maliciosos en roles, modificaciones en la configuración de recursos o anomalías en los inicios de sesión. Utiliza el SDK de Azure Monitor Query para ejecutar consultas KQL desde Python, aprovechando la autenticación gestionada de Azure (DefaultAzureCredential). Está diseñada para analistas de SOC, ingenieros de seguridad o desarrolladores que necesitan automatizar la búsqueda de amenazas en entornos Azure, probar reglas de detección o investigar incidentes. Soporta consultas sobre firmas de ataque comunes, como la escalada de privilegios mediante cambios en asignaciones de roles, el acceso a secretos de Key Vault desde IPs desconocidas o la modificación de políticas de acceso condicional. La habilidad se basa en un flujo de trabajo estructurado: definir la consulta KQL, ejecutarla contra el workspace de Log Analytics y analizar los resultados en busca de indicadores de compromiso.

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-azure-activity-logs-for-threats

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Documentación

¿Qué hace Análisis de Registros de Actividad de Azure para Amenazas?

Cuándo usar

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

Prerrequisitos

  • Familiaridad con conceptos y herramientas de operaciones de seguridad
  • Acceso a un entorno de pruebas o laboratorio para ejecución segura
  • Python 3.8+ con las dependencias requeridas instaladas
  • Autorización apropiada para cualquier actividad de prueba

Instrucciones

Usa azure-monitor-query para ejecutar consultas KQL contra workspaces de Azure Log Analytics, detectando operaciones administrativas sospechosas y anomalías en inicios de sesión.

from azure.identity import DefaultAzureCredential
from azure.monitor.query import LogsQueryClient
from datetime import timedelta

credential = DefaultAzureCredential()
client = LogsQueryClient(credential)

response = client.query_workspace(
    workspace_id="WORKSPACE_ID",
    query="AzureActivity | where OperationNameValue has 'MICROSOFT.AUTHORIZATION/ROLEASSIGNMENTS/WRITE' | take 10",
    timespan=timedelta(hours=24),
)

Consultas clave de detección:

  1. Cambios en asignaciones de roles (escalada de privilegios)
  2. Modificaciones en grupos de recursos y suscripciones
  3. Acceso a secretos de Key Vault desde nuevas IPs
  4. Cambios en reglas de grupos de seguridad de red
  5. Modificaciones en políticas de acceso condicional

Ejemplos

# Detectar nuevas asignaciones de rol de Administrador Global
query = '''
AuditLogs
| where OperationName == "Add member to role"
| where TargetResources[0].modifiedProperties[0].newValue has "Global Administrator"
'''

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-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,

analyzing-docker-container-forensics

Investigate compromised Docker containers by analyzing images, layers,

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