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analisando-artefatos-do-powershell-empire

Detecte artefatos do framework de pós-exploração PowerShell Empire nos logs de Script Block Logging (ID do Evento 4104) e Module Logging (ID do Evento 4103) do Windows, incluindo a string de inicialização padrão, payloads Base64 codificados com WebClient/FromBase64String, invocações de módulos conhecidos (Invoke-Mimikatz, Invoke-Kerberoast) e padrões de URL de staging. Use ao caçar ou confirmar atividade do Empire C2 em logs de eventos do Windows.

O que é analisando-artefatos-do-powershell-empire?

Esta habilidade foi projetada para analisar logs de eventos do Windows em busca de artefatos do PowerShell Empire, um framework de pós-exploração amplamente utilizado. Ela se concentra em dois tipos principais de logs: PowerShell Script Block Logging (ID 4104) e Module Logging (ID 4103). A habilidade identifica a string de inicialização padrão do Empire, payloads Base64 que contêm classes .NET como System.Net.WebClient e FromBase64String, e invocações de módulos maliciosos conhecidos, como Invoke-Mimikatz e Invoke-Kerberoast. Além disso, ela reconhece padrões de URL de staging e strings de user-agent. O resultado é um relatório JSON que inclui IOCs correspondentes, payloads decodificados, uma linha do tempo de eventos suspeitos, mapeamentos de técnicas MITRE ATT&CK e pontuações de severidade. A habilidade é útil para analistas de SOC, construção de regras de detecção e validação de cobertura de monitoramento de segurança.

Funciona com~Claude Code~Codex CLI~Cursor
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Documentação

Analisando Artefatos do PowerShell Empire

Visão Geral

PowerShell Empire é um framework de pós-exploração que consiste em listeners, stagers e agentes. Seus artefatos deixam vestígios detectáveis nos logs de eventos do Windows, particularmente no PowerShell Script Block Logging (ID do Evento 4104) e Module Logging (ID do Evento 4103). Esta habilidade analisa logs de eventos em busca da string de inicialização padrão do Empire (powershell -noP -sta -w 1 -enc), payloads codificados em Base64 contendo System.Net.WebClient e FromBase64String, invocações de módulos conhecidos (Invoke-Mimikatz, Invoke-Kerberoast, Invoke-TokenManipulation) e padrões de URL de staging.

Quando Usar

  • Ao investigar incidentes de segurança que exigem análise de artefatos do powershell empire
  • 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

  • Python 3.9+ com acesso ao Log de Eventos do Windows ou arquivos EVTX exportados
  • PowerShell Script Block Logging (ID do Evento 4104) habilitado via Política de Grupo
  • Module Logging (ID do Evento 4103) habilitado para cobertura abrangente

Principais Padrões de Detecção

  1. Inicializador padrão — powershell -noP -sta -w 1 -enc seguido por blob Base64
  2. Indicadores de stager — System.Net.WebClient, DownloadData, DownloadString, FromBase64String
  3. Assinaturas de módulo — Invoke-Mimikatz, Invoke-Kerberoast, Invoke-TokenManipulation, Invoke-PSInject, Invoke-DCOM
  4. Strings de user-agent — user-agents padrão do Empire na configuração do listener HTTP
  5. URLs de staging — /login/process.php, /admin/get.php e padrões de URI padrão semelhantes

Saída

Relatório JSON com IOCs correspondentes, payloads Base64 decodificados, linha do tempo de eventos suspeitos, mapeamentos de técnicas MITRE ATT&CK e pontuações de severidade.

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

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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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