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analisando-malware-android-com-apktool

Realize análise estática de malware Android em APK usando apktool para descompilação de recursos, jadx para recuperação de código Java e androguard para inspeção de manifesto, detecção de combinações perigosas de permissões e identificação de código ofuscado, carregamento dinâmico de código e chamadas de API baseadas em reflexão. Use para triagem estática de um APK suspeito sem executá-lo ou para construir regras de detecção de malware móvel.

O que é analisando-malware-android-com-apktool?

Este skill capacita agentes de IA a realizar análise estática de malware Android distribuído como arquivos APK, utilizando ferramentas como androguard, apktool e jadx. Ele é útil para analistas de SOC, engenheiros de segurança e desenvolvedores que precisam extrair permissões, atividades, serviços, receptores de broadcast e chamadas de API suspeitas sem executar a amostra. O skill suporta plataformas como Claude Code e outros agentes de linha de comando, fornecendo um fluxo de trabalho estruturado: desde a análise do manifesto até a detecção de padrões de ofuscação, carregamento dinâmico de código (DexClassLoader, Runtime.exec) e indicadores de rede (URLs, IPs). O resultado final é um relatório JSON detalhado com análise de permissões, componentes, chamadas suspeitas e mapeamentos MITRE ATT&CK para dispositivos móveis, facilitando a criação de regras de detecção e a triagem rápida de amostras maliciosas.

Funciona com~Claude Code~Codex CLI~Cursor

npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-android-malware-with-apktool

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Documentação

Analisando Malware Android com Apktool

Visão Geral

Malware Android distribuído como arquivos APK pode ser analisado estaticamente para extrair permissões, atividades, serviços, receptores de broadcast e chamadas de API suspeitas sem executar a amostra. Este skill utiliza androguard para análise programática de APKs, identificando combinações perigosas de permissões, padrões de código ofuscado, carregamento dinâmico de código, chamadas de API baseadas em reflexão e indicadores de comunicação de rede.

Quando Usar

Ao investigar incidentes de segurança que exigem análise de malware Android com apktool
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 androguard
apktool (para descompilação de recursos)
jadx (para recuperação de código Java, opcional)
Ambiente de análise isolado (VM ou sandbox)
Arquivos APK de amostra para análise

Passos

Analisar APK com androguard para extrair metadados do manifesto
Enumerar permissões solicitadas e sinalizar combinações perigosas
Listar atividades, serviços, receptores e provedores do manifesto
Escanear por chamadas de API suspeitas (reflexão, criptografia, SMS, telefonia)
Detectar padrões de carregamento dinâmico de código (DexClassLoader, Runtime.exec)
Extrair URLs, IPs e indicadores C2 codificados em strings
Gerar relatório de avaliação de risco com mapeamentos MITRE ATT&CK para dispositivos móveis

Saída Esperada

Relatório JSON com análise de permissões, listagem de componentes, chamadas de API suspeitas, indicadores de rede e pontuação de risco
Strings extraídas e possíveis IOCs do APK

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-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,

analyzing-docker-container-forensics

Investigate compromised Docker containers by analyzing images, layers,

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