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analisando-pacotes-de-rede-com-scapy

Use o Scapy para construir, enviar, capturar e dissecar pacotes TCP/UDP/ICMP/DNS, analisar arquivos pcap, implementar varreduras SYN e detectar tráfego anômalo, como pacotes fragmentados ou malformados. Utilize-o ao realizar reconhecimento de rede autorizado, análise forense em nível de protocolo ou construção de detecção de anomalias de tráfego durante testes de segurança.

O que é analisando-pacotes-de-rede-com-scapy?

Esta habilidade permite que agentes de IA e desenvolvedores utilizem a biblioteca Scapy em Python para realizar tarefas avançadas de análise e manipulação de pacotes de rede. O Scapy é uma ferramenta poderosa para construir, enviar, capturar e dissecar pacotes em múltiplas camadas de protocolo, sendo essencial para atividades de segurança ofensiva e defensiva autorizadas, como análise forense de tráfego, varreduras SYN e detecção de anomalias. A habilidade cobre a leitura e análise de arquivos pcap/pcapng, extração de campos de protocolo (IP, TCP, UDP, DNS, HTTP), cálculo de estatísticas de tráfego, e identificação de padrões maliciosos como inundações SYN e exfiltração por DNS. Suporta ambientes Linux e Windows (com Npcap ou libpcap) e exige privilégios de administrador para operações de soquete bruto. O resultado esperado é um relatório JSON estruturado contendo estatísticas, distribuição de protocolos, principais IPs de origem/destino, anomalias detectadas e resumos por fluxo.

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npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-network-packets-with-scapy
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Documentação

Analisando Pacotes de Rede com Scapy

Visão Geral

O Scapy é uma biblioteca de manipulação de pacotes em Python que permite construir, enviar, capturar e dissecar pacotes de rede em camadas de protocolo granulares. Esta habilidade cobre o uso do Scapy para tarefas relacionadas à segurança, incluindo construção de pacotes TCP/UDP/ICMP, análise de arquivos pcap, extração de campos de protocolo, implementação de varreduras SYN, análise de consultas DNS e detecção de padrões de tráfego anômalos, como pacotes excessivamente fragmentados ou cabeçalhos malformados.

Quando Usar

  • Ao investigar incidentes de segurança que exigem análise de pacotes de rede com Scapy
  • 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 3.8+ com a biblioteca scapy instalada (pip install scapy)
  • Privilégios de root/administrador para operações de soquete bruto (captura, envio)
  • Npcap (Windows) ou libpcap (Linux) para captura de pacotes
  • Autorização para realizar operações de pacotes na rede alvo

Passos

  1. Ler e analisar arquivos pcap/pcapng com rdpcap() para análise off-line
  2. Extrair camadas de protocolo (IP, TCP, UDP, DNS, HTTP) e valores de campo
  3. Calcular estatísticas de tráfego: principais comunicadores, distribuição de protocolos, frequência de portas
  4. Detectar padrões de inundação SYN analisando as taxas de flags TCP
  5. Identificar indicadores de exfiltração por DNS por meio da análise de comprimento e entropia da consulta
  6. Construir pacotes de teste personalizados para testes de rede autorizados
  7. Exportar descobertas como um relatório JSON estruturado

Saída Esperada

Relatório JSON contendo estatísticas de pacotes, distribuição de protocolos, principais IPs de origem/destino, anomalias detectadas (inundações SYN, indicadores de tunelamento DNS, ataques de fragmentação) e resumos por fluxo.

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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