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análise-de-logs-de-acesso-do-api-gateway

Analisa logs de acesso do API Gateway (AWS API Gateway, Kong, Nginx) para detectar padrões de ataque.

O que é análise-de-logs-de-acesso-do-api-gateway?

Esta habilidade permite que agentes de IA analisem logs de acesso de gateways de API (como AWS API Gateway, Kong e Nginx) para identificar padrões de ataque, incluindo autorização de objeto com nível quebrado (BOLA), exposição excessiva de dados e tentativas de injeção. É especialmente útil para analistas de SOC que investigam incidentes de segurança, constroem regras de detecção ou realizam caça a ameaças. A análise utiliza Python com pandas para processar logs em lote, detectando padrões como enumeração sequencial de IDs de recurso (BOLA/IDOR), bypass de rate limit via manipulação de cabeçalhos, varreduras de credenciais (surtos de 401 de uma única origem), injeções SQL/NoSQL e métodos HTTP incomuns em endpoints somente leitura. A saída inclui dados agregados que podem ser usados para criar alertas ou feeds de inteligência de ameaças.

Funciona com~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-api-gateway-access-logs

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Documentação

Analisando Logs de Acesso do API Gateway

Quando Usar

  • Ao investigar incidentes de segurança que exigem análise de logs de acesso do API Gateway
  • 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

  • Familiaridade com conceitos e ferramentas de operações de segurança
  • Acesso a um ambiente de teste ou laboratório para execução segura
  • Python 3.8+ com dependências necessárias instaladas
  • Autorização apropriada para quaisquer atividades de teste

Instruções

Analise logs de acesso do API Gateway para identificar padrões de ataque, incluindo autorização de objeto com nível quebrado (BOLA), exposição excessiva de dados e tentativas de injeção.

import pandas as pd

df = pd.read_json("api_gateway_logs.json", lines=True)
# Detecta BOLA: mesmo usuário acessando muitos IDs de recurso diferentes
bola = df.groupby(["user_id", "endpoint"]).agg(
    unique_ids=("resource_id", "nunique")).reset_index()
suspicious = bola[bola["unique_ids"] > 50]

Principais padrões de detecção:

  1. BOLA/IDOR: enumeração sequencial de IDs de recurso
  2. Bypass de rate limit via manipulação de cabeçalhos
  3. Varredura de credenciais (surtos de 401 de uma única origem)
  4. Injeção SQL/NoSQL em parâmetros de consulta
  5. Métodos HTTP incomuns (DELETE, PATCH) em endpoints somente leitura

Exemplos

# Detecta surtos de 401 indicando varredura de credenciais
auth_failures = df[df["status_code"] == 401]
scanner_ips = auth_failures.groupby("source_ip").size()
scanners = scanner_ips[scanner_ips > 100]

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

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achieving-cmmc-level-2-compliance

>-

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