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analisando-logs-de-servidor-web-para-intrusao

Analisar logs de acesso do Apache e Nginx para detectar tentativas de injeção SQL e outros ataques.

O que é analisando-logs-de-servidor-web-para-intrusao?

Esta skill automatiza a análise de logs de servidores web (Apache e Nginx) para detectar atividades maliciosas, como injeção SQL, path traversal, XSS, scanners e ataques de força bruta. Ela é útil para analistas SOC, engenheiros de segurança e desenvolvedores que precisam investigar incidentes, construir regras de detecção ou validar a cobertura de monitoramento. Suporta plataformas baseadas em Python e utiliza bibliotecas como geoip2 e user-agents para enriquecimento de dados. O processo envolve instalar dependências, coletar logs no formato Combined Log, aplicar regras de detecção específicas (por exemplo, padrões como UNION SELECT para SQLi, ../ para path traversal) e gerar um relatório priorizado com dados GeoIP.

Funciona com~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-web-server-logs-for-intrusion
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Documentação

Analisando Logs de Servidor Web para Intrusão

Quando Usar

  • Ao investigar incidentes de segurança que exigem análise de logs de servidor web para intrusão
  • Ao construir regras de detecção ou consultas de caça a ameaças para este domínio
  • Quando analistas 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

  1. Instalar dependências: pip install geoip2 user-agents
  2. Coletar logs de acesso do servidor web no Formato de Log Combinado (Apache) ou formato padrão do Nginx.
  3. Analisar cada entrada de log extraindo: IP, timestamp, método, URI, código de status, tamanho da resposta, user-agent, referer.
  4. Aplicar regras de detecção:
    • Injeção SQL: UNION SELECT, OR 1=1, ' OR ', padrões de codificação hexadecimal
    • LFI/Path traversal: ../, /etc/passwd, /proc/self, php://filter
    • XSS: <script>, javascript:, onerror=, onload=
    • Assinaturas de scanners: user-agents nikto, sqlmap, dirbuster, gobuster, wfuzz
    • Força bruta: >50 requisições POST para endpoints de login do mesmo IP em 5 minutos
  5. Enriquecer com dados GeoIP e gerar um relatório de achados priorizados.
python scripts/agent.py --log-file /var/log/nginx/access.log --geoip-db GeoLite2-City.mmdb --output web_intrusion_report.json

Exemplos

Detectar SQLi na URI

192.168.1.100 - - [15/Jan/2024:10:30:45 +0000] "GET /products?id=1' UNION SELECT username,password FROM users-- HTTP/1.1" 200 4532

Detecção de User-Agent de Scanner

Nikto/2.1.6, sqlmap/1.7, DirBuster-1.0-RC1, gobuster/3.1.0

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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