Skills

Analyzing Web Server Logs For Intrusion

Parse Apache and Nginx access logs to detect SQL injection attempts, local file...

Install

npx skills add AgentFlocks/flocks --skill analyzing-web-server-logs-for-intrusion -g -a claude-code -y
Repository
AgentFlocks/flocks504
Category
Security
Updated
5d ago
License
Apache-2.0
Context cost
Lightabout 445 tokens
Runs scripts
Yes, review before use

What it does

Parse Apache and Nginx access logs to detect SQL injection attempts, local file inclusion, directory traversal, web scanner fingerprints, and brute-force patterns. Uses regex-based pattern matching against OWASP attack signatures, GeoIP enrichment for source attribution, and statistical anomaly detection for request frequency and response size outliers.

Analyzing Web Server Logs for Intrusion

When to Use

  • When investigating security incidents that require analyzing web server logs for intrusion
  • When building detection rules or threat hunting queries for this domain
  • When SOC analysts need structured procedures for this analysis type
  • When validating security monitoring coverage for related attack techniques

Prerequisites

  • Familiarity with security operations concepts and tools
  • Access to a test or lab environment for safe execution
  • Python 3.8+ with required dependencies installed
  • Appropriate authorization for any testing activities

Instructions

  1. Install dependencies: pip install geoip2 user-agents
  2. Collect web server access logs in Combined Log Format (Apache) or Nginx default format.
  3. Parse each log entry extracting: IP, timestamp, method, URI, status code, response size, user-agent, referer.
  4. Apply detection rules:
    • SQL injection: UNION SELECT, OR 1=1, ' OR ', hex encoding patterns
    • LFI/Path traversal: ../, /etc/passwd, /proc/self, php://filter
    • XSS: <script>, javascript:, onerror=, onload=
    • Scanner signatures: nikto, sqlmap, dirbuster, gobuster, wfuzz user-agents
    • Brute force: >50 POST requests to login endpoints from same IP in 5 minutes
  5. Enrich with GeoIP data and generate a prioritized findings report.
python scripts/agent.py --log-file /var/log/nginx/access.log --geoip-db GeoLite2-City.mmdb --output web_intrusion_report.json

Examples

Detect SQLi in 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

Scanner User-Agent Detection

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

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