Analyzing Web Server Logs for Intrusion
SkillDatabases & dataThis skill helps your AI find SQL injection attempts in Apache and Nginx access logs, the records of requests made to a site. Once it is added, your AI can go through those logs and flag entries that look like intrusion attempts. You get a clear answer about suspicious activity without reading the logs yourself.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding it, point your AI at an Apache or Nginx access log and ask it to check the log for SQL injection attempts.
Then ask your AI: use the Analyzing Web Server Logs for Intrusion skill
What your AI can do with it
- Read Apache access logs
- Read Nginx access logs
- Flag SQL injection attempts found in the logs
- Show which log entries look suspicious
What this skill tells your AI
The instructions your AI receives, as published by 26zl/cybersec-toolkit in .claude/skills/analyzing-web-server-logs-for-intrusion/SKILL.md and read by ahel’s review.
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
- Install dependencies:
pip install geoip2 user-agents - Collect web server access logs in Combined Log Format (Apache) or Nginx default format.
- Parse each log entry extracting: IP, timestamp, method, URI, status code, response size, user-agent, referer.
- 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
- SQL injection:
- 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
Signals
- GitHub stars
- 54
- Forks
- 10
- Last commit
- Sep 2026
ahel review
K1binfo
installs-packages
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Catalog kind
- skill
- Gateway key
analyzing-web-server-logs-for-intrusion- Source
- github.com/26zl/cybersec-toolkit