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Mapped every skill to NIST CSF 2.0 subcategory IDs (GV/ID/PR/DE/RS/RC functions) based on subdomain and content analysis. Restores 11 skills corrupted during prior rebase, re-enriching with ATLAS, D3FEND, NIST AI RMF, and CSF 2.0 fields. All 754 skills now carry structured mappings for all 5 security frameworks: - MITRE ATT&CK (in tags) - MITRE ATLAS v5.5 (atlas_techniques) - MITRE D3FEND v1.3 (d3fend_techniques) - NIST AI RMF 1.0 (nist_ai_rmf) - NIST CSF 2.0 (nist_csf)
2.3 KiB
2.3 KiB
name, description, domain, subdomain, tags, version, author, license, nist_csf
| name | description | domain | subdomain | tags | version | author | license | nist_csf | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| analyzing-web-server-logs-for-intrusion | 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. | cybersecurity | security-operations |
|
1.0 | mahipal | Apache-2.0 |
|
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
- 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