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mukul975
27c6414ca5
Complete skill folder anatomy across all cybersecurity skills: - scripts/agent.py: 80-150 line Python agents using real libraries (impacket, boto3, azure-mgmt-*, kubernetes, pefile, yara, scapy, shodan, stix2, etc.) - references/api-reference.md: real API documentation with method signatures - LICENSE: MIT license for all skill folders
38 lines
1.6 KiB
Markdown
38 lines
1.6 KiB
Markdown
---
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name: analyzing-web-server-logs-for-intrusion
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description: >-
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Parse Apache and Nginx access logs to detect SQL injection attempts, local file inclusion,
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directory traversal, web scanner fingerprints, and brute-force patterns. Uses regex-based
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pattern matching against OWASP attack signatures, GeoIP enrichment for source attribution,
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and statistical anomaly detection for request frequency and response size outliers.
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---
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## Instructions
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1. Install dependencies: `pip install geoip2 user-agents`
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2. Collect web server access logs in Combined Log Format (Apache) or Nginx default format.
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3. Parse each log entry extracting: IP, timestamp, method, URI, status code, response size, user-agent, referer.
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4. Apply detection rules:
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- SQL injection: `UNION SELECT`, `OR 1=1`, `' OR '`, hex encoding patterns
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- LFI/Path traversal: `../`, `/etc/passwd`, `/proc/self`, `php://filter`
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- XSS: `<script>`, `javascript:`, `onerror=`, `onload=`
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- Scanner signatures: nikto, sqlmap, dirbuster, gobuster, wfuzz user-agents
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- Brute force: >50 POST requests to login endpoints from same IP in 5 minutes
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5. Enrich with GeoIP data and generate a prioritized findings report.
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```bash
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python scripts/agent.py --log-file /var/log/nginx/access.log --geoip-db GeoLite2-City.mmdb --output web_intrusion_report.json
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```
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## Examples
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### Detect SQLi in URI
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```
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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
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```
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### Scanner User-Agent Detection
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```
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Nikto/2.1.6, sqlmap/1.7, DirBuster-1.0-RC1, gobuster/3.1.0
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```
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