# Detecting SQL Injection Via Waf Logs

> Analyze WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity audit logs and JSON WAF event logs to identify SQLi patterns (UNION SELECT, OR 1=1, SLEEP(), BENCHMARK()), tracks attack sources, correlates multi-stage injection attempts, and generates incident reports with OWASP classification.

- Skill: `yanacuti1121/detecting-sql-injection-via-waf-logs` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds add yanacuti1121/detecting-sql-injection-via-waf-logs`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yanacuti1121/detecting-sql-injection-via-waf-logs/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- License: Apache-2.0
- Author: yanacuti1121 (https://skillmd.com/u/yanacuti1121)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/yanacuti1121/detecting-sql-injection-via-waf-logs

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# Detecting SQL Injection via WAF Logs


## When to Use

- When investigating security incidents that require detecting sql injection via waf logs
- 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 requests`
2. Collect WAF logs (ModSecurity audit log, AWS WAF JSON logs, or Cloudflare firewall events).
3. Run the agent to parse and analyze:
   - Detect SQLi payloads via 15+ regex patterns
   - Classify attacks by OWASP injection type (classic, blind, time-based, UNION-based)
   - Identify persistent attackers by IP clustering
   - Correlate multi-request injection campaigns
   - Calculate attack success probability based on response codes

```bash
python scripts/agent.py --log-file /var/log/modsec_audit.log --format modsecurity --output sqli_report.json
```

## Examples

### ModSecurity SQLi Detection
```
Rule 942100 triggered: SQL Injection Attack Detected via libinjection
URI: /api/users?id=1' UNION SELECT username,password FROM users--
Source IP: 203.0.113.42 (47 requests in 5 minutes)
Classification: UNION-based SQLi campaign
```

