Anthropic-Cybersecurity-Skills detecting-sql-injection-via-waf-logs
Analyze WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity
install
source · Clone the upstream repo
git clone https://github.com/mukul975/Anthropic-Cybersecurity-Skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/detecting-sql-injection-via-waf-logs" ~/.claude/skills/mukul975-anthropic-cybersecurity-skills-detecting-sql-injection-via-waf-logs && rm -rf "$T"
manifest:
skills/detecting-sql-injection-via-waf-logs/SKILL.mdsource content
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
- Install dependencies:
pip install requests - Collect WAF logs (ModSecurity audit log, AWS WAF JSON logs, or Cloudflare firewall events).
- 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
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