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detecting-sql-injection-via-waf-logs

detecting-sql-injection-via-waf-logs

github.com/mukul975Security35.2k180 installsUpdated 8w ago
Repository

About detecting-sql-injection-via-waf-logs

A SQL injection detection procedure for SOC analysts working with WAF logs. It describes log parsing, attack classification, source clustering, and request correlation.

Key features

  1. 01Parse several WAF log formats
  2. 02Detect SQL injection with regex patterns
  3. 03Classify by OWASP injection type
  4. 04Cluster IPs to identify persistent attackers
  5. 05Correlate campaigns and estimate success likelihood

Use cases

  1. 01Investigate SQL injection events in WAF logs
  2. 02Build injection detection rules
  3. 03Analyze attacks from recurring IP addresses
  4. 04Validate security monitoring coverage

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill detecting-sql-injection-via-waf-logs

After installing, type/detecting-sql-injection-via-waf-logsin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

LICENSE
references/
api-reference.md
scripts/
agent.py

Details

From the project README

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
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

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