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In Part1,we covered how to deploy and configure , a free and open source WAF built by Chaitin Tech.
Now it’s time to test it.
? Smart Detection: Semantic Analysis Engine
SafeLine doesn’t rely on basic rule-matching. Its built-in semantic analysis engine deeply understands request intent, making it way more accurate against modern attacks.
? Advanced Defense
- Web attacks: SQLi, XSS, RCE, CRLF, XXE, SSRF, etc.
- Bot Defense: CAPTCHA, rate limiting, anti-crawlers
- HTTP Flood: Throttle IPs that exceed traffic thresholds
- Authentication: Enforce login for sensitive endpoints
- Threat Intelligence: Auto-block IPs from known bad actors
# SQL Injection
# XSS
<img+src=x+onerror=alert()>
# Path Traversal
# Code Injection
# XXE
<?xml+version="1.0"?><!DOCTYPE+foo+SYSTEM+"">
? Test with BlazeHTTP (WAF Benchmark Tool)
Run this Docker container to benchmark SafeLine’s protection:
docker run --rm --net=host chaitin/blazehttp:latest /app/blazehttp -t ""
? Real Test Results
| WAF | Accuracy | Detection | Miss Rate | False Positives |
|---|---|---|---|---|
| SafeLine (Personal - Balanced) | 99.45% | 71.65% | 28.35% | 0.07% |
| SafeLine (Personal - Strict) | 99.38% | 76.17% | 23.83% | 0.22% |
| SafeLine (Pro - Strict) | 99.66% | 90.68% | 9.32% | 0.07% |
| CloudFlare | 98.40% | 10.70% | 89.30% | 0.07% |
| ModSecurity L1 | 82.39% | 82.26% | 17.74% | 17.61% |
| ModSecurity L4 | 48.32% | 96.77% | 3.23% | 52.49% |
? Accuracy = (Correct Blocks + Correct Passes) / Total Samples
? Detection Rate = Correct Blocks / Attack Samples
? Miss Rate = Incorrect Passes / Attack Samples
? False Positive Rate = Incorrect Blocks / Normal Samples
- Personal Edition: Lightweight, runs with just 1 CPU + 1GB RAM, handles ~800 QPS
- Lite Edition: Efficient and low-resource friendly
- Pro Edition: Full performance, maxes out server capacity
Minimum requirements:
- CPU: 1 core
- RAM: 2 GB
- Disk: 60 GB, 2000 IOPS
Scale up: Add 1 core, 2 GB RAM, and 40 GB disk for every 1000 QPS.
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