When a web application goes live, one of the earliest security questions developers and DevOps teams ask is:
How quickly can we stand up a Web Application Firewall (WAF) that actually protects traffic?
This hands-on comparison is based on real installations and basic attack tests of several self-hosted WAFs, with a focus on time to first effective protection, not marketing promises.
Test Environment
All WAFs were installed and tested under the same conditions:
- OS: Ubuntu 22.04 LTS
- CPU: 4 vCPUs
- Memory: 8 GB RAM
- Runtime: Docker 24.x (where applicable)
- Proxy: NGINX
- Goal: Block basic SQLi / XSS with minimal configuration
1. SafeLine WAF (Docker-based)
Deployment model: Docker / Docker Compose
Time to first protection: ~15 minutes
Installation Experience
mkdir -p "/data/safeline" && cd "/data/safeline"
wget https://waf.chaitin.com/release/latest/compose.yaml
docker compose up -d
The management UI becomes available at:
http://localhost:9443
Default rules and semantic analysis are enabled automatically.
Test Result
curl "http://example.test/?id=1 OR 1=1"
➡ Request blocked (HTTP 403)
Observations
Pros
- Very fast Docker-native deployment
- Built-in dashboard, logging, and rule management
- Semantic and behavior-based detection works out of the box
Cons
- Requires Docker and basic networking knowledge
- Advanced tuning takes time
- Logs can be verbose in high-traffic environments
Verdict:
One of the fastest paths from zero to meaningful protection in a self-hosted setup.
2. ModSecurity + OWASP Core Rule Set (CRS)
Deployment model: Web server module
Time to first protection: ~45–75 minutes
Installation Experience
apt install libnginx-mod-http-modsecurity
Manual steps required:
- Enable ModSecurity in NGINX
- Download and configure OWASP CRS
- Tune blocking mode
Test Result
curl "http://example.test/?q=<script>alert(1)</script>"
➡ Blocked by CRS rule
Observations
Pros
- Industry-standard rule engine
- Large community and documentation
- Deep inspection capability
Cons
- No UI or dashboards by default
- False positives common without tuning
- Slower time to usable protection
Verdict:
Powerful but slower to operationalize, especially for small teams.
3. BunkerWeb
Deployment model: NGINX security wrapper
Time to first protection: ~20–40 minutes
Installation Experience
BunkerWeb provides a bundled NGINX setup with a management UI and security presets.
Basic attack patterns are blocked by default.
Observations
Pros
- Clean UI
- Sane defaults
- Easier than raw ModSecurity
Cons
- Limited deep exploit and bot detection
- Often needs complementary security tools
- Smaller ecosystem
Verdict:
Good for quick protection on simple sites, less suitable for complex threat models.
4. OpenAppSec (Check Point)
Deployment model: Agent / SDK-based
Time to first protection: 1–2 hours (environment-dependent)
Installation Experience
- Requires environment mapping
- API integration or sidecar deployment
- ML-based detection setup
Observations
Pros
- Machine-learning-driven detection
- Strong for API and microservice security
- Backed by a major vendor
Cons
- Slower initial deployment
- Less intuitive for traditional VM-based stacks
- More moving parts
Verdict:
Strong for modern cloud-native stacks, but not the fastest to deploy.
Deployment Speed Comparison
| WAF | Time to First Protection | Setup Complexity |
|---|---|---|
| SafeLine WAF | ⭐⭐⭐⭐ (~15 min) | Medium |
| BunkerWeb | ⭐⭐⭐ (~20–40 min) | Low–Medium |
| ModSecurity + CRS | ⭐⭐ (~45–75 min) | High |
| OpenAppSec | ⭐ (~1–2 hrs) | Medium–High |
Key Takeaways
- Fast deployment matters, but only if default protection is meaningful.
- Container-based WAFs reduce setup friction dramatically.
- Traditional engines remain powerful but slower to operationalize.
- UI-driven tools trade depth for speed.
- ML-based solutions offer advanced detection at the cost of setup time.
Final Thoughts
There is no universally “best” self-hosted WAF—only the best fit for your team’s skills, infrastructure, and urgency.
If your priority is getting protected quickly, Docker-native WAFs provide the shortest path. If you need deep customization and have time to tune, traditional engines still deliver strong results.
In security, the fastest win is often deploying something effective today, rather than planning something perfect tomorrow.
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