waf-detect

To detect a Web Application Firewall, you can use automated tools like wafw00f or manual curl fingerprinting against the target URL. This process identifies specific WAF products such as Cloudflare, AWS WAF, or Akamai by analyzing response behaviors.

WAF fingerprinting is the process of identifying the specific Web Application Firewall product in front of a target. You need it during reconnaissance and penetration testing to verify WAF presence, enabling accurate threat modeling and targeted bypass planning.

You need Python 3 with wafw00f installed via pip for automated WAF detection. However, a manual fallback using curl is supported for fingerprinting if the automated tooling is unavailable, provided you have network access to the target URL.

Yes, you can use manual curl requests to check for WAFs like F5 BIG-IP. The detection workflow supports a manual fingerprinting fallback, allowing you to identify WAF products by sending specific HTTP requests and analyzing the responses.

The best way to identify WAFs like Cloudflare or AWS WAF during a bug bounty engagement is running an automated wafw00f check against the target URL. This quickly verifies WAF presence and type, allowing you to tailor your security assessment approach.

A limitation of using wafw00f for WAF detection is its dependency on Python 3 and network access to the target URL. If the tool is unavailable or network access is restricted, you must rely on manual curl fingerprinting to identify the WAF product.