waf-detect

waf-detect is a skill for Claude Code, Codex from woohyun212/security-skill. It costs 24 tokens per session (1,142 once invoked), scanned A, original, MIT.

A check that finds and identifies a web application firewall (WAF), a service that filters suspicious web requests before they reach an application.

In plain words
What is it for?
Use it to identify products such as Cloudflare, AWS WAF, or Akamai on a target URL, either with wafw00f or curl.
Why use it?
It shows whether a WAF may be changing test results or blocking requests during a security assessment.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to identify products such as Cloudflare, AWS WAF, or Akamai on a target URL, either with wafw00f or curl.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/woohyun212/security-skill/waf-detect
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add woohyun212/security-skill --skill waf-detect
Clone the repo
git clone --depth 1 https://github.com/woohyun212/security-skill

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for waf-detect

README.md
[![agentmods](https://agentmods.dev/badge/skills/woohyun212/security-skill/waf-detect/github.svg)](https://agentmods.dev/skills/woohyun212/security-skill/waf-detect)
Your own site
<a href="https://agentmods.dev/skills/woohyun212/security-skill/waf-detect"><img src="https://agentmods.dev/badge/skills/woohyun212/security-skill/waf-detect/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for waf-detect

Your own site · 80×15
<a href="https://agentmods.dev/skills/woohyun212/security-skill/waf-detect"><img src="https://agentmods.dev/badge/skills/woohyun212/security-skill/waf-detect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,142 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00024 $0.01142
Opus 5 $0.00012 $0.00571
Sonnet 5 $0.00005 $0.00228
Haiku 4.5 $0.00002 $0.00114

Measured 9d ago against content hash 13bebde16a91, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

waf-detect scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

Detects whether a WAF (Web Application Firewall) is present in front of a target URL using the `wafw00f` tool or manual curl fingerprinting, and identifies the specific WAF product — Cloudflare, AWS WAF, Akamai, F5 BIG-I
waf-detect/SKILL.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

What this skill does

Detects whether a WAF (Web Application Firewall) is present in front of a target URL using the wafw00f tool or manual curl fingerprinting, and identifies the specific WAF product — Cloudflare, AWS WAF, Akamai, F5 BIG-IP, and others.

When to use

  • Before formulating a WAF bypass strategy during the initial reconnaissance phase of a pentest or bug bounty engagement
  • When verifying that your own service's WAF is functioning correctly
  • When suspecting a WAF as the cause of false positives or false negatives from a scanner

Prerequisites

  • Python 3 and pip required (for wafw00f installation)
  • curl required (manual fallback method)
  • HTTP/HTTPS access to the target URL

Inputs

Variable Description Example
TARGET_URL Target URL to test https://example.com

Workflow

Step 1: Install wafw00f (if not installed)

# Check for wafw00f and install if missing
if ! command -v wafw00f &>/dev/null; then
  echo "wafw00f not found. Installing..."
  pip install wafw00f --quiet
else
  echo "wafw00f already installed: $(wafw00f --version 2>&1 | head -1)"
fi

Step 2: Detect WAF with wafw00f

TARGET_URL="https://example.com"

echo "=== wafw00f WAF detection ==="
wafw00f "$TARGET_URL" -a 2>&1
# -a : output all WAF candidates

Step 3: Manual fingerprinting when wafw00f is unavailable

echo ""
echo "=== Manual WAF fingerprinting (curl) ==="

# 1) Collect baseline headers with a normal request
echo "--- Normal request ---"
NORMAL=$(curl -s -I "$TARGET_URL" --max-time 10 2>&1)
echo "$NORMAL" | grep -iE "server:|x-powered-by:|cf-ray:|x-amz|x-cache|x-cdn|via:|x-sucuri|x-fw-|x-waf"

# 2) Send a malicious payload to trigger WAF response
echo ""
echo "--- Payload request (checking WAF reaction) ---"
ATTACK=$(curl -s -o /dev/null -w "%{http_code}" \
  "$TARGET_URL/?q=<script>alert(1)</script>" \
  --max-time 10 2>&1)
echo "XSS payload HTTP status: $ATTACK"

SQLI=$(curl -s -o /dev/null -w "%{http_code}" \
  "$TARGET_URL/?id=1'+OR+'1'='1" \
  --max-time 10 2>&1)
echo "SQLi payload HTTP status: $SQLI"

HEADERS_ATTACK=$(curl -s -I \
  "$TARGET_URL/?q=<script>alert(1)</script>" \
  --max-time 10 2>&1)
echo ""
echo "--- Payload request response headers ---"
echo "$HEADERS_ATTACK" | grep -iE "server:|cf-ray:|x-amz|x-cache|x-sucuri|x-iinfo:|x-check-cacheable:|x-fw-|set-cookie:"

Read the full file on GitHub · 121 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 121 lines · 24 tokens per session scan A 13bebde16a91

Subscribe to this mod's changes

waf-detect is a skill published in the GitHub repository woohyun212/security-skill (21 stars, last pushed 4mo ago), licensed MIT. It adds 24 tokens to every session and 1,142 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens