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.
npx skills add woohyun212/security-skill --skill waf-detectgit clone --depth 1 https://github.com/woohyun212/security-skillWrote 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.
[](https://agentmods.dev/skills/woohyun212/security-skill/waf-detect)<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.
<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>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.
| Model | Per session | Once 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 |
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 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
wafw00finstallation) curlrequired (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:"
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.
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.
- 9d ago First seen · 121 lines · 24 tokens per session scan A 13bebde16a91
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.
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