waf-detection

waf-detection is a skill for Claude Code from MingyiSecLab/Mingyi-Atlas. It costs 26 tokens per session (422 once invoked), scanned A, original, Apache-2.0.

A guide for identifying web application firewalls and other front-end proxies, such as Cloudflare, AWS WAF, Akamai, and Imperva.

In plain words
What is it for?
Use it to fingerprint the front-end protection from tools, response headers, cookies, and proxy behavior, then record the observed web stack.
Why use it?
These services can change how requests are filtered and can hide details about the server behind them.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to fingerprint the front-end protection from tools, response headers, cookies, and proxy behavior, then record the observed web stack.

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Install with agentmods
npx agentmods add skills/mingyiseclab/mingyi-atlas/waf-detection
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 MingyiSecLab/Mingyi-Atlas --skill waf-detection
Clone the repo
git clone --depth 1 https://github.com/MingyiSecLab/Mingyi-Atlas

Made for: Claude Code.

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-detection

README.md
[![agentmods](https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/waf-detection/github.svg)](https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/waf-detection)
Your own site
<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/waf-detection"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/waf-detection/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-detection

Your own site · 80×15
<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/waf-detection"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/waf-detection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 422 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 $0.00026 $0.00422
Opus 5 $0.00013 $0.00211
Sonnet 5 $0.00005 $0.00084
Haiku 4.5 $0.00003 $0.00042

Measured 9d ago against content hash 97e54a5e7ae6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

waf-detection 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.

curl -s "https://<target>/?id=1' OR '1'='1" -I | grep -iE '(server|x-cdn|cf-ray|x-sucuri|x-aws)'
src/skills/standard/recon/web-recon/waf-detection/SKILL.md · 40 lines

What it actually says

WAF Detection & Fingerprinting

Identify any front-end shield (Cloudflare, AWS WAF, Akamai, Imperva, etc.) so exploit can choose appropriate evasion (encoding, payload obfuscation, alternate transport). A multi-proxy/CDN stack is also the recognition signal for HTTP request smuggling — note this for handoff.

Tooling

# wafw00f
wafw00f https://<target>

# Manual detection via response patterns
curl -s "https://<target>/?id=1' OR '1'='1" -I | grep -iE '(server|x-cdn|cf-ray|x-sucuri|x-aws)'

Known WAF Indicators

WAF Signal
Cloudflare CF-RAY header, __cfduid cookie
AWS WAF x-amzn-requestid header
Akamai AkamaiGHost server header
Imperva X-CDN header, incap_ses cookie
Sucuri X-Sucuri-ID header
F5 BIG-IP BIGipServer cookie

Multi-Proxy / Smuggling Signal

If the response chain shows TWO different Server: strings on subsequent requests, or a CDN front in front of an origin server with different framing, note this in the handoff under "Frontend stack" — it is the recognition signal for HTTP request smuggling routing in exploit.

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 · 40 lines · 26 tokens per session scan A 97e54a5e7ae6

Subscribe to this mod's changes

waf-detection is a skill published in the GitHub repository MingyiSecLab/Mingyi-Atlas (11 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 26 tokens to every session and 422 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 2026-09-03.