Independent technical audit

dalfox.hahwul.com

Overall AI readiness score

A combined result across all audit signals.

Excellent

AI readiness audit: 9/24/2026Public technical data

Overall AI readiness assessment

How ready dalfox.hahwul.com is for AI systems

87/100

Dalfox (dalfox.hahwul.com) received an AI-readiness score of 87/100 in an automated technical audit. llms.txt was accessible, llms-full.txt was accessible, and ai.txt was not found. The robots.txt analysis found 0 explicitly allowed and 0 blocked AI crawlers, with 1 declared sitemap. Homepage markup completeness was 70%; Schema.org types included SoftwareApplication and 5 OpenGraph tags were detected. Results reflect the public site response observed on 2026-09-24T02:33:24.864Z.

Audit context

llms.txt is accessible and contains 1,363 tokens. An expanded llms-full.txt is also available with 99,355 tokens, giving agents more direct context. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.

robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 1. The homepage exposes Schema.org types SoftwareApplication; 5 OpenGraph tags were found and markup completeness is 70%.

The mobile Lighthouse profile adds Performance 83/100, Accessibility 92/100, Best Practices 100/100, SEO 100/100, and experimental Agentic Browsing 67/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.

Confirmed strengths

Accessible llms.txt
Expanded llms-full.txt
1 sitemap declaration
Schema.org: SoftwareApplication

Priority improvements

1Reduce mobile rendering delay and main-thread work.

llms.txt tokens1,363

llms-full.txt tokens99,355

ai.txt

sitemap.xml

Google Lighthouse technical profile

A mobile Lighthouse measurement. Google’s experimental Agentic Browsing category is explained separately and does not replace the broader llmsmap AI-readiness score.

Mobile · Lighthouse

Performance

Accessibility

100

Best Practices

100

Technical SEO

Agentic Browsing

What these results mean

Mobile performance is 83/100, with the largest visible content block appearing in 3.3 s and the browser main thread blocked for 0 ms. Layout shift was 0. The main thread is where the browser runs JavaScript, calculates layout, and paints the page; long work there delays both user input and browser-agent actions.

Accessibility scored 92/100, Best Practices 100/100, and technical SEO 100/100. The experimental Agentic Browsing category scored 67/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.

Free the main thread and accelerate the first view

Split long JavaScript tasks, defer non-critical scripts and styles, and shorten blocking request chains. This helps the primary content appear sooner and makes controls usable earlier.

Optimise images and their loading order

Serve correctly sized modern formats, prioritise the primary visual, and lazy-load content below the first viewport.

Reduce network delay

Improve server response time, remove unnecessary redirects and repeat downloads, and use compression, caching, and selective preconnect hints.

Make controls unambiguous

Give buttons and links accessible names, associate labels with fields, and use ordered headings and semantic regions. The same structure helps screen readers and software agents understand actions.

FCP3.2 s

First content

LCP3.3 s

Main content

CLS0

Layout stability

TBT0 ms

Blocking time

SI4.8 s

Visual speed

Metric glossary

FCP · First content: When the first text or image appeared on screen.
LCP · Main content: When the largest visible element in the first viewport rendered.
CLS · Layout stability: How much content shifted unexpectedly while loading; lower is better.
TBT · Blocking time: How long the browser main thread could not respond quickly to input.
SI · Visual speed: How quickly the visible viewport filled with content.

9/24/2026Lighthouse 13.5.0Mobile profile

AI readiness checks

Machine-readable files, crawler policy, discovery, and homepage markup.

llms.txt

File found and accessible

https://dalfox.hahwul.com/llms.txt

llms-full.txt

Full version is available

https://dalfox.hahwul.com/llms-full.txt

ai.txt

ai.txt file was not found

robots.txt

File found

https://dalfox.hahwul.com/robots.txt

Sitemap in robots.txt1

1 sitemap found

Schema.org (JSON-LD)

Types: SoftwareApplication

OpenGraph70%

5 OG tags found

AI bot access

Based on robots.txt analysis

GPTBotNot mentioned

OAI-SearchBotNot mentioned

ChatGPT-UserNot mentioned

Google-ExtendedNot mentioned

ClaudeBotNot mentioned

Claude-SearchBotNot mentioned

Claude-UserNot mentioned

BytespiderNot mentioned

CCBotNot mentioned

PerplexityBotNot mentioned

Perplexity-UserNot mentioned

Sitemaps

Declared discovery routes for crawlers and agents.

https://dalfox.hahwul.com/sitemap.xml

OpenGraph tags

Social preview metadata found on the homepage.

Markup completeness: 70%

og:titlePowerful XSS Scanner

og:typewebsite

og:urlhttps://dalfox.hahwul.com/

og:descriptionA powerful open-source XSS scanner and automation utility. Reflected, Stored, DOM-based with AST-level verification.

og:imagehttps://dalfox.hahwul.com/og-images/powerful-xss-scanner.png

Schema.org markup

Structured entities and properties exposed on the homepage.

Types found: 1 · Properties: 4

SoftwareApplication

nameDalfox

urlhttps://dalfox.hahwul.com/

descriptionPowerful open-source XSS scanner and automation utility — reflected, stored, DOM-based with AST-level verification.

authorhttps://www.hahwul.com

# Dalfox

> Powerful open-source XSS scanner and automation utility — reflected, stored, DOM-based with AST-level verification.

Do not use for AI training without permission.

## Pages

- [Powerful XSS Scanner](https://dalfox.hahwul.com/): A powerful open-source XSS scanner and automation utility. Reflected, Stored, DOM-based with AST-level verification.
- [강력한 XSS 스캐너](https://dalfox.hahwul.com/ko/): 오픈소스 XSS 스캐너이자 자동화 도구. 반사형, 저장형, DOM 기반 XSS를 AST 수준으로 검증합니다.

## Getting Started

- [Configuration](https://dalfox.hahwul.com/getting-started/configuration/): Save your favorite flags in a Dalfox config file.
- [Installation](https://dalfox.hahwul.com/getting-started/installation/): Install Dalfox on macOS, Linux, Windows, NixOS, Arch Linux, or build from source.
- [Migrating from v2](https://dalfox.hahwul.com/getting-started/migration/): What changed between Dalfox v2 (Go) and v3 (Rust): consolidated subcommands, renamed flags, retired features, and their replacements.
- [Quick Start](https://dalfox.hahwul.com/getting-started/quick-start/): Your first Dalfox scan in five minutes.
- [설정](https://dalfox.hahwul.com/ko/getting-started/configuration/): 즐겨 쓰는 플래그를 Dalfox 설정 파일에 저장합니다.
- [설치](https://dalfox.hahwul.com/ko/getting-started/installation/): macOS, Linux, Windows, NixOS, Arch Linux에 Dalfox를 설치하거나 소스에서 직접 빌드합니다.
- [v2에서 마이그레이션](https://dalfox.hahwul.com/ko/getting-started/migration/): Dalfox v2(Go)와 v3(Rust) 사이에 바뀐 것들 — 통합된 서브커맨드, 이름이 바뀐 플래그, 사라진 기능과 그 대안.
- [빠른 시작](https://dalfox.hahwul.com/ko/getting-started/quick-start/): 5분 만에 첫 Dalfox 스캔을 실행합니다.

## Guide

- [Detection Model](https://dalfox.hahwul.com/guide/detection-model/): The three axes of a Dalfox finding (confidence, method, impact) and what each evidence tier actually proves.
- [Output & Reports](https://dalfox.hahwul.com/guide/output/): Plain, JSON, JSONL, Markdown, SARIF, TOML, and how to integrate findings with your pipeline.
- [Parameters & Discovery](https://dalfox.hahwul.com/guide/parameters/): How Dalfox finds the inputs that matter, and how to steer the discovery phase.
- [Payloads & Encoding](https://dalfox.hahwul.com/guide/payloads/): Built-in payload families, encoders, custom payloads, and remote wordlists.
- [Scanning Modes](https://dalfox.hahwul.com/guide/scanning-modes/): Single URL, file batch, pipeline, stored XSS, server, and MCP. Pick the mode that fits your workflow.
- [Stored XSS](https://dalfox.hahwul.com/guide/stored-xss/): Inject on one URL, verify the payload fires on another.
- [WAF Bypass](https://dalfox.hahwul.com/guide/waf-bypass/): Detect WAFs automatically and apply per-WAF evasion strategies.
- [탐지 모델](https://dalfox.hahwul.com/ko/guide/detection-model/): Dalfox 결과의 세 축(신뢰도, 방식, 영향도)과 각 증거 등급이 실제로 무엇을 증명하는지.
- [출력과 리포트](https://dalfox.hahwul.com/ko/guide/output/): Plain, JSON, JSONL, Markdown, SARIF, TOML 형식과 탐지 결과를 파이프라인에 통합하는 방법을 다룹니다.
- [파라미터와 탐색](https://dalfox.hahwul.com/ko/guide/parameters/): Dalfox가 중요한 입력값을 찾아내는 방식과 탐색 단계를 제어하는 방법을 설명합니다.
- [페이로드와 인코딩](https://dalfox.hahwul.com/ko/guide/payloads/): 내장 페이로드 계열, 인코더, 커스텀 페이로드, 그리고 원격 워드리스트를 다룹니다.
- [스캔 모드](https://dalfox.hahwul.com/ko/guide/scanning-modes/): 단일 URL, 파일 배치, 파이프라인, 저장형 XSS, 서버, MCP까지. 워크플로에 맞는 모드를 선택하세요.
- [저장형 XSS](https://dalfox.hahwul.com/ko/guide/stored-xss/): 한 URL에서 주입하고, 다른 URL에서 페이로드가 실행되는지 검증합니다.
- [WAF 우회](https://dalfox.hahwul.com/ko/guide/waf-bypass/): WAF를 자동으로 탐지하고 WAF별 회피 전략을 적용합니다.

## Integrations

- [Caido Workflows](https://dalfox.hahwul.com/integrations/caido/): Run Dalfox automatically from Caido Active Workflows and Findings to catch XSS in real time.
- [MCP Server](https://dalfox.hahwul.com/integrations/mcp/): Expose Dalfox to Claude and other MCP clients as a set of scanner tools.
- [REST API Server](https://dalfox.hahwul.com/integrations/server/): Run Dalfox as an HTTP service with async job management, CORS, JSONP, and API-key auth.
- [Agent Skill](https://dalfox.hahwul.com/integrations/skills/): Drop-in `SKILL.md` for Claude Code, Cursor, OpenCode, Codex, and other skill-aware agents.
- [Caido 워크플로](https://dalfox.hahwul.com/ko/integrations/caido/): Caido Active Workflows와 Findings에서 Dalfox를 자동으로 실행하여 XSS를 실시간으로 잡아냅니다.
- [MCP 서버](https://dalfox.hahwul.com/ko/integrations/mcp/): Dalfox를 Claude 및 기타 MCP 클라이언트에 스캐너 도구(tool) 모음으로 노출합니다.
- [REST API 서버](https://dalfox.hahwul.com/ko/integrations/server/): 비동기 작업 관리, CORS, JSONP, API 키 인증을 갖춘 HTTP 서비스로 Dalfox를 실행합니다.
- [에이전트 스킬](https://dalfox.hahwul.com/ko/integrations/skills/): Claude Code, Cursor, OpenCode, Codex 및 기타 스킬 인식 에이전트를 위한 드롭인 `SKILL.md`.

## Reference

- [CLI 레퍼런스](https://dalfox.hahwul.com/ko/reference/cli/): Dalfox가 지원하는 모든 서브커맨드와 플래그.
- [설정 파일](https://dalfox.hahwul.com/ko/reference/config/): Dalfox의 TOML/JSON 설정 파일이 지원하는 모든 키.
- [환경 변수](https://dalfox.hahwul.com/ko/reference/environment/): Dalfox가 런타임에 읽는 환경 변수.
- [XSSMaze 점수](https://dalfox.hahwul.com/ko/reference/xssmaze/): Dalfox가 XSSMaze 랩을 얼마나 탐지하는지, main 브랜치를 기준으로 측정한 값.
- [CLI Reference](https://dalfox.hahwul.com/reference/cli/): Every subcommand and flag Dalfox accepts.
- [Config File](https://dalfox.hahwul.com/reference/config/): All keys supported in Dalfox's TOML/JSON config file.
- [Environment](https://dalfox.hahwul.com/reference/environment/): Environment variables Dalfox reads at runtime.
- [XSSMaze Score](https://dalfox.hahwul.com/reference/xssmaze/): How much of the XSSMaze lab Dalfox detects, measured against the main branch.

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Added 9/24/2026