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analyzing-malicious-url-with-urlscan — Claude Code skill: scan

This skill walks through scanning suspicious and phishing URLs with URLScan.io and pulling the screenshot, DOM, redirect chain and IOCs out of the report.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-malicious-url-with-urlscan -a claude-code
Open on GitHub

What analyzing-malicious-url-with-urlscan does

URLScan.io renders a page in an isolated Chromium instance and keeps what it does: a screenshot, the HTML after JavaScript runs, network requests in HAR format, SSL certificate details. The skill covers both the web interface and the API, so you can investigate phishing pages and redirect chains without opening them on your own machine.

The workflow runs in steps: submit the URL, check the screenshot for brand impersonation, follow redirects to the final destination, look for credential input forms in the DOM, then collect domains, IPs and resource hashes. The bundled scripts/process.py automates the scanning and cross-references findings with VirusTotal, PhishTank and Google Safe Browsing.

Automation needs a URLScan.io account with an API key, and the script wants Python 3.8+ with the requests library. Without a key you are left submitting URLs by hand through the site. If you are working an incident and would rather not point your own IP at a lure page, handing the link to a scanner beats clicking it.

What it helps with

  • open a suspicious link in an isolated environment and get a screenshot
  • trace a redirect chain to its final destination
  • find credential-harvesting forms in the rendered DOM
  • collect contacted domains, IPs and resource hashes
  • cross-check findings against VirusTotal, PhishTank and Google Safe Browsing

Example prompts for the agent

  • scan this link with URLScan and show me the screenshot and redirect chain
  • pull the IOCs out of the URLScan report for this URL
  • check the page for brand impersonation and password forms

How to install analyzing-malicious-url-with-urlscan

1Skills CLI (Vercel)

npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-malicious-url-with-urlscan -a claude-code

2Manually: put the files in place

~/.claude/skills/analyzing-malicious-url-with-urlscan/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/analyzing-malicious-url-with-urlscan/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about analyzing-malicious-url-with-urlscan

How do I install analyzing-malicious-url-with-urlscan in Claude?

Run npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-malicious-url-with-urlscan -a claude-code. The skill lands in ~/.claude/skills/analyzing-malicious-url-with-urlscan/SKILL.md.

What does analyzing-malicious-url-with-urlscan do?

It describes investigating suspicious URLs through URLScan.io: submitting them for scanning, reviewing the screenshot, DOM, redirects and certificate, then extracting IOCs and checking them against outside sources.

What do I need before using it?

A URLScan.io account with an API key for automation, plus Python 3.8+ and the requests library for scripts/process.py. Familiarity with HTTP and common phishing URL patterns helps too.

Source text

SKILL.md · Apache-2.0
---
name: analyzing-malicious-url-with-urlscan
description: URLScan.io is a free service for scanning and analyzing suspicious URLs.
  It captures screenshots, DOM content, HTTP transactions, JavaScript behavior, and
  network connections of web pages in an isolat
domain: cybersecurity
subdomain: phishing-defense
tags:
- phishing
- email-security
- social-engineering
- dmarc
- awareness
- url-analysis
- threat-intelligence
version: '1.0'
author: mahipal
license: Apache-2.0
atlas_techniques:
- AML.T0052
nist_csf:
- PR.AT-01
- DE.CM-09
- RS.CO-02
- DE.AE-02
mitre_attack:
- T1566.002
- T1204.001
- T1598.003
---
# Analyzing Malicious URL with URLScan

## Overview
URLScan.io is a free service for scanning and analyzing suspicious URLs. It captures screenshots, DOM content, HTTP transactions, JavaScript behavior, and network connections of web pages in an isolated environment. This skill covers using URLScan's web interface and API to investigate phishing URLs, credential harvesting pages, and malicious redirects without exposing the analyst's system to risk.


## When to Use

- When investigating security incidents that require analyzing malicious url with urlscan
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques

## Prerequisites
- URLScan.io account (free tier available, API key for automation)
- Python 3.8+ with requests library
- Understanding of HTTP protocols and web technologies
- Familiarity with phishing URL patterns

## Key Concepts

### URLScan Capabilities
1. **Safe browsing**: Renders URLs in isolated Chromium instance
2. **Screenshot capture**: Visual snapshot of the rendered page
3. **DOM analysis**: Full HTML content after JavaScript execution
4. **Network log**: All HTTP requests made by the page (HAR format)
5. **Certificate analysis**: SSL/TLS certificate details
6. **Technology detection**: Identifies web frameworks and libraries
7. **IP/ASN mapping**: Infrastructure intelligence
8. **Verdict**: Community and automated classification

### Phishing URL Red Flags
- Newly registered domains (< 30 days)
- Free hosting services (Wix, GitHub Pages, Firebase)
- URL shorteners hiding final destination
- Excessive subdomain depth (login.microsoft.com.evil.com)
- Brand name in subdomain or path, not domain
- Non-standard ports
- Data URIs or base64-encoded content
- JavaScript-heavy pages with minimal HTML

## Workflow

### Step 1: Submit URL to URLScan
```
Web: Navigate to https://urlscan.io and submit the suspicious URL
API: POST https://urlscan.io/api/v1/scan/
     Header: API-Key: your-api-key
     Body: {"url": "https://suspicious-url.com", "visibility": "private"}
```

### Step 2: Analyze Results
- Review screenshot for brand impersonation
- Check redirects and final destination URL
- Examine DOM for credential input forms
- Review network requests for data exfiltration endpoints
- Check SSL certificate validity and issuer

### Step 3: Extract IOCs
- Domains and IPs contacted
- URLs in redirect chain
- SHA-256 hashes of page resources
- JavaScript file hashes

### Step 4: Cross-Reference with Threat Intelligence
Use the `scripts/process.py` to automate URL scanning, extract IOCs, and cross-reference with VirusTotal, PhishTank, and Google Safe Browsing.

## Tools & Resources
- **URLScan.io**: https://urlscan.io/
- **URLScan API**: https://urlscan.io/docs/api/
- **VirusTotal URL Scanner**: https://www.virustotal.com/
- **PhishTank**: https://phishtank.org/
- **Google Safe Browsing**: https://transparencyreport.google.com/safe-browsing/search
- **Any.Run**: https://any.run/ (interactive sandbox)
- **Hybrid Analysis**: https://www.hybrid-analysis.com/

## Validation
- Successfully scan a suspicious URL via API
- Extract screenshot and identify brand impersonation
- Document complete redirect chain
- Generate IOC list from scan results
- Cross-reference findings with at least 2 threat intelligence sources

© mahipal · Apache-2.0 · mukul975/Anthropic-Cybersecurity-Skills

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