Atlas / Skills / mukul975 / Analyzing Malicious Url With Urlscan

Analyzing Malicious Url With UrlscanSAFE

skills/mukul975/analyzing-malicious-url-with-urlscan

817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
1.0
Hosts
—
License
Apache-2.0
Stars
33,870
01

Overview

817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·

Read from source at commit 6c59587be632OBSERVED · 2026-10-07
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
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
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codePASS
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
declared (5 observation(s))
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-07 · audit v0.4.1 · source sha 6c59587be632full audit observations/trust-audit/skill/mukul975__analyzing-malicious-url-with-urlscan.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-076c59587be632SAFEB89first audit
05

Questions

What does the Analyzing Malicious Url With Urlscan skill do?

817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·

Is Analyzing Malicious Url With Urlscan safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Analyzing Malicious Url With Urlscan access on my machine?

The audit observed that it reaches the network. Each of those is consistent with what it says it does. Secrets in the source: none found.

How current is this page?

The grade is for one exact copy of the source (6c59587be632), read on 2026-10-07. The repository is watched, and a new audit runs when it changes — this is the first audit.

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