Analyzing Malicious Url With Urlscan

TL;DR

• 目的：URLScan.io is a free service for scanning and analyzing suspicious URLs. It captures screenshots, DOM content, HTTP transactions, JavaScript…
• 适用：恶意软件分析/逆向
• 输入：目标 URL + 端点/参数清单
• 输出：IOC 列表 + 行为分析报告
• 红线：仅限授权范围内；扫描限速 -c 10 -rl 10；所有动作记 oplog
• 关联：上游：003-src-session-start → 下游：137-analyzing-malicious-pdf-with-peepdf, 142-analyzing-pdf-malware-with-pdfid, 139-analyzing-malware-behavior-with-cuckoo-sandbox

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 & Systems

• 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 Criteria

• 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

Tools & Systems

• Cuckoo Sandbox — Automated dynamic analysis
• CAPE Sandbox — Config extraction + evasion detection
• Any.run — Cloud-based interactive sandbox
• Ghidra — NSA's reverse engineering framework
• dnSpy — .NET assembly decompiler
• PE Studio — Static PE analysis
• Volatility — Memory forensics
• YARA — Pattern-based malware identification

Run all tools in isolated sandbox environment. Never connect to production networks.

Advanced Techniques

YARA Rule Authoring

Build incremental YARA rules starting with unique strings, then behavioral patterns, then API call sequences.

Memory Forensics with Volatility

Use volatility -f mem.dmp --profile=Win10x64 malfind to identify injected code regions.