analyzing-malicious-url-with-urlscan 精选
URLScan.io is a free service for scanning and analyzing suspicious URLs.
安装方式
cp -r skills/analyzing-malicious-url-with-urlscan ~/.claude/skills/analyzing-malicious-url-with-urlscan把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/
/plugin marketplace add mukul975/Anthropic-Cybersecurity-Skills⚠️ 该命令形态随客户端版本变化,仅在检测到 .claude-plugin/marketplace.json 时展示;不可用时请用「目录复制」。
https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/54a798831d2266a3ca61ce68a7acb80b81160d57/skills/analyzing-malicious-url-with-urlscan/SKILL.md下载后另存为 ~/.claude/skills/analyzing-malicious-url-with-urlscan/SKILL.md。链接锁定采集时的 commit,内容与本站展示一致。
整仓一次性获取:git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
依赖与权限
- 需要 API Key —— 使用前需配置相应的密钥环境变量
- 需要联网访问外部服务
- 依赖外部命令:
python - 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。
SKILL.md 正文
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
- Safe browsing: Renders URLs in isolated Chromium instance
- Screenshot capture: Visual snapshot of the rendered page
- DOM analysis: Full HTML content after JavaScript execution
- Network log: All HTTP requests made by the page (HAR format)
- Certificate analysis: SSL/TLS certificate details
- Technology detection: Identifies web frameworks and libraries
- IP/ASN mapping: Infrastructure intelligence
- 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
质量与来源
- 所属仓库
- mukul975/Anthropic-Cybersecurity-Skills
- 仓库星标
- 3.4 万
- 最近更新
- 1 个月前
- 采集时间
- 今天
- commit
- 54a798831d22
- 内容指纹
- sha256:82f4a952f988eb2
- 文件路径
- skills/analyzing-malicious-url-with-urlscan/SKILL.md