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使用 URLScan 分析惡意網址

URLScan.io 是一個免費服務,用於掃描和分析可疑網址。

使用 URLScan 分析惡意網址 是什麼?

這項技能詳細說明如何使用 URLScan.io 的安全隔離環境來調查釣魚網址、憑證竊取頁面及惡意重新導向,避免分析者的系統暴露於風險中。它涵蓋了 URLScan 的網頁介面與 API 操作,從提交網址、檢視截圖與 DOM 內容,到分析 HTTP 交易、JavaScript 行為及網路連線。技能列出釣魚網址的關鍵紅旗(如新註冊網域、免費託管服務、過長子網域),並提供從掃描結果中提取入侵指標(IOC)的標準流程,包含網域、IP、雜湊值等。最後,它建議將發現的 IOC 與 VirusTotal、PhishTank、Google Safe Browsing 等威脅情報來源交叉比對,並可搭配自動化腳本(process.py)批量處理。此技能適用於 SOC 分析師、威脅研究人員及安全工程師,支援 Windows、macOS 與 Linux 平台。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-malicious-url-with-urlscan

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說明文件

使用 URLScan 分析惡意網址 是做什麼的?

概述

URLScan.io 是一個免費服務,用於掃描和分析可疑網址。它能在隔離環境中捕捉網頁的螢幕截圖、DOM 內容、HTTP 交易、JavaScript 行為以及網路連線。這項技能涵蓋如何使用 URLScan 的網頁介面和 API 來調查釣魚網址、憑證竊取頁面以及惡意重新導向,且不讓分析者的系統暴露於風險中。

使用時機

  • 調查需要透過 urlscan 分析惡意網址的安全事件時
  • 為此領域建立偵測規則或威脅獵捕查詢時
  • SOC 分析師需要此類分析類型的結構化流程時
  • 驗證相關攻擊技術的安全監控涵蓋範圍時

先決條件

  • URLScan.io 帳戶(免費方案可用,API 金鑰用於自動化)
  • Python 3.8+ 並安裝 requests 函式庫
  • 了解 HTTP 通訊協定與網頁技術
  • 熟悉釣魚網址模式

關鍵概念

URLScan 功能

  1. 安全瀏覽:在隔離的 Chromium 實例中渲染網址
  2. 螢幕截圖捕捉:渲染頁面的視覺快照
  3. DOM 分析:JavaScript 執行後的完整 HTML 內容
  4. 網路日誌:頁面發出的所有 HTTP 請求(HAR 格式)
  5. 憑證分析:SSL/TLS 憑證詳細資訊
  6. 技術偵測:識別網頁框架與函式庫
  7. IP/ASN 對應:基礎設施情報
  8. 判定結果:社群與自動化分類

釣魚網址紅旗

  • 新註冊網域(少於 30 天)
  • 免費託管服務(Wix、GitHub Pages、Firebase)
  • 隱藏最終目的地的網址縮短服務
  • 過多的子網域層級(login.microsoft.com.evil.com)
  • 品牌名稱出現在子網域或路徑,而非主網域
  • 非標準通訊埠
  • 資料 URI 或 base64 編碼內容
  • 大量 JavaScript、極少 HTML 的頁面

工作流程

步驟 1:將網址提交至 URLScan

網頁:前往 https://urlscan.io 並提交可疑網址
API:POST https://urlscan.io/api/v1/scan/
     標頭:API-Key: your-api-key
     請求主體:{"url": "https://suspicious-url.com", "visibility": "private"}

步驟 2:分析結果

  • 檢視螢幕截圖以識別品牌冒充
  • 檢查重新導向與最終目標網址
  • 檢查 DOM 中是否有憑證輸入表單
  • 檢視網路請求以找出資料外洩端點
  • 檢查 SSL 憑證的有效性與簽發者

步驟 3:提取入侵指標

  • 接觸到的網域與 IP
  • 重新導向鏈中的網址
  • 頁面資源的 SHA-256 雜湊值
  • JavaScript 檔案雜湊值

步驟 4:與威脅情報交叉比對

使用 scripts/process.py 自動化網址掃描、提取 IOC,並與 VirusTotal、PhishTank 及 Google Safe Browsing 進行交叉比對。

工具與資源

驗證

  • 成功透過 API 掃描可疑網址
  • 提取螢幕截圖並識別品牌冒充
  • 記錄完整的重新導向鏈
  • 從掃描結果產生 IOC 清單
  • 與至少 2 個威脅情報來源交叉比對發現結果

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

abusing-dpapi-for-credential-access

Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket

abusing-shadow-credentials-for-privesc

Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target

achieving-cmmc-level-2-compliance

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acquiring-disk-image-with-dd-and-dcfldd

Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.

analyzing-active-directory-acl-abuse

Detect dangerous ACL misconfigurations in Active Directory using ldap3

analyzing-android-malware-with-apktool

Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

analyzing-api-gateway-access-logs

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect

analyzing-apt-group-with-mitre-navigator

Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups

analyzing-azure-activity-logs-for-threats

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query

analyzing-bootkit-and-rootkit-samples

Analyzes bootkit and advanced rootkit malware infecting the Master

analyzing-browser-forensics-with-hindsight

Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user

analyzing-campaign-attribution-evidence

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

analyzing-certificate-transparency-for-phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to

analyzing-cloud-storage-access-patterns

Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules.

analyzing-cobalt-strike-beacon-configuration

Extract and analyze Cobalt Strike beacon configuration from PE files

analyzing-cobaltstrike-malleable-c2-profiles

Parse and analyze Cobalt Strike Malleable C2 profiles with dissect.cobaltstrike (profiles and beacon-payload configs) and pyMalleableC2 (AST parsing) to extract HTTP/DNS transforms, URIs, headers, sleep/jitter, and injection behavior, then generate network detection signatures. Use when reverse-engineering a captured malleable profile or building detections against Cobalt Strike Beacon traffic.

analyzing-command-and-control-communication

Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom

analyzing-cyber-kill-chain

Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain

analyzing-disk-image-with-autopsy

Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.

analyzing-dns-logs-for-exfiltration

Analyzes DNS query logs to detect data exfiltration via DNS tunneling,

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