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analyzing-malicious-url-with-urlscan

URLScan.io is a free service for scanning and analyzing suspicious URLs.

analyzing-malicious-url-with-urlscan 是什么?

analyzing-malicious-url-with-urlscan is a Claude Code agent skill that uRLScan.io is a free service for scanning and analyzing suspicious URLs.

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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

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

Individual skills in this repo

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

abusing-dpapi-for-credential-access

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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

>-

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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