Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add pinkpixel-dev/skills-collection-1 --skill analyzing-malicious-url-with-urlscangit clone --depth 1 https://github.com/pinkpixel-dev/skills-collection-1Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pinkpixel-dev/skills-collection-1/analyzing-malicious-url-with-urlscan)<a href="https://agentmods.dev/skills/pinkpixel-dev/skills-collection-1/analyzing-malicious-url-with-urlscan"><img src="https://agentmods.dev/badge/skills/pinkpixel-dev/skills-collection-1/analyzing-malicious-url-with-urlscan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pinkpixel-dev/skills-collection-1/analyzing-malicious-url-with-urlscan"><img src="https://agentmods.dev/badge/skills/pinkpixel-dev/skills-collection-1/analyzing-malicious-url-with-urlscan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.00884 |
| Opus 5 | $0.00024 | $0.00442 |
| Sonnet 5 | $0.00010 | $0.00177 |
| Haiku 4.5 | $0.00005 | $0.00088 |
Grade A, and why
analyzing-malicious-url-with-urlscan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
95% identical to analyzing-malicious-url-with-urlscan — 26 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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"}
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 93 lines · 48 tokens per session scan A 6a0d047f1987
analyzing-malicious-url-with-urlscan is a skill published in the GitHub repository pinkpixel-dev/skills-collection-1 (7 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 48 tokens to every session and 884 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to analyzing-malicious-url-with-urlscan, differing in 26 lines, and is treated as a copy.
Other skills, from other repositories
analyzing-malicious-url-with-urlscan
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.
analyzing-malicious-url-with-urlscan
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.
analyzing-malicious-url-with-urlscan
A guide for investigating suspicious web addresses with URLScan.io, a service that opens a URL in an isolated browser and records its screenshot, page structure, network requests, scripts, and redirects.
analyzing-malicious-url-with-urlscan
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.
analyzing-malicious-url-with-urlscan
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.
analyzing-malicious-url-with-urlscan
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.