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A deterministic, AI‑free environment for validating URL‑security logic in browser extensions, automated scanners, and threat‑detection systems.
Designed for clarity, auditability, and enterprise‑grade repeatability.
Security engineers need safe, predictable, and realistic URLs to test detection logic — without exposing themselves to real threats.
This sandbox provides a curated dataset of benign, suspicious, and intentionally flagged URLs used to validate:
- Browser extension security workflows
- URL classification engines
- Redirect‑handling logic
- Threat‑flagging heuristics
- CI/CD security automation
This project demonstrates your ability to design controlled security environments, structured datasets, and testable threat‑simulation workflows — all highly relevant to cybersecurity roles.
┌────────────────────────────────────┐
│ Zero‑AI URL Security Sandbox │
│ (Static, Curated Test URL Dataset)│
└───────────────────┬────────────────┘
│
▼
┌────────────────────────────────────┐
│ Security Tool Under Test │
│ (Browser Extension / Scanner / CI) │
└───────────────────┬────────────────┘
│
▼
┌────────────────────────────────────┐
│ Detection Logic │
│ - Heuristics │
│ - Pattern Matching │
│ - Domain Reputation Checks │
└───────────────────┬────────────────┘
│
▼
┌────────────────────────────────────┐
│ Output Layer │
│ - Alerts │
│ - Logs │
│ - Reports │
└────────────────────────────────────┘
[ Developer / Security Engineer ]
│
▼
┌──────────────────────┐
│ Clone Repository │
└──────────┬───────────┘
│
▼
┌──────────────────────┐
│ Integrate Test URLs │
│ into Tool/Scanner │
└──────────┬───────────┘
│
▼
┌──────────────────────┐
│ Run Detection Logic │
│ (Local or CI/CD) │
└──────────┬───────────┘
│
▼
┌──────────────────────┐
│ Compare Results │
│(VT, urlscan.io, etc.)│
└──────────┬───────────┘
│
▼
┌──────────────────────┐
│ Improve Heuristics │
│ & Re‑Test │
└──────────────────────┘
/test-urls/
safe/
suspicious/
flagged/
patterns/
docs/
README.md
- safe/ — benign URLs for baseline behavior
- suspicious/ — typosquatting, homoglyphs, scam‑style patterns
- flagged/ — domains intentionally marked unsafe by major vendors
- patterns/ — structural examples (query‑string abuse, fake login paths, etc.)
- Validate URL‑scanning logic
- Test warning UI triggers
- Evaluate redirect‑following behavior
- Benchmark domain reputation checks
- Stress‑test pattern‑based detection
- Compare results with external scanners (VirusTotal, urlscan.io, Cloudflare Radar)
This repository references safe‑for‑testing URLs such as:
- Google Safe Browsing test domain
- EICAR test resources
- Sinkholed malware domains
- Public phishing‑pattern examples
These are safe to scan but should not be opened in a browser.
This repository does not contain malware, scripts, or harmful content.
However, many URLs are intentionally flagged by security engines.
Use only in controlled testing environments.
git clone https://github.com/JAYKAAGE/Zero-AI-URL-Security-Sandbox.gitIntegrate the test URLs into your extension, scanner, or CI pipeline.
Validate detection logic across each category.
Iterate and refine your security heuristics.
This project demonstrates:
- Ability to design controlled cybersecurity testing environments
- Understanding of URL‑based threat vectors
- Familiarity with industry‑standard security testing domains
- Experience with browser extension security workflows
- Strong documentation and professional presentation skills
- Capability to build repeatable, auditable test frameworks
Perfect for roles in:
- Application Security
- Browser Security
- Threat Detection Engineering
- Security Automation
- Cybersecurity Research
Contributions are welcome — especially new safe test domains, suspicious patterns, or documentation improvements.
Distributed under the MIT License.
Jayden Brewton - CEO of BrewTecc