🔐 SheerID Verification Tool

A comprehensive collection of tools for automating SheerID verification workflows for various services (Spotify, YouTube, Google One, etc.).

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🛠️ Available Tools

Tool	Type	Target	Description
spotify-verify-tool	🎵 Student	Spotify Premium	University student verification
youtube-verify-tool	🎬 Student	YouTube Premium	University student verification
one-verify-tool	🤖 Student	Gemini Advanced	Google One AI Premium verification
boltnew-verify-tool	👨‍🏫 Teacher	Bolt.new	Teacher verification (University)
canva-teacher-tool	🇬🇧 Teacher	Canva Education	UK Teacher verification (K-12)
k12-verify-tool	🏫 K12	ChatGPT Plus	K12 Teacher verification (High School)
veterans-verify-tool	🎖️ Military	General	Military status verification
veterans-extension	🧩 Chrome	Browser	Chrome extension for military verification

🔗 External Tools

Tool	Type	Description
RoxyBrowser	🦊 Browser	Anti-detect browser — Safely manage multiple verified accounts without getting banned
Check IP	🌐 Web	Check IP — Check your IP address and proxy status
SheerID Verification Bot	🤖 Bot	Automated Telegram verification bot
Gmail Farmer Bot	🤖 Bot	Create Gmail accounts automatically
GitHub Bot	🤖 Bot	Auto GitHub Stars & engagement service
Student Card Generator	🎓 Tool	Create student cards for manual verification
Payslip Generator	💰 Tool	Generate payslips for teacher verification

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🧠 Core Architecture & Logic

All Python tools in this repository share a common, optimized architecture designed for high success rates.

1. The Verification Flow

The tools follow a standardized "Waterfall" process:

1. Data Generation: Creates a realistic identity (Name, DOB, Email) matching the target demographic.
2. Submission (collectStudentPersonalInfo): Submits data to SheerID API.
3. SSO Skip (DELETE /step/sso): Crucial step. Bypasses the requirement to log in to a school portal.
4. Document Upload (docUpload): Uploads a generated proof document (Student ID, Transcript, or Teacher Badge).
5. Completion (completeDocUpload): Signals to SheerID that upload is finished.

2. Intelligent Strategies

🎓 University Strategy (Spotify, YouTube, Gemini)

• Weighted Selection: Uses a curated list of 45+ Universities (US, VN, JP, KR, etc.).
• Success Tracking: Universities with higher success rates are selected more often.
• Document Gen: Generates realistic-looking Student ID cards with dynamic names and dates.

👨‍🏫 Teacher Strategy (Bolt.new)

• Age Targeting: Generates older identities (25-55 years old) to match teacher demographics.
• Document Gen: Creates "Employment Certificates" instead of Student IDs.
• Endpoint: Targets collectTeacherPersonalInfo instead of student endpoints.

🏫 K12 Strategy (ChatGPT Plus)

• School Type Targeting: Specifically targets schools with type: "K12" (not HIGH_SCHOOL).
• Auto-Pass Logic: K12 verification often auto-approves without document upload if the school and teacher info match.
• Fallback: If upload is required, it generates a Teacher Badge.

🎖️ Veterans Strategy (ChatGPT Plus)

• Strict Eligibility: Targets Active Duty or Veterans separated within the last 12 months.
• Authoritative Check: SheerID verifies against DoD/DEERS database.
• Logic: Defaults to recent discharge dates to maximize auto-approval chances.

🛡️ Anti-Detection Module

All tools now include anti_detect.py which provides:

• Random User-Agents: 10+ real browser UA strings (Chrome, Firefox, Edge, Safari)
• Browser-like Headers: Proper sec-ch-ua, Accept-Language, etc.
• TLS Fingerprint Spoofing: Uses curl_cffi to impersonate Chrome's JA3/JA4 fingerprint
• Random Delays: Gamma distribution timing to mimic human behavior
• Smart Session: Auto-selects best available HTTP library (curl_cffi > cloudscraper > httpx > requests)
• NewRelic Headers: Required tracking headers for SheerID API calls
• Session Warming: Pre-verification requests to establish legitimate browser session
• Email Generation: Creates realistic student emails matching university domains
• Proxy Geo-Matching: Matches proxy location to university country for consistency
• Multi-Browser Impersonation: Rotates between Chrome, Edge, and Safari fingerprints

📄 Document Generation Module

New doc_generator.py provides anti-detection for generated documents:

• Noise Injection: Random pixel noise to avoid template detection
• Color Variation: 6 different color schemes for uniqueness
• Dynamic Positioning: ±3px variance on element positions
• Multiple Types: Student ID, Transcript, Teacher Badge
• Realistic Details: Random barcodes, QR codes, course grades

Warning

API-Based Tools Have Inherent Limitations

SheerID uses advanced detection including:

• TLS Fingerprinting: Python requests/httpx have detectable signatures
• Signal Intelligence: IP address, device attributes, email age analysis
• AI Document Review: Detects forged/template documents

For best results: Use residential proxies + install curl_cffi for TLS spoofing. Browser extensions generally have higher success rates than API tools.

Important

Gemini/Google One is US-ONLY (since Jan 2026)

The one-verify-tool only works with US IPs. International users will see verification failures.

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📋 Quick Start

Prerequisites

• Python 3.8+
• pip

Installation

1. Clone the repository:

   git clone https://github.com/ThanhNguyxn/SheerID-Verification-Tool.git
   cd SheerID-Verification-Tool

2. Install dependencies:

   pip install httpx Pillow

3. 🚨 REQUIRED: TLS Fingerprint Spoofing:

   pip install curl_cffi

   ⚠️ Without curl_cffi, success rate drops from ~60-80% to ~5-20%! SheerID detects Python's TLS fingerprint and will reject most requests.

4. [Optional] Cloudflare Bypass:

   pip install cloudscraper

5. [Optional] Cloudflare Bypass:

   pip install cloudscraper

6. Run a tool (e.g., Spotify):

   cd spotify-verify-tool
   python main.py "YOUR_SHEERID_URL"

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🔧 Troubleshooting: fraudRulesReject Error

This is the #1 issue users face. SheerID's fraud detection blocked your request.

Why It Happens

Cause	Description
TLS Fingerprint	Python's HTTP libraries have detectable signatures
Datacenter IP	VPN/datacenter IPs are often blacklisted
Request Frequency	Too many requests from same IP
Data Patterns	Generated data looks automated

Solutions (in order of importance)

Priority	Solution	Command/Action
🔴 CRITICAL	Install curl_cffi	pip install curl_cffi
🟠 HIGH	Use residential proxy	--proxy http://user:pass@residential-ip:port
🟡 MEDIUM	Wait before retry	Wait 24-48 hours between attempts
🟢 LOW	Try different university	Tool auto-rotates, or specify manually
🟢 LOW	Rotate fingerprint	Each attempt generates new fingerprint

Quick Fix Checklist

# 1. Install curl_cffi (REQUIRED!)
pip install curl_cffi

# 2. Verify it's working
python -c "from curl_cffi import requests; print('✅ curl_cffi OK')"

# 3. Run with residential proxy
python main.py "URL" --proxy http://user:pass@residential.proxy.com:8080

Tip

If you don't have a residential proxy, try RoxyBrowser which provides anti-detect browser with residential IPs.

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🦊 Official Partner: RoxyBrowser

🛡 Anti-Detect Protection — Unique fingerprint for each account, looks like different real devices.

📉 Prevent Linkage — Stops SheerID and platforms from linking your accounts.

🚀 Ideal for Bulk Users — Safely manage hundreds of verified accounts.

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⚠️ Disclaimer

This project is for educational purposes only. The tools demonstrate how verification systems work and how they can be tested.

• Do not use this for fraudulent purposes.
• The authors are not responsible for any misuse.
• Respect the Terms of Service of all platforms.

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🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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❤️ Support

If you find this project helpful, consider supporting me:

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🌐 Translations

🇺🇸 English	🇻🇳 Tiếng Việt	🇨🇳 中文	🇯🇵 日本語	🇰🇷 한국어
🇪🇸 Español	🇫🇷 Français	🇩🇪 Deutsch	🇧🇷 Português	🇷🇺 Русский
🇸🇦 العربية	🇮🇳 हिन्दी	🇹🇭 ไทย	🇹🇷 Türkçe	🇵🇱 Polski
🇮🇹 Italiano	🇮🇩 Bahasa Indonesia