Last updated: 2026-03-14

Crypto Scam Check: Community Testing Access

By Bheshaj T. — Building Crypto Scam Dataset | Blockchain Forensic | Malware Researcher | Threat Intelligence Analyst | Crypto Investigation | GREM | CREA | CEH | CCFI | ATII DARKWEBATHON Winner

Gain early access to a research-first tool that quickly checks crypto addresses against a curated scam dataset, helping you accelerate investigations, improve accuracy, and validate findings with less context switching. Join a community-driven testing phase to shape the next version with your real-world feedback and use cases.

Published: 2026-03-14

Primary Outcome

Users can rapidly confirm whether a crypto address is linked to scams using a curated dataset, reducing investigation time and boosting confidence in findings.

Who This Is For

What You'll Learn

Prerequisites

About the Creator

Bheshaj T. — Building Crypto Scam Dataset | Blockchain Forensic | Malware Researcher | Threat Intelligence Analyst | Crypto Investigation | GREM | CREA | CEH | CCFI | ATII DARKWEBATHON Winner

LinkedIn Profile

FAQ

What is "Crypto Scam Check: Community Testing Access"?

Gain early access to a research-first tool that quickly checks crypto addresses against a curated scam dataset, helping you accelerate investigations, improve accuracy, and validate findings with less context switching. Join a community-driven testing phase to shape the next version with your real-world feedback and use cases.

Who created this playbook?

Created by Bheshaj T., Building Crypto Scam Dataset | Blockchain Forensic | Malware Researcher | Threat Intelligence Analyst | Crypto Investigation | GREM | CREA | CEH | CCFI | ATII DARKWEBATHON Winner.

Who is this playbook for?

Senior crypto investigators evaluating suspicious wallets, Blockchain analysts conducting OSINT-led scam research, Cybersecurity professionals validating threat intel against emerging scams

What are the prerequisites?

Interest in education & coaching. No prior experience required. 1–2 hours per week.

What's included?

Curated scam dataset for quick verification. Cross-tool efficiency with consolidated checks. Community-driven feedback to improve accuracy. Real-world use cases shape future features

How much does it cost?

$0.70.

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