The Scan DeFi project launched on August 19, 2021. Its focus is on combating fraudulent crypto projects by providing analysis tools and educational resources. Scan DeFi provides a platform to detect scams in the world of decentralized finance (DeFi), which is a fast-growing segment of the cryptocurrency industry that offers various financial services such as lending, borrowing, and trading without intermediaries.
Scan DeFi uses artificial intelligence and blockchain analysis to identify and flag potential frauds, such as rug pulls, exit scams, and phishing attacks. A platform to detect scams in the world of cryptocurrencies, the user will be able to report scammers and thus warn other users of the danger.
Scan DeFi is a platform focused on identifying and eliminating scams within the cryptocurrency space. It offers users the ability to report fraudulent activities, enabling others to steer clear of potential scams. Key features:
Users can report scams, fostering a community-driven effort to warn others about fraudulent activities.
It aims to provide a comprehensive analysis of cryptocurrencies, aiding in the identification and elimination of scams.
Provides real-time charts, including trading volume and market cap data for Scan DeFi (SCAN), allowing users to stay updated on trends.
Real-time price updates for SCAN against different currencies, assisting in making informed decisions.
The platform's code is available on GitHub, showcasing transparency and potentially allowing community contributions
Introducing Scan DeFi, a collective intelligence platform where users can report scams, risky projects, and other suspicious activities as well as warn others from repeat threats seeking new victims.
Backed by the SCAN token, the platform aligns incentives towards identifying not just simple scams but more complex and institutionalized fraud in trading, lending, tokenized arts, gambling and more.
The roadmap focuses first on building core scam detection and community reporting tools, then expanding to cover more crypto sectors, integrating more web3 security features, and eventually developing ML automation and connections with external stakeholders.