scam-sniffer-primary-sources-2026-04-25

Scam Sniffer primary-source snapshot

Fetched: 2026-04-25 UTC

1) Official homepage

Source: https://www.scamsniffer.io/

Selected excerpts from the official site:

Enhance anti-scam capability of individual users to accelerate the mass adoption of web3.

With our Malicious Website Detection and Blacklist API, you could provide more safe web3 browsing and signing experience for your users!

Additional signals from the homepage:

• Homepage positions Scam Sniffer as both an end-user security product and a B2B security-data/API vendor
• Product surfaces include API solutions, a browser extension, public research, and pricing tiers for startup, standard, and enterprise usage
• Official site claims large-scale scanning and detection metrics, including tens of millions of scanned URLs, hundreds of thousands of scams found, and hundreds of thousands of blocked domains
• Marketing copy emphasizes phishing, wallet drainers, and safer browsing/signing rather than protocol mechanics or token economics

2) Security-check docs

Source: https://docs.scamsniffer.io/docs/security-check

Selected excerpts from the docs:

Security check contains a series of security checks that are performed when a transaction is initiated and before the transaction is confirmed by the wallet.

Based on @TenderlyApp’s transaction simulation, we can try to simulate the execution to see if there is an authorization and token transfer to remind users of the risk

Additional signals from the docs:

• Docs enumerate layered checks including domain checks, contract open-source checks, transaction simulation, suspicious-address checks, malicious-code checks, and sign-request checks
• The page explicitly references third-party data/services such as Etherscan, Tenderly, SlowMist, and GoPlus for parts of the risk-evaluation flow
• This makes Scam Sniffer notable as an operational anti-scam pipeline rather than just a browser warning list

3) API/reference portal

Source: https://docs.scamsniffer.io/reference

Selected excerpts/signals from the reference portal:

Guides

API Reference

Additional signals from the reference portal:

• The public docs expose a dedicated API/reference surface alongside guides, suggesting a partner/integration model rather than only a consumer extension
• The docs navigation also links directly to the Chrome extension, blog/research surface, and the open-source scam database repo

4) Official open-source blacklist repo

Source: https://github.com/scamsniffer/scam-database

Selected excerpts from the repo:

Welcome to ScamSniffer’s open-source repository, dedicated to combating crypto phishing threats.

Daily Updates: Our data is refreshed every 24 hours to ensure you have the most current information.

7-Day Delay: The open-source data is provided with a 7-day delay to balance between offering free resources and protecting our real-time data’s integrity.

Additional signals from the repo:

• The repo exposes phishing domain and phishing address blacklists as concrete data products, not only marketing claims
• Official README says real-time access is a paid API, creating a clear split between community data and premium threat-intelligence feeds
• README lists major downstream users/partners, which is a useful adoption signal, though those claims were not independently verified in this pass

5) Official GitHub organization

Source: https://github.com/scamsniffer

Selected excerpts/signals from the public org page:

• The organization publicly anchors the project’s code/data footprint beyond the marketing site
• The GitHub surface is especially useful here because the website and docs are product-oriented, while the repo shows actual maintainable blacklist artifacts and integration posture

Notes

• This pass did not locate a classic whitepaper or litepaper from official Scam Sniffer sources.
• The strongest primary materials were the homepage, security-check docs, API/reference portal, and the scam-database GitHub repository.
• Scam Sniffer appears best categorized as a web3 anti-scam / phishing-detection / browser-safety and threat-intelligence platform rather than as a protocol or token project.