I've been building FraudShield because I kept running into a simple problem: when something looks suspicious online, the evidence is usually spread across multiple places. A domain might look unusual, an email may not match the business, a brand name may appear in a look-alike domain, or there may be other technical signals — but checking all of these manually is time-consuming. FraudShield is my attempt to bring these checks together through an API. The current version focuses on things like: • Domain and website analysis • Typosquatting and brand look-alike detection • IDN/Punycode and Unicode-confusable checks • Email authentication (SPF/DKIM/DMARC) • Domain/infrastructure signals • Evidence and relationship analysis One thing I'm deliberately trying to avoid is simply returning "scam" or "not a scam." I'd rather show the underlying signals and let users understand why something deserves further investigation. This is still early, and I'm launching partly to learn. If you work in SaaS, fintech, e-commerce, marketplaces, cybersecurity, or build APIs, I'd really appreciate your feedback: What information would you actually want from an API like this? And what would you need to see before trusting its results? Thanks for checking it out 🙌

FraudShield

Evidence-driven fraud investigation API

Evidence-driven fraud investigation API