Fraud Detection Library

Content fraud, decoded

A reference library of the fraud and scam patterns that target online platforms — the warning signals that expose each one, and how to detect fraudulent content at scale.

Identity abuse

Impersonation

Impersonation is when an account pretends to be a real brand, business, or person to win trust and exploit it. On platforms it shows up as fake official accounts, cloned profiles of real users, and seller pages that copy a legitimate brand to redirect its customers.

Detection guide →
Marketplace fraud

Scam listings

A scam listing is a fake product, service, or rental ad posted to a marketplace to take payment or personal data without ever delivering. The seller usually pushes the deal off-platform, asks for upfront payment, and disappears once paid.

Detection guide →
Payment abuse

Payment fraud

Payment fraud on a platform is any attempt to move a transaction outside its protected payment flow, or to fake a payment, so the victim loses money with no recourse. It surfaces in content as requests to pay off-platform, fake escrow links, and overpayment tricks.

Detection guide →
Reputation abuse

Fake reviews

A fake review is a rating or testimonial written to manipulate a product's reputation rather than report real experience. It can be positive (paid or incentivized praise) or negative (a competitor or extortion attempt). Most fake reviews come in coordinated bursts from accounts with no genuine purchase history.

Detection guide →
Social engineering

Phishing content

Phishing content is any user-submitted message, post, or listing that tries to trick someone into handing over credentials, payment details, or personal data. On platforms it usually arrives as a fake support reply, a too-good giveaway, or a link to a lookalike login page.

Detection guide →

Fraudulent content moderation, as a service

ModPilot detects scams, fraud, and abuse across text and images in real time — AI workflows, custom rules, and human escalation behind a single API.

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