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Live dataset · refreshed continuously

The Global Scam Database — Updated Daily

What we track, where the signals come from, and how to use the database to verify an account, a wallet, or a URL before money moves.

What this database tracks

The GACS scam database is a public-good index of the patterns scammers use to extract money and identity from real people. It is not a list of names or accusations. It is a structured record of behaviours, infrastructure, and linguistic fingerprints that have been observed in confirmed fraud cases. As of 2026 the database covers four primary surfaces:

  • Impersonator account clusters. Handles across X, TikTok, Instagram, YouTube, Telegram, and WhatsApp Business that have been flagged as imitating a verified entity. Clusters are grouped by shared infrastructure — recycled bios, identical posting cadences, shared destination links — so that taking one down surfaces the rest.
  • Scam phrase signatures. Multi-word phrases drawn from confirmed scam DMs and comments, including the AI-generated variants that started replacing handwritten templates in 2025. Phrases are stored with category, language, and first-seen date so a journalist or platform-trust team can ask "when did this pattern emerge?" and get an answer.
  • Wallet and address blacklists. On-chain addresses linked to confirmed rug pulls, drainers, fake recovery agents, and pig-butchering off-ramps. Each entry carries an evidence pointer (transaction hash, source report ID) so you can audit the call.
  • Cross-platform fraud trails. Many 2026 scams hop platforms: TikTok comment to Telegram DM to a wallet drainer site to a Cash App tag. The database links these hops so a single search can surface every leg of a campaign.

Daily scam trends

Every 24 hours the trend report regenerates. Here is what the top of the list typically looks like in mid-2026 — the categories are stable, the specific accounts and addresses rotate constantly:

Top 10 scam types by daily volume

  1. Recovery scams — fake "fund recovery" agents targeting victims of earlier scams. The fastest-growing category two years running.
  2. AI celebrity impersonation — deepfake giveaway videos posted to TikTok and YouTube Shorts, redirecting to Telegram.
  3. Wallet drainer phishing — fake airdrop and claim pages targeting Web3 wallets.
  4. Pig-butchering on dating apps — long-con investment fraud, increasingly handed off to AI chat agents after the first week.
  5. Fake job offers — "remote crypto analyst" roles that require a wallet deposit to start.
  6. Cashtag and Zelle impersonation — fake customer-support handles intercepting payment-app users.
  7. Tech support scams — pop-up and phone-based, still resilient because they target non-technical adults.
  8. Sextortion — AI-generated nude images of real people, used as leverage.
  9. Fake brokers — copy-paste broker sites with fabricated regulator badges.
  10. Rugpull memecoins — paired with influencer impersonation to seed demand.

What's new in the last 30 days

  • A surge in deepfake voice-note "emergencies" on WhatsApp, using cloned voices of the recipient's adult children.
  • A new "verified deepfake-protected message" phrase template that scammers attach to outbound DMs to short-circuit suspicion.
  • Impersonator clusters using Threads and Bluesky as overflow infrastructure when their primary X accounts get suspended.
  • A wave of fake "press releases" posted to discount PR-distribution sites, used to dress up rugpull tokens with the appearance of legitimate coverage.

How GACS collects signals

The methodology matters because a bad scam database is worse than no scam database — false positives destroy real businesses and erode trust. GACS uses four signal streams, all of which are auditable:

  • Public reports. Anyone can submit a scam through gacs.app. Reports include the URL, handle, or address, plus optional evidence (screenshots, message text). Submissions are anonymous; we don't tie reports to accounts.
  • Automated scanners. Our social scanner checks handle structure, posting cadence, bio language, follower-to-following ratio, and link destinations against learned patterns. The wallet scanner checks on-chain behaviour (mixers, sanctioned addresses, drainer contract interactions).
  • Cross-platform correlation. When the same destination link or wallet address appears across multiple reports from different surfaces, it gets promoted from "watch" to "confirmed". Single reports never trigger a public flag on their own.
  • Partner feeds. Where available, we ingest open-intel signals from anti-fraud communities, chain-analytics providers, and APWG-style exchanges. Every external source is attributed.

No personal data is stored on searchers. When you look up a handle, we log the category and count for trend reports — never your IP, browser fingerprint, or session in a form that can be re-identified. That is enforced at the database layer, not just in a policy document.

How to use the database

Search

Paste a handle, a URL, or a wallet address into the scanner on any GACS tool page. You get back a verdict (Safe, Caution, or Danger), the matching signals, and — if the entity is part of a known cluster — links to the related accounts. No login required.

Scan

Beyond one-off lookups, the scanner can run on your following list or your recent DMs to surface impersonators already inside your orbit. Use this monthly if you have a public following; weekly if you are over 100k followers.

Report

If you encounter a scam not in the database, submit it. Every confirmed report makes the next search faster for someone else. Reports take 60 seconds and require no account.

How to protect yourself

A scam database is a verification tool, not a force field. The actual safety checklist is short and old:

  • Verify before sending. Any payment request — by anyone, on any platform — gets a second-channel check. Phone the person on a number you already had. Reply to an old email thread.
  • Treat urgency as a red flag. Real institutions do not require action in the next 30 minutes. Scammers do, because urgency disables verification.
  • Never approve a wallet transaction you don't fully understand. If the signature prompt has a function name you don't recognize, decline and look it up.
  • Use a hardware wallet for anything above pocket change. Browser wallets are fundamentally exposed to drainer sites; hardware wallets are not.
  • Run a free scan before you act on a DM about money. Five seconds of friction prevents most losses.

Bottom line

The Global Scam Database exists to put a verification step between a scammer's pitch and a victim's wallet. It is free, anonymous, continuously updated, and built on signals you can audit. Use it before you send; use it before you sign; and if you see something it has missed, report it so the next person doesn't get hit.

Related reading

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