Community Scam Database
Scams reported and tracked by our community
The community database is the running record of scams that ScamSupport users have actively reported in the last few weeks. It serves two purposes: as a quick-lookup index for confirming that a suspicious subject line you have just received is part of an active campaign that others have also flagged, and as a feedback loop into the detection model itself — the more independent reports the model sees for a particular pattern, the more reliably it catches that pattern when the next user pastes a similar message in.
The database is built entirely from voluntary submissions through the Report a Scam form. We do not crawl email for content, we do not buy scam-message datasets from third parties, and we do not include messages users have only scanned (the scanner is private and the content never reaches us). Everything below has been submitted by someone, reviewed by a moderator, and stripped of personal details before being clustered into the visible entries. The volume numbers next to each entry (“Reported 47 times”) are the count of independent submissions for that campaign cluster, not a scraped or estimated figure.
Recently Reported Scams
Subject: "Confirm your PayPal account - Action required"
Fake PayPal verification email with suspicious link. Reported 47 times.
Subject: "Unusual activity on your Amazon account"
Fake Amazon billing notification. Reported 23 times.
Subject: "Your HMRC tax refund is ready - Claim now"
Government impersonation claiming tax refund. Reported 156 times.
Subject: "Verify your Apple ID - Security alert"
Fake Apple security warning with malicious link. Reported 89 times.
Subject: "Windows Security Alert - Download protection now"
Fake Microsoft Windows alert prompting malware download. Reported 234 times.
Top Threats This Week
| Scam Type | Reports | Trend |
|---|---|---|
| PayPal Phishing | 487 | ↑ 23% |
| HMRC Tax Scams | 342 | ↑ 18% |
| Amazon Account Fraud | 298 | → 0% |
| Microsoft/Windows Alert | 276 | ↓ 5% |
| Romance Scams | 198 | ↑ 8% |
How the Database Works
The community database is built entirely from user submissions. When someone submits a scam through the Report page, we strip identifying details (their email, any names mentioned in the message body), tag the entry with the scam type and the impersonated brand, and merge it with similar reports already on file. Reports that share the same sender domain, similar subject line, and overlapping body text are clustered into a single entry with a counter — that's where the "Reported 47 times" figure on each row comes from.
The trend column on the weekly table is calculated from the change in submissions versus the previous week. A scam type rising 20% week-on-week usually means a fresh campaign is in active distribution; a flat or declining number means the campaign has run its course and the people behind it have likely moved on to a new lure.
How to Use This Page
Treat the database as a sanity check. If you've received an email or text that you suspect is a scam, search this page for the impersonated brand or the subject line. If you see a recent entry with a similar pattern and a high report count, you can stop second-guessing — it's almost certainly the same campaign. Don't click any link, don't reply, don't call any number in the message; just delete it.
If you receive something that isn't in the database yet, that doesn't mean it's safe. New campaigns appear daily and our database lags real-world distribution by hours to days. Run the suspicious message through ScamSupport's main checker, which uses the underlying detection model rather than the public archive of past reports.
What We Don't Show
We never publish the email address or phone number of the person who reported a scam, and we redact recipient details from the body of the reported message before it enters the database. We also don't publish messages whose content is unique to the reporter (for example, romance scam conversations referencing real names or family members).
If you spot one of your own messages in the database and want it removed, contact us at info@signaltools.org — we'll take it down within 24 hours.
Reading the Trends Honestly
The numbers on this page reflect what our community submits, not the absolute volume of scam activity in the wild. Treat the table as a leading indicator of what ordinary people are encountering, not as a comprehensive intelligence feed.
That said, the trends here track surprisingly well with data from the National Cyber Security Centre's Suspicious Email Reporting Service, with Report Fraud's published quarterly figures, and with the abuse reports published by major brands.
The most useful application of the table is timing. If you receive a message that matches a recent high-volume entry, the probability that it's a scam is overwhelming.
Why the database is selective rather than comprehensive
The database covers a meaningful slice of what is in circulation, not all of it. UK Finance and the new Report Fraud service each receive multiples of our submission volume; the National Cyber Security Centre’s Suspicious Email Reporting Service (SERS) processes tens of millions of forwarded emails a year. We do not try to compete with the national-scale intelligence aggregation that those bodies do, because we cannot — the volume and the institutional access are not comparable. What we can do is curate at human scale: every entry on the database has been read by someone and described in plain language, and the categorisation is consistent enough that you can scan ten entries in a minute and form a useful picture of what is currently active.
The trade-off is coverage. A campaign in active distribution may not appear here until enough independent submitters have flagged it for a cluster to form, which can lag the live attack by hours or days. If you have a specific message in front of you and you want a verdict now, the scanner is the right tool. The database is the right tool for checking whether a pattern you saw a few days ago has been confirmed by others, and for seeing the slower-moving picture of which categories are growing this month.
Contributing to the Database
Have you encountered a scam? Help protect others by reporting it to our community database. Your reports help improve our detection algorithms and protect millions of users.
Report a Scam →