How Sift makes decisions.
Sift has two shields: scam protection and news source context. This page explains exactly how each one works, what data we use, and where our judgments come from. We think you should know.
Scam Detection
Sift's scam detection runs on every page you visit and checks three things independently. All analysis happens locally in your browser — no data is sent anywhere.
1. Known scam domain list
We maintain a list of domains confirmed to host scam content — tech support fraud, fake prize pages, IRS impersonation, and similar schemes. If you visit one of these domains, Sift immediately shows a high-severity warning.
2. URL structure analysis
Sift analyzes the URL of every page for patterns common in phishing attacks, even on domains not in our list:
- Brand impersonation in subdomains — e.g. a URL containing "paypal" or "microsoft" that does not actually belong to those companies
- Unusually deep subdomain structure — five or more subdomain levels is a strong phishing signal
- IP address URLs — legitimate services almost never use bare IP addresses instead of domain names
3. Page content phrase scanning
Sift scans the visible text on the page for language patterns characteristic of common scams, grouped by category:
Tech support fraud
"Your computer has been infected", fake Windows Defender alerts, instructions not to close the browser, phone numbers presented as Microsoft or Apple support.
Fake prizes & rewards
"You have been selected", "claim your free gift", gift card payment requests, sweepstakes that require personal information to claim.
Government impersonation
IRS arrest warrant threats, Social Security suspension notices, Medicare card update requests, fake tax debt demands.
Financial fraud
Requests to verify bank account or credit card numbers, suspicious SSN requests, get-rich-quick investment promises, fake account suspension threats.
Important limitation: Sift catches known patterns, not every possible scam. New scam tactics emerge constantly. Sift is a first layer of protection — if something feels wrong, always stop and call a family member before providing any information or payment.
News Source Context
When you visit a news site or social platform in our database, Sift shows a banner with the source's bias rating and factual accuracy — and links to how AP News, Reuters, and PBS are covering the same story.
How we classify sources
Each source is assigned a bias category and a factual accuracy rating based on published research from established media analysis organisations. We do not make our own editorial judgments.
| Category | What it means |
|---|---|
| Far right | Strong conservative bias; frequently publishes misleading or unverified claims |
| Right-leaning | Conservative bias in framing and story selection; factual accuracy varies |
| Left-leaning | Liberal bias in framing and story selection; factual accuracy varies |
| Far left | Strong liberal bias; frequently publishes misleading or one-sided claims |
| Conspiracy / unreliable | Regularly publishes false, fabricated, or pseudoscientific content |
| Social platform | User-generated content with no editorial oversight — anyone can post |
Where our ratings come from
We cross-reference ratings from the following established media analysis organisations. We flag a source when there is meaningful consensus across at least two of them.
Why we don't flag centrist or mainstream sources
Sources like CNN, NBC, the New York Times, and the Washington Post have acknowledged left-leaning tendencies in framing and story selection. We do not currently flag them because their factual accuracy ratings remain high across the analysis organisations we reference, and because the goal of Sift is to protect against misinformation — not to flag every source with a viewpoint.
We may add context for centrist sources in a future update, presented differently to reflect the distinction between bias and inaccuracy.
What Sift doesn't do
- Sift does not block any content. Every banner is dismissible in one click.
- Sift does not tell you what to think or what to believe.
- Sift does not collect, store, or transmit any of your browsing data.
- Sift does not flag satire sites, opinion-only publications, or sources outside our current database.
- Sift's scam detection is pattern-based and will occasionally produce false positives on legitimate pages.
Suggesting a correction or addition
If you believe a source is incorrectly rated, missing from our database, or if you've encountered a scam pattern we're not catching, we want to hear from you.