Threat detection

Real threats found. Noise filtered out.

Unphish runs every signal through five layers of detection, combining custom rules, machine learning, AI reasoning and a final check by an analyst. You get confirmed phishing sites, scams and impersonation, including the ones built to hide from scanners, without the false alarms.

Detection pipeline · “Solstice Pay” · 24hExample
  1. 01
    Signals collectedDomains, certificates, ads, social, reports
    48,210
  2. 02
    Match your brand rulesNames, logos, kits, known bad hosts
    1,906
  3. 03
    Look like a threatMachine learning on code and visuals
    214
  4. 04
    High risk in contextAI reasoning and risk score
    31
  5. 05
    Confirmed by an analystReady for your threat feed
    9
9real threats
3rated P1
0sent without review

How it works

Five layers between a signal and your feed.

Each layer narrows thousands of raw signals down to the few that matter. Automation does the heavy lifting, and a person makes the final call.

01

Collect

Take in every signal.

New domains, certificates and hosting changes, search and social ads, social pages, messaging channels, spam and consumer reports.

DomainsAdsReports
02

Filter

Apply your brand rules.

Rules built for your brand look for your names, logos, copied layouts, phishing kit code and infrastructure linked to known bad actors.

Brand rulesKit codeFingerprints
03

Classify

Spot what looks fake.

Machine learning checks each page's code, logo and visuals, and keeps learning from new scam patterns.

Machine learningVisual match
04

Reason

Judge it in context.

AI-assisted analysis reads intent across languages, names the scam type and gives a risk score. The score sets priority but never hides a threat.

AI-assisted analysisRisk score
05

Validate

An analyst confirms it.

Nothing goes to takedown without a person checking it. Their decisions feed back into the models so detection keeps improving.

Analyst reviewFeedback loop

What we look at

What gives a fake away.

One signal rarely proves a site is fake. Detection works by putting many of them together.

New domains

solsticepay-rewards.top

Registrations that look like your name

Certificates and hosting

SSL issued · new host

Sites getting ready to go live

Phishing kit code

/kit/login.php

Code and layouts reused across scam sites

Logos and visuals

logo match 98%

Your branding copied onto pages and profiles

Infrastructure fingerprints

JARM · IP · AV tags

Servers linked to known bad actors

Ads

Sponsored · Solstice Pay

Search and social ad libraries

Social and messaging

t.me/solstice_bonus

Pages, profiles and channels pushing traffic

Spam and reports

“Your points expire today”

Scam emails, texts and customer reports

Hidden behaviour

mobile only · redirects

Pages that show the scam only to some visitors

See what our detection finds for your brand.

Get a free threat scan of the phishing sites, fake accounts and apps using your name today.

The results

Accurate enough to act on.

From cases we detected and closed for our clients in the first half of 2026.

96%

of the threats we detected and pursued were taken down

99%

of our reports held up with the platform. Fewer than 1% were rejected

100%

of threats checked by an analyst before any takedown

5

layers of detection between a raw signal and your threat feed

What our detection found

  • Phishing sitesFake logins, payment pages and rewards sites
    40%
  • ImpersonationFake accounts, pages and support profiles
    27%
  • Trademark and copyright misuseYour name, logo and content used without permission
    15%
  • Everything elseFake shops, apps, scam campaigns and data leaks
    17%

Share of all threats we closed, rounded

Nearly half of the threats were rated P1, the highest priority, so the most urgent ones were handled first.

Source: Unphish cases opened January to June 2026 across all clients and channels. Takedown rates exclude cases closed for other reasons, such as at the client's request.

Case study · Airline group

100%

of more than 180 mobile-only scam sites we pursued were taken down.

Fake points and rewards sites showed a blank or harmless page on a computer and only showed the scam on a phone, so ordinary scanners saw nothing wrong.

What we found

  • Checked the way customers see themPages were loaded as a phone would load them, so the hidden scam was found and captured as evidence
  • Cheap domains, swapped often42% were on .top domains, registered cheaply and replaced as soon as one was taken down
  • Points and gift card luresOffers to redeem or swap frequent flyer points for gift cards, built to collect logins

Client name withheld to protect confidentiality. January to June 2026.

AI reasoning in context

Normal for one brand, a red flag for another.

A huge discount is normal in a fashion sale and suspicious for a payments brand. AI-assisted analysis reads each finding in the context of your brand and industry, so it flags what's unusual for you and lets the rest go.

  • Names the scam type and the brand being copied
  • Reads content in multiple languages
  • Gives every threat a risk score to set priority
  • The score never hides a threat. An analyst still checks it
Explore threat monitoring →
Same offer, two brandsExample

Fashion retailer

“70% off everything this weekend.”

RiskLow

Big sales are normal for this brand

Solstice Pay

“Claim 70,000 bonus points. Log in by midnight.”

RiskHigh · P1

Payments brands don't ask for logins to claim offers

Why it was flagged

  • Urgencyby midnight
  • Login requestForm sends to another domain

Also checked

  • Domain ageRegistered 3 days ago
  • LogoCopied from your site
Sent to analyst review · confirmedIn your feed

Scams Prevention Framework

Ready for Australia's Scams Prevention Framework?

The SPF requires banks, telcos and digital platforms to take reasonable steps to prevent, detect, disrupt and report scams. Unphish gives you the action and the evidence to show you have.

01

Prevent

Spot lookalike domains, fake profiles and scam ads before they reach your customers.

02

Detect

Continuous monitoring across the web, social media, app stores and ads.

03

Disrupt

Rapid removal of scam websites, accounts and ads, backed by enforcement-grade evidence.

04

Report

A complete audit trail of every detection and takedown, ready for regulator reporting.

What's included

Everything you need to find threats early.

Threat FeedSearch…⌘K

https://solsticepay-rewards.top/redeem

P1Web PhishingAwaiting your review
OverviewTechnicalEvidenceTimelineDetection history

AI assessment

Likely phishing. A fake points redemption page for Solstice Pay that asks for login details. The scam only appears on mobile browsers. Desktop visitors see an empty page.

Confidence96%
  1. 01
    Collected

    New domain registration matched “solsticepay”

    09:02
  2. 02
    Rule match

    Known phishing kit layout · .top domain

    09:02
  3. 03
    ML classification

    Logo and login form match your site

    09:03
  4. 04
    AI reasoning

    Mobile-only content · points lure · P1

    09:03
  5. 05
    Analyst confirmed

    Evidence captured on mobile and desktop

    09:41

Captures

Solstice PayRedeem 70,000 pointsLog in

Mobile

Desktop

DismissApprove for EnforcementWatchWhitelist

Illustration of the Unphish client portal with example data.

Five-layer detectionCollection, rule filters, machine learning, AI reasoning and analyst validation in one pipeline
Brand-specific rulesYour names, logos, products and known lures built into the filters
Machine learningPage code, logos and visuals checked against known scam patterns
AI-assisted analysisContext, intent and language read for every finding, with a risk score to set priority
Hidden content checksPages loaded the way customers see them, to catch mobile-only scams and redirects
Analyst validationEvery threat checked by a person before it goes to takedown
WhitelistingYour official sites, accounts and partners recorded so they're never flagged
One-click enforcementReviewed threats move straight into takedown, where configured
EscalationIf a platform, host or registrar is slow or says no, we escalate through alternative contacts and abuse channels
Removal verifiedAutomated checks confirm threats are gone and flag them if they come back
Threat intelligenceRelated domains, kits and infrastructure clustered into campaigns
Reporting and audit trailDetection history, timelines, scheduled reports and a record of every action

Why it's different

Unphish vs basic alerting.

Basic alertingWith Unphish
Signals

Keyword and domain name matches

Domains, code, visuals, ads, social and reports

Accuracy

Floods of false alarms, or real threats missed

Five layers, then an analyst check

Hidden scams

Missed when a page looks clean to a scanner

Checked the way customers see it

Priority

Every alert looks the same

Risk-scored so urgent threats go first

Takedown

A separate, manual process

Send detections to enforcement in one click

Reporting

No record of why something was flagged

Full detection history and audit trail

Want to see what our detection finds for you?

Get a free threat scan →

FAQ

Threat detection questions, answered.

What is threat detection?

It's the process of deciding which of the things found by monitoring are real threats to your brand. Unphish takes in signals from domains, websites, ads, social media, messaging channels and reports, then works out which are phishing sites, scams or impersonation and how urgent they are.

How does the five-layer detection work?

Signals are collected, then filtered with rules built for your brand. Machine learning checks page code, logos and visuals. AI-assisted analysis reads context and intent and gives a risk score. Finally, an analyst confirms the threat before it reaches your feed or goes to takedown.

How do you avoid false positives?

Every threat is checked by an analyst before any takedown, and your official sites and accounts are whitelisted. It shows in the results. In the first half of 2026, fewer than 1% of our reports were rejected by the platform they were sent to.

Is it all done by AI?

No. Automation and AI-assisted analysis do the heavy lifting, but a person makes the final call. The AI risk score sets priority and never filters a threat out, and analyst decisions feed back into the models so detection keeps improving.

Can you detect scam sites that hide from scanners?

Yes. Some scam sites only show the scam on a phone, or redirect reviewers somewhere harmless. We load pages the way customers see them, so the hidden content is caught and captured as evidence. For one airline group, every one of the more than 180 mobile-only scam sites we pursued was taken down.

What happens after a threat is detected?

It appears in your threat feed with evidence, a risk score and its full detection history. From there it can go to enforcement in one click, where configured. In the first half of 2026, 96% of the threats we pursued were taken down.

Does Unphish help with the FTC Impersonation Rule?

Yes. The FTC Impersonation Rule, in force since April 2024, allows civil penalties up to $53,088 per violation for impersonating a business. Unphish finds and takes down those impersonations fast, with a complete audit trail of every detection and takedown.

Spot the signal

Red flag or red herring?

Our detection looked at a new site using the Solstice Pay name and found six things. Which ones actually point to a scam?

  1. Spot
  2. Reveal
  3. Take down

Red flag or not?

  1. SSL

    Padlock in the address bar

    HTTPS · valid certificate

    The site has a valid SSL certificate.

  2. 3d

    Registered 3 days ago

    Domain age

    solsticepay-rewards.top went live this week.

  3. MOB

    Scam only shows on phones

    Hidden behaviour

    On a computer, the page is blank.

  4. SP

    Uses your real logo

    Branding

    The Solstice Pay logo, exactly as on your site.

  5. FORM

    Login form sends elsewhere

    Page code

    Details typed in go to a different domain.

  6. HOST

    Hosted overseas

    Hosting

    The server is in another country.

Mark all six, then check your answers.

Results

Not on its own
  • PadlockMost phishing sites have one too. It means the connection is encrypted, not that the site is real.
  • Your real logoFakes copy it, but so do partners, news sites and resellers. It needs other signals with it.
  • Overseas hostingPlenty of real sites, maybe even yours, are hosted in another country.
Red flag
  • Brand new domainA days-old domain using your name, on a cheap extension, is a classic sign.
  • Mobile-only scamHiding from computers is how scam sites dodge scanners and reviewers.
  • Login sent elsewhereReal login pages don't send your password to someone else's server.

How we catch them

Put together, the three red flags make a confirmed phishing site. Here’s which layer catches each one.

New domainRule filters

New registrations using your name are matched against your brand rules as they appear.

Mobile-only pageChecked as a phone

Pages are loaded the way customers see them, so the hidden scam is captured as evidence.

Login sent elsewhereCode analysis

Machine learning reads the page code and spots forms sending details to another domain.

No single signal proves a site is fake. Detection is about putting them together, then having an analyst confirm before anything is taken down.

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Keep exploring

See where your name is being misused.

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