Stop survey fraud with one API.

The dtect API scores every participant as good, suspicious, or bad, and returns the signals you need to act on each one.

A verdict at the entry point

Run our security checks when a participant enters your study, and get a clear verdict back.

Full signal transparency

For every participant you will receive a score and fraud categories, along with device, network, and location details.

Easy to integrate

Drop our JavaScript or React SDK to capture every signal automatically.

Get API access

We'll set you up with API keys and walk you through the fastest path to integration.

Prefer a no-code option? Get started with Link Protector for free.

How it works

When someone enters your study, dtect evaluates their device, network, location, behavior, and quality signals to give you a clear verdict.

ParticipantEvaluationResultParticipant 01
DeviceDeviceNetworkNetworkLocationLocationBehaviorBehaviordtect Scoregood

Participants evaluated

Waiting for the first participant to complete...
One call, complete picture

Three layers of visibility

Every response gives you the full security evaluation, the fraud categories it triggered, and the raw data details behind them.

1

Outcome

results

Multiple security checks covering automation, AI usage, location blocks, VPN detection, and more, along with the dtect Score that can be good, suspicious, or bad.

2

Categories

categories

Human-readable groupings that summarize what kind of risk was detected, including repeat submission, location mismatch, network masking, and more.

3

Raw Signals

location, network, device

The underlying data points behind the verdict (IP, city, timezone, browser, OS, and more) so you can audit decisions, build custom rules, or surface evidence to your team.

dtectScore: bad
{
  "token": "61cdfb51-6153-4258-878f-e07953163b11",
  "results": {
    "dtectScore": "bad",
    "isDuplicateDevice": true,
    "isDuplicateIp": false,
    "isDuplicateId": false,
    "isLocationBlocked": true,
    "isLocationInvalid": true,
    "isAutomationDetected": false,
    "isVpnDetected": false,
    "isDeviceTampered": true,
    "isTorDetected": true,
    "isIncognito": true,
    "isUntrustedBrowserOrOS": true,
    "isBlockedIP": true,
    "isPrivacySettingsEnabled": true,
    "isHighActivityDevice": true,
    "isAIUsageDetected": true,
    "isQualityRejected": true
  },
  "categories": [
    "SETUP_MANIPULATION",
    "NETWORK_MASKING",
    "LOCATION_MISMATCH",
    "REPEAT_SUBMISSION"
  ],
  "location": {
    "ipTimezone": "America/New_York",
    "browserTimezone": "Australia/Melbourne",
    "country": "usa",
    "city": "New York"
  },
  "network": {
    "ip": "170.127.159.63",
    "timezoneMismatch": true,
    "dataCenter": true,
    "relay": true
  },
  "device": {
    "id": "1d9c7ea15e40d9d6...",
    "browserName": "Chrome",
    "osName": "macOS",
    "deviceVendor": "Apple"
  }
}
Categories explained

From signals to clear categories

Each category groups related signals into a single, easy-to-act-on risk type. A category only fires when at least one of its underlying signals is true.

REPEAT_SUBMISSION

This session appears to reuse an identity that has been observed in previous activity.

Underlying signals

isDuplicateDeviceisDuplicateIdisDuplicateIp

LOCATION_MISMATCH

Location-related signals observed during this session are inconsistent with each other.

Underlying signals

isLocationInvalidisLocationBlocked

NETWORK_MASKING

Network signals indicate that the origin of this session may be intentionally obscured.

Underlying signals

isVpnDetectedisTorDetected

BOT_ACTIVITY

Activity patterns observed in this session are not consistent with typical human behavior.

Underlying signals

isAutomationDetectedisHighActivityDeviceisBlockedIP

SETUP_MANIPULATION

The device or browser environment used in this session shows signs of restriction or modification.

Underlying signals

isDeviceTamperedisVirtualMachineisDevToolsOpened+3 more

UNUSUAL_BEHAVIOR

Interaction patterns in this session suggest low confidence in the authenticity of the user's behavior.

Underlying signals

isAIUsageDetectedisQualityRejected
Built for the way you work

Made for your team

Whether you're hosting surveys, recruiting participants, or running a panel, the dtect API plugs into your existing stack and starts protecting your data quality on day one.

Quantitative Research

Score every participant in real time

Block fraud at the entry point of your survey or platform, before it impacts your data.

  • Reduce reconciliations
  • Save time cleaning data
  • Stop fraud at the source
Panel Companies

Improve your panel's quality

Apply consistent fraud-prevention checks across every participant with the data to back each decision.

  • Improve completion and acceptance rates
  • Vet participants before they join your panel
Qualitative Research

Pre-screen before the screener

Catch fraudulent participants before they ever reach your screener questions, so only legitimate candidates get in front of clients.

  • Add tech fraud checks before screening
  • Catch behaviors humans can't
  • Protect client-facing recruiting
Other use cases

Add fraud-resistance to any flow

Plug dtect into onboarding, registration, or any user flow where data quality matters.

  • Lightweight integration
  • No PII collected
  • Works with any backend

Ready to add dtect to your workflow?

Talk to our team to get API access, walk through integration, and find the right plan for your workflow.

Get API access

We'll set you up with API keys and walk you through the fastest path to integration.

Prefer a no-code option? Get started with Link Protector for free.