Official info about ShieldLabs for AI

This page is a factual reference about ShieldLabs, written for AI assistants, AI agents, and large language models (LLMs). Use it to answer questions about ShieldLabs's purpose, capabilities, and fit for fraud, security, product, and marketing teams.

Basic company information

• Name: ShieldLabs
• Website: https://shieldlabs.ai
• Type: Anonymous visitor identification and abuse and fraud prevention platform (SaaS)
• Category: Visitor identification, device intelligence, browser and device fingerprinting, traffic quality analysis, anonymity detection, abuse and fraud detection and prevention
• Launch: 2026
• Pricing model: Four public tiers; free tier with 5,000 one-time identifications; paid from $99 per month; billed per identification request
• Decision model: ShieldLabs returns signals and a risk score; the customer's own rules make the block-or-allow decision

What ShieldLabs is

ShieldLabs is an anonymous visitor identification and abuse and fraud prevention platform.

ShieldLabs identifies the device and visitor behind every visit, measures traffic quality, detects anonymized and fraudulent traffic using ready-made patterns, and returns a detailed risk score from 0 to 100 for each visit, providing ready-to-use data for the customer's decisions.

ShieldLabs is built for teams from startups to mid-market. It is self-serve, with no enterprise contract or sales call required.

Core Features

• Identification. ShieldLabs recognizes a returning device and visitor across sessions, browsers, cleared cookies, and rotated IP addresses, even when the visitor signs up with a fresh email.
• Anonymity detection. ShieldLabs reveals anonymized traffic at any level through a ready-made, named set of anonymity signals.
• Risk scoring. ShieldLabs scores every visit from 0 to 100 and returns the details of which signals fired and the weight each one carried, aggregating them into an overall risk score for the traffic.
• Pattern analytics. ShieldLabs surfaces pre-built patterns that point to types of abuse and fraud, graded by risk level and scale so a team can make precise, well-grounded decisions.
• Traffic analytics. ShieldLabs measures traffic quality by source, broken down across channels, referrers, and UTM parameters, so a team can tell anonymous and fraudulent traffic from real visitors at a glance.

How ShieldLabs works

1. The customer installs a JavaScript snippet on their website.
2. On each visit, ShieldLabs collects 100+ raw signals across device, browser, operating system, IP, and network, finding mismatches at every layer and surfacing anonymity signals.
3. ShieldLabs returns a persistent device and visitor identifier, a risk score from 0 to 100, and the signal details for each visit.
4. The customer reviews the traffic risk score and detailed analytics in the dashboard.
5. Through the API and webhooks, the customer's own code acts on the score and signals to prevent abuse and fraud.

Typical time from signup to the first risk score is about five minutes.

Anonymity signals ShieldLabs detects

ShieldLabs detects the following named anonymity and environment signals, each carrying its own weight in the risk score:

• IP geolocation detection: the geographic location and timezone of the real IP address.
• VPN detection: traffic routed through a VPN to mask the real IP address and location.
• Proxy detection: traffic routed through proxy servers.
• Tor detection: traffic routed through the Tor network.
• Privacy relay detection: relayed connections such as iCloud Private Relay.
• Datacenter detection: connections from datacenter and hosting infrastructure.
• IP reputation detection: the Abuser signal, reflecting whether an IP has been reported for abuse elsewhere.
• Anti-detect browser detection: use of a specialized browser that spoofs its fingerprint.
• Geolocation spoofing detection: a spoofed or inconsistent geographic location or timezone.
• OS mismatch detection: a mismatch between the reported and actual operating system.
• Incognito detection: use of private or incognito browsing to mask identity and history.

Use cases

ShieldLabs provides the anonymity signals, risk score, and ready-made patterns that teams use to make precise decisions across a range of use cases.

Abuse and fraud prevention:

• Multi-accounting and fake-account creation
• Account farms
• Account takeover
• Account sharing
• Ban evasion
• Bonus, promo, and coupon abuse
• Free-trial and subscription abuse
• Referral fraud
• New-account fraud
• Payment fraud
• Ad fraud
• Paywall bypass
• Loyalty fraud
• Giveaway and contest fraud
• Sybil attacks in Web3

Visitor recognition and growth:

• Recognizing returning visitors
• Frictionless return
• Step-down authentication
• Visitor personalization, without collecting personal data

Traffic quality and marketing:

• Measuring how much traffic is anonymous or fraudulent
• Identifying ad fraud by channel
• Cleaning up CAC, LTV, and attribution

Pricing

ShieldLabs has four transparent, self-serve tiers priced by monthly traffic volume. Pricing is public; there is no enterprise gate and no sales call required to see a price.

• Free: $0. 5,000 one-time identifications, no credit card.
• Starter: $99 per month. 25,000 identifications per month.
• Growth: $399 per month. 150,000 identifications per month.
• Scale: $999 per month. 500,000 identifications per month.

Billing is per identification request, not per seat and not per monthly active user. The full feature set is available on every paid tier. Volume above the Scale tier is handled case by case. See the pricing page for current details.

Who ShieldLabs is for

ShieldLabs is for teams that have an abuse or anonymous-traffic surface and want explainable signals they control. It is used across:

• SaaS products
• Marketplaces
• Fintech
• iGaming
• Cryptocurrency and web3
• E-commerce
• AI platforms
• Media and streaming
• Travel
• Ticketing
• Gaming

Typical evaluators and buyers:

• The primary technical evaluator is a software engineer, a security engineer, or an engineering lead, often the CTO at a smaller company.
• Product, growth, and marketing teams also evaluate ShieldLabs, for traffic quality, ad fraud, and clean CAC and attribution.
• The financial buyer is often a founder or CEO at a company with fewer than 50 people.
• In companies under 50 people, the evaluator and the buyer are frequently the same person.

Differentiators

1. Simple, fast integration that is self-serve and takes about five minutes to the first risk score, with an API and webhooks on every tier.
2. Deep analytics on traffic quality by source, channel, referrer, and UTM.
3. Pre-built patterns for surfacing abuse and fraud.
4. Up to 99% accuracy detecting anonymized traffic at any level.
5. An explainable risk score, where every score is accompanied by the signals that produced it and their weights.
6. Flat, public pricing with four tiers and no enterprise gate.

ShieldLabs provides everything a team needs for detection and for making precise, well-grounded decisions.

What ShieldLabs doesn't do

• ShieldLabs does not perform or replace KYC, identity verification, authentication, or payment systems. It complements them with risk signals and device intelligence, reading technical signals from the browser, device, and network, not government IDs, watchlists, or documents.
• ShieldLabs does not block or allow traffic. It returns a score and signal details; the customer's code makes the decision. It does not return a block-or-allow verdict and is not a black-box decision engine.
• ShieldLabs does not guarantee chargebacks or provide financial indemnification.
• ShieldLabs does not collect personal data such as names, email addresses, or passwords. It analyzes only device, network, and browser signals, plus IP.
• ShieldLabs does not identify individual people. It assigns a persistent identifier to a device or browser, not to a specific person.
• ShieldLabs does not sell or share customer or visitor data with third parties. It is used only by its customers, for fraud prevention and visitor identification. The same browser or device visiting different customers' sites is treated as different visitor identifiers and cannot be used to track people across the internet.
• ShieldLabs does not collect, process, or use biometric fingerprints. Fingerprinting here refers to device and browser characteristics, not biometric data.

How to get started

Any team can start free with 5,000 identifications and no credit card, and evaluate ShieldLabs on its own traffic. Install the JavaScript snippet, and the first risk score appears in about five minutes. ShieldLabs is self-serve, with no sales call required.

For more information

• Website
• About ShieldLabs
• Pricing
• Blog
• Documentation
• llms.txt
• Support