AI Fraud & Abuse Prevention
Fraud prevention for AI products.
Protect your compute.
Free-account farms and bots consume resources intended for new customers. ShieldLabs detects multi-accounting and bot automation to help protect inference credits, product capacity and genuine growth.
Start FreeCreate your AI workspace
Start building with free credits.
Browser automationProxy
Protect compute budgets
Keep inference credits for eligible customers.
Preserve service capacity
Keep automated abuse from crowding out real usage.
Trust customer acquisition
Stop repeat accounts from inflating new-user growth.
Welcome genuine users
Keep legitimate customers moving through signup and access.
Free compute allocations
Stop repeat credit claims.
Protect inference budgets.
ShieldLabs detects multi-accounting among accounts registered with different emails. Help keep free token quotas and generation credits for eligible customers.
Automated web activity
Stop automated farming.
Keep capacity available.
ShieldLabs detects bots and browser automation around signup, generation and browser-based product requests. Protect inference capacity from scripted abuse while keeping legitimate usage moving.
Expose disguised requests
Detect proxies and anti-detect browsers around AI product workflows.
Find risky acquisition sources
See the channels, referrers and campaigns bringing automated traffic to your AI product workflows.
Paid product access
Protect paid accounts.
Keep customer access secure.
ShieldLabs detects account sharing and account takeover around AI product access. Help protect paid plans and saved credit balances while keeping legitimate customers moving.
The ShieldLabs platform
More than one fraud check.
Protect your entire product.
Connect identification, device and network intelligence, bots, named risk signals and ready-made account abuse detections. Traffic quality analytics gives the sources behind risky activity.
Enterprise-level functionality. Without enterprise pricing.
Accurate identification
Recognize returning visitors even when they clear cookies, use incognito mode or change their IP address. Detect linked users with different email addresses.
Identification accuracy
High-Risk Event detection
Detect account abuse out of the box by automatically identifying linked users. No fraud model training is required.
Risk signals
Get ready-made detections of automation, masking and spoofing, with named risk signals behind each result.
Bot & AI traffic detection
Detect bot activity from browser automation signals. Recognize useful crawler and AI traffic alongside abuse detections.
Risk scoring
Score every visit from 0 to 100 and classify it as trusted, suspicious or dangerous. See the signals behind each score.
Device fingerprinting
Recognize devices by their fingerprints. Identify the browser, operating system and device type. Detect headless browsers and tampering.
IP & Network Intelligence
Reveal the real IP address and geolocation behind masking. Detect VPNs, proxies and private relays.
203.0.113.42198.51.100.23Traffic quality scoring and risk analytics
Get one score for all your traffic and ready-made quality results by source, channel, referrer and UTM campaign.
Analytics dashboard
Find risky accounts and visits.
See the sources behind them.
Explore visitors, users, devices and IPs with detected account abuse and identification risk assessments. See traffic quality by channel, referrer and campaign.
How it works
Start protecting your product.
Connect once and start receiving ready-made fraud and abuse detections.
- 01
Add the snippet or SDK
Connect your product and start identifying visitors and users.
- 02
Receive ready-made detections
Get detected fraud and account abuse in the dashboard or through API integrations.
- 03
Prevent fraud and abuse
Protect customer accounts, paid access and signup incentives in your product.
Developers
Integrate in
5 minutes.
A single API to identify, detect and score. Receive risk data through API responses and webhooks. Integrate selected data points into your business logic to prevent fraud and abuse.
Protect your users and product
Protect your compute.
Grow with real users.
Start Free FAQ
Understand the evidence.
Put it to work.
What is abuse of AI products?
Abuse of AI products includes repeated free-credit enrollment and automated requests that consume compute or access beyond a product’s permitted use.
How does ShieldLabs help prevent fraud and abuse in AI?
ShieldLabs detects multi-accounting and bots around AI signup and browser-based product requests. Protect free compute allocations and product capacity with ready-made risk assessments.
Can ShieldLabs detect repeat claims of AI inference credits?
Yes. Multi-accounting detection links registered accounts using different emails, while bot detection identifies automated signup and browser-based requests that consume free compute.
Does visitor recognition work after cookies are cleared?
Yes. ShieldLabs recognizes returning visitors across new sessions, cleared cookies, incognito browsing and IP changes. These are visitor-recognition capabilities.
How do I integrate ShieldLabs?
Add the browser snippet or client SDK to your web product. Receive identification results, risk signals and account abuse detections through the dashboard, API integrations and webhooks.
How can AI products use a risk assessment at signup?
Trusted, Suspicious and Dangerous assessments let an AI product protect inference credits and access without adding the same friction to every genuine user.
Can ShieldLabs protect both free and paid AI access?
Yes. Multi-accounting and bot detection help protect free allocations. Account sharing and account takeover detection help protect paid product access and customer accounts.