ShieldLabs

ShieldLabs

Fraud detection and prevention with traffic quality scoring.

G
@growth213
Published on Aug 17, 2026
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11 PeerPush
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Ranked #3
Product of the Day
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Pricing
Freemium from $79
Platforms
Web

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Community award Aug 18, 2026Community awardA Product of the Day, Week, or Month award this product won from the community.
#3 Product of the Day

Aug 18, 2026

AI-readyAI-readyWhether this product carries the structured data - use cases, audiences, platforms - that lets AI match it to the right questions.
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Described for AI with use cases, audiences, platforms and pricing so assistants can match it to the right questions.
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Live

Via the PeerPush API and MCP

Queryable through the PeerPush API, MCP and semantic search from day one.

About ShieldLabs

ShieldLabs is a fraud detection and prevention platform built on visitor identification and anonymity signal detection. Detection covers the full spectrum of anonymity: VPNs, proxies, Tor, Apple Private Relay, datacenter IP ranges, anti-detect browsers, browser automation and bot traffic, drawn from more than 100 signals collected on each visit and interpreted by a combination of deterministic rules and AI. Identification persists over time. A returning visitor is recognised with up to 99% accuracy despite cleared cookies, incognito mode, IP rotation and months between visits. Alongside the score for an individual visit, the dashboard gives an overall traffic risk score for the whole property, with the split across clean, low, medium and high risk bands and how it moves over time. It also pre-computes patterns across accounts, devices and identities, pointing to multi-accounting, account sharing, account takeover and account farms operating behind one connection. Traffic quality analytics break traffic down by risk band and by source, including channels, referrers and campaigns, showing which acquisition channels bring anonymised and high-risk visitors. Stops multi-accounting, free-trial abuse, bonus and promo abuse, referral fraud, loyalty fraud, new-account fraud, account takeover, account sharing, ban evasion, paywall bypass, payment fraud, ad fraud, location spoofing and Sybil attacks. The same recognition works the other way round as well, letting you identify a returning customer without making them prove who they are again. Setup is one JavaScript snippet, about five minutes to the first signal, with ready-made guides for React, Next.js, Vue, Angular, Svelte and Preact, as well as WordPress, Shopify and Tilda. Server-side SDKs are available for Node.js, Python, Go and PHP, with an OpenAPI specification for everything else. Pricing is published and flat: 5,000 free identifications with no card and no expiry, then $99, $399 and $999 per month. The cost per identification falls as volume grows, yearly billing saves 20 percent, and traffic above a plan allowance keeps being identified and scored.

Product Video

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Reviews (1)

Average 5.0 out of 5

5.0

Based on 1 review

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Comments (4)

omribenshoham
@omribenshoham

Strong fraud detection that stops bad actors before they cost you real money. Quality traffic matters more than volume - this tool makes sure every visitor strengthens your business, not weakens it.

omribenshoham
@omribenshoham

Fraud detection that actually catches bad traffic patterns saves millions in wasted spend. Real-time quality scoring lets you focus budget on genuine conversions instead of chasing phantom leads. That's the power of getting traffic intellig

saeef
@saeef

Interesting approach to fraud detection. Curious how accurate the 99% returning visitor recognition is in real-world traffic, especially with more advanced anti-detect browsers.

G
@growth213

Detection that works is usually sold through a demo and a quote. This is a snippet, five minutes to the first signal, and a published price. 5,000 free identifications, no card. Questions welcome.