# SHIELD alternative: explained decisions for web, apps and APIs

Source: https://kavralab.com/compare/shield-alternative/

**SHIELD** is a device-first fraud intelligence platform that gives each physical device a persistent ID and flags tools such as emulators, app cloners, GPS spoofers, VPNs, proxies and bots. **Kavra** assesses every request across network, device, browser and behavior, and returns a plain-language finding with a recommended action your backend applies.

- **Kavra approach:** Explained assessment and recommended action per request
- **SHIELD approach:** Persistent device ID plus 20+ risk indicators, mobile-first
- **Visitor friction:** Both run invisibly; trusted devices can skip challenges
- **Best for:** Kavra: web, bots and proxies. SHIELD: deep mobile app tampering

## What SHIELD does

SHIELD calls itself a device-first fraud intelligence platform for web and mobile apps. Its core is **SHIELD Device ID**, which SHIELD says stays persistent across sessions, app reinstalls, factory resets and tampering, and in incognito mode, so fraudulent activity ties back to the same physical device. Trusted devices can then skip re-verification, one-time passwords and CAPTCHAs.

On top of the ID, SHIELD returns **20+ risk indicators** that flag fraud tools and techniques, including emulators, app cloners, GPS spoofers, VPNs, proxies and bots. **SHIELD Sentinel**, its always-on session monitoring, profiles the whole device session so it can catch the moment a trusted user switches on an app cloner, GPS spoofer or screen-sharing tool mid-session. SHIELD also describes cluster analysis that links shared devices to expose fraud networks, behavioral biometrics, location intelligence and configurable risk thresholds with trust scores.

SHIELD ships iOS and Android SDKs, JavaScript for web and support for Unity, React Native, Flutter and Cordova. It markets to ride-hailing, fintech, digital banking, e-commerce, social media, gaming, iGaming and crypto platforms, and says no personally identifiable information is needed to start.

## How Kavra approaches the problem differently

SHIELD is built around recognizing the device. Kavra is built around deciding what to do with the request. Each Kavra assessment has a plain-language headline, the findings behind it, risk by domain (automation, impersonation, network, tampering, abuse), network context and a recommended action: allow, verify or block. Your backend applies it. Kavra never blocks on its own.

Kavra analyzes 3,000+ data points per visit and looks for contradictions between layers. It recognizes returning devices across visits and links one actor behind many accounts, and when a device changes its fingerprint, Kavra keeps it as one actor with N rotations. The main differences show up on the web and on the network side.

- **Browser automation and fake browsers.** Playwright, Puppeteer, Selenium, stealth plugins, headless Chrome and HTTP clients imitating browsers, caught across layers. See [headless browsers](https://kavralab.com/detect/headless-browsers/).
- **The real connection.** Kavra's own edge network sees how a visitor actually connects, not only what the page or app reports.
- **Own proxy intelligence.** Real exit IPs of commercial residential and mobile proxy networks, measured continuously, on top of 30+ public reputation feeds.
- **Verified good bots and AI agents.** Search crawlers and [AI agents](https://kavralab.com/detect/ai-agents/) are verified by cryptographic signatures and published IP ranges, so you can allow them on purpose.
- **API and backend traffic.** A server-side request API assesses calls that never load a page.

## Kavra vs SHIELD: capability comparison

Both products detect spoofed devices without friction for real users. They put the weight in different places.

|  | Kavra | SHIELD |
|---|---|---|
| Main output | Headline, findings, domain risk, recommended action | Persistent device ID, risk indicators and trust scores |
| Center of gravity | Web, app and API requests, with network evidence | Mobile apps and web, device-first |
| Device recognition | Returning devices recognized; rotation kept as one actor | Device ID persistent across reinstalls, factory resets and tampering, per SHIELD |
| Emulators, VMs, device farms | Detected by contradictions between claimed and observed environment | Emulator detection among the risk indicators; device clusters linked |
| App cloners and GPS spoofing | Not dedicated signals; spoofed devices and emulators are covered | Core risk indicators, plus mid-session monitoring |
| Browser automation | Automation frameworks, stealth plugins, headless browsers, HTTP clients | Bots among the risk indicators; web methods not publicly detailed |
| Proxy intelligence | Own measurement of commercial proxy exit IPs plus 30+ feeds | VPN and proxy risk indicators |
| Verified AI agents and crawlers | Recognized by signatures and published IP ranges | Not publicly documented |
| SDKs | One web script, native iOS and Android SDKs, server-side API | iOS, Android, JavaScript, Unity, React Native, Flutter, Cordova |
| Identity data you must send | None; technical signals only, legal basis applied per visitor region | No PII needed to start; GDPR compliance stated |

## When SHIELD may be the better fit

SHIELD's focus on mobile devices makes it a natural choice for some teams.

- Your product is **mainly a mobile app**, such as ride-hailing or mobile gaming, and most fraud happens inside the app.
- You need dedicated detection of **app cloners, GPS spoofers and screen-sharing tools**, including when they are switched on mid-session.
- You build games in **Unity** and want an engine plugin, or you ship with Cordova.
- Your fraud model mainly needs a **device ID that survives factory resets** as its key, with your own team writing the rules.
- Location truth matters a lot, for example driver or rider location on a ride-hailing platform.

## When Kavra is the better fit

- Much of your traffic and fraud is on the **web**: signups, logins, checkouts, bonus claims and public APIs.
- You face browser automation: [credential stuffing](https://kavralab.com/solutions/credential-stuffing/), [scalping](https://kavralab.com/solutions/scalping/), scraping or scripted signups.
- Operators hide behind [residential and mobile proxies](https://kavralab.com/detect/residential-proxies/) and you want them recognized for what they are.
- You want each decision explained in plain words for analysts, support and customer appeals.
- You want to allow verified AI agents and search crawlers while stopping unverified ones.

The two can work side by side. An app-first business can keep a mobile device ID for in-app tampering signals and use Kavra on its website, login and API endpoints, where browser automation and proxy traffic arrive. Kavra's native iOS and Android SDKs also cover apps when you want one explained verdict across every channel.

## Device ID first vs decision first

**Decision-first (Kavra)**

- What is on the other end: person, bot, AI agent or disguised tool
- What gave it away, in plain language
- Allow, verify or block, with presets to tune
- Observe-only mode before anything is blocked

**Device-first (SHIELD)**

- Which physical device this is, over time
- Which fraud tools are active on it
- Trust scores and thresholds to configure
- Signals that feed your own risk engine

> **The short version:** SHIELD answers **which device is this, and what tools is it running?** with a strong mobile focus. Kavra answers **what is behind this request, what gave it away, and what should you do?** across web, apps and APIs. For [iGaming](https://kavralab.com/industries/igaming/) and other mixed web and app businesses, the choice often comes down to where most of the abuse happens.

## Why teams choose Kavra

One script and one API call, and every request comes back explained.

- **Explained decisions**: Headline, findings, domain risk and a recommended action on every assessment.
- **Browser automation caught**: Automation frameworks, stealth plugins and fake browsers exposed across layers.
- **Own proxy intelligence**: Commercial residential and mobile proxy exits measured continuously.
- **Rotation stays one actor**: A device that changes its fingerprint is tracked as one actor with N rotations.
- **Your backend decides**: Kavra recommends and never blocks on its own. Start in observe-only mode.

## FAQ

### What is SHIELD device intelligence?

SHIELD is a device-first fraud intelligence platform. It assigns each physical device a persistent ID that, according to SHIELD, survives reinstalls, factory resets and tampering, and it flags fraud tools such as emulators, app cloners, GPS spoofers, VPNs, proxies and bots through 20+ risk indicators. It offers SDKs for mobile, web and game engines.

### Does Kavra detect emulators and device farms like SHIELD?

Yes. Kavra detects emulators, virtual machines, device farms and spoofed devices by checking what a device claims against how it actually behaves and connects. It links accounts that share an actor, so a farm of emulated phones claiming referral or signup rewards shows up as one cluster rather than many new users.

### Is Kavra only for websites?

No. Kavra starts with one web script and one API call, and also offers native iOS and Android SDKs and a server-side request API for backend and API traffic. The same explained assessment, with findings and a recommended action, comes back whichever channel the request arrived on.

### Can I use SHIELD and Kavra together?

Yes. A common split is to keep a mobile device ID for in-app tampering signals such as app cloners and GPS spoofing, and use Kavra on the website, login and APIs, where browser automation and proxy traffic arrive. Your backend combines both into its own allow, verify or block rules.

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