Fraud Detection and Prevention for Web Applications

ShieldLabs is a fraud detection and prevention platform designed for web applications. It helps businesses identify risky users, improve traffic quality, and detect abuse such as multi-accounting, account sharing, account takeover, and fraudulent traffic. By analyzing device, browser, network, and identity signals, ShieldLabs provides a risk score for each visitor, helping teams make better decisions based on real user activity instead of anonymous or suspicious traffic.

1. Traffic quality scoring

ShieldLabs evaluates every visit and converts traffic behavior into a traffic-quality score. This helps businesses understand anonymous traffic levels, identify risky sources, and improve the accuracy of marketing and user analytics.

2. Visitor identification with 300+ signals

The platform creates persistent visitor identities using device, browser, network, and IP-related signals. It can continue recognizing visitors even after cookie removal, IP changes, or incognito sessions.

3. Fraud and abuse detection

ShieldLabs detects common online abuse scenarios, including:

• Multi-accounting
• Account sharing
• Account takeover
• Promo and bonus abuse
• Free trial abuse
• Ad and traffic fraud

4. Risk scoring and explainable signals

Each visitor receives a risk score from 0 to 100 with related risk indicators. Businesses can review signals such as VPN usage, proxy connections, datacenter IPs, anti-detect browsers, and suspicious activity before taking action.

5. High-Risk Events monitoring

ShieldLabs connects users, devices, and IP addresses to identify suspicious patterns. Detection events include confidence levels and can be customized for different fraud prevention needs.

6. Developer-friendly integration

The platform provides a JavaScript snippet, API, and webhooks. According to the website, installation can be completed with one JS snippet and is designed to work with various frameworks, CMS platforms, and no-code builders.

7. Traffic analytics

Traffic analytics help businesses measure traffic risks by channel, referrer, and UTM source. This allows teams to identify low-quality acquisition sources and better understand audience behavior.

1. Add the ShieldLabs JavaScript snippet to your website to begin collecting visitor signals.

2. Review the generated visitor IDs, risk scores, and risk signals through the API or dashboard.

3. Configure backend actions based on risk levels, such as additional verification or blocking suspicious activity.

4. Monitor traffic sources regularly to identify channels with high anonymous or suspicious traffic.

5. Use fraud detection signals together instead of relying only on individual indicators like IP address or cookies.

What is ShieldLabs?

ShieldLabs is a fraud detection and prevention tool that helps websites identify risky users and suspicious traffic. It focuses on detecting issues such as multi-accounting, account sharing, account takeover, and traffic fraud.

How does ShieldLabs work?

ShieldLabs collects device, browser, and network signals from visitors and creates a visitor identity. It then provides a risk score and related signals through API and webhooks.

What types of fraud can ShieldLabs detect?

ShieldLabs is designed to detect multiple types of abuse, including fake accounts, repeated free trial usage, bonus abuse, suspicious logins, ad fraud, and account sharing.

Does ShieldLabs provide API access?

Yes. The website states that API and webhooks are available across plans, allowing developers to integrate risk information into their own systems.

Does ShieldLabs have a free plan?

Yes. ShieldLabs provides a free tier with 5,000 free identifications according to the website. Paid plans are available for higher identification volumes.

ShieldLabs offers a free tier and paid plans based on monthly identifications.

The website also mentions custom scaling options for higher traffic volumes.

1. ShieldLabs provides a focused solution for businesses that need fraud detection, visitor identification, and traffic quality analysis. The combination of risk scoring, device intelligence, and network signals makes it suitable for websites dealing with account abuse or unreliable traffic sources.

2. The developer-oriented setup is a practical advantage. The JavaScript snippet, API, and webhook support can help teams integrate fraud signals into existing workflows without building a detection system from scratch.

3. A potential limitation is that businesses still need to define their own response strategies after receiving risk scores. The platform identifies suspicious behavior, but final decisions such as blocking users or adding verification steps require business-specific rules.

4. Overall, ShieldLabs is positioned as a specialized fraud prevention tool for SaaS, fintech, e-commerce, gaming, and other industries where user identity quality and traffic reliability are important. Its effectiveness will depend on how well organizations configure and apply the provided risk information.