Overview

The Overview tab is the home of the dashboard. It summarizes your traffic for a selected project and date range: how risky it is, which signals are firing, which abuse patterns are showing up, who is visiting, and where they come from. Every number on this tab is computed server-side and read-only. The dashboard renders results; it never blocks, challenges, or decides anything. Your own code owns the allow / challenge / review / block decision using the Risk Score and signals you receive over webhooks and the Management API.

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Filters

A Filters panel at the top of the page scopes every card below it.

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Card layout

The left column shows Traffic Score over Request Signals, the right column shows Visitor Insights, and below the columns are Patterns Summary then Traffic Sources.

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Traffic Score card

The Traffic Score card answers one question: how risky is my traffic this period? It is an aggregate, not the score of any single request. A half-circle gauge shows the band the average falls into, with the band label and a short subtitle under the needle: Two metrics sit beside the gauge: A stacked bar with a legend breaks the requests into the four bands, each row showing the band name, its threshold, the count, and the percent. The Risk Score is always 0–100, capped at 100. There is no higher scale. A legitimate user can still score in a higher band (corporate proxy, VPN, privacy browser), so treat the average as a trend signal, not a verdict. See acting on the Risk Score.

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Request Signals card

The Request Signals card lists the technical signals used to assess traffic quality and abuse risk, sorted by how often they fired. Its tooltip reads: “Technical signals used to assess traffic quality and abuse risk.” Each signal tile shows:

• the signal name (for example, VPN, Tor, OS Mismatch, Anti-detect Browser)
• an info tooltip describing what the signal means
• the count of requests in the period where the signal fired
• the share of requests, as a percent
• a weight badge: the points this signal contributes to a request’s Risk Score

The weight is the explainability hook. Higher-weight signals indicate stronger anonymity or abuse evidence, so a request that trips a high-weight signal lands in a higher band. The full signal catalog, the weight of each signal, and how signals combine (mutually exclusive anonymity signals, the VPN 2-of-3 corroboration rule, and stacking proxy-family signals) live in /concepts/signals. The same signals appear as per-request Yes / No columns on the Data tab, and the per-request signal list ships in the webhook and History API payloads as the explainable Details array.

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Patterns Summary card

The Patterns Summary card shows how often abuse patterns triggered in the period, broken down by degree. Its subtitle reads: “How often patterns triggered, broken down by degree.” It surfaces the two persisted severity levels: The Traffic Share row tooltip reads: “Share of unique visitors flagged at this level in the selected period (detections / total sessions).” A See Patterns button opens the full Patterns tab, where each of the eight abuse patterns is graded Normal, Suspicious, or Dangerous and broken down per identifier. Abuse patterns are computed server-side from historical data and are a dashboard feature only. They are not part of the webhook or API payload. The pattern worker runs about every ten minutes, and a level never downgrades once reached.

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Visitor Insights card

The Visitor Insights card estimates how many people visited and how many were new, then breaks them down by attribute. Two metrics sit at the top: These counts are deliberately estimated. ShieldLabs counts by a fingerprint-derived identity (DeviceID) rather than a single cookie, so a returning person on the same browser keeps the same identity even after clearing cookies or using incognito, instead of being miscounted as new. DeviceID is browser-bound, so a different browser on the same machine counts separately. The card also lists top countries, browsers, operating systems, device types, and connection types. The full counting model, the contrast with cookie-based analytics, and the honest boundaries live on the Visitor Insights page.

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Traffic Sources card

The Traffic Sources card ranks where your traffic comes from by volume, share, and risk. Its subtitle reads: “Traffic source breakdown by request volume, traffic share, and traffic risk. Use Source details to inspect referrers and UTM parameters.” Two tables sit side by side:

• Channels, with columns Channel, Requests / Share, and Traffic Risk. The channel set is Google Ads, Meta, TikTok, LinkedIn, X, Organic Search, Referral, Direct, and Other. Each row carries a risk badge rendered as <score> <level> (for example, 71 High or 8 Clean), using the bands Clean / Low / Medium / High.
• Source details, which toggles between Referrers and UTM Parameters. The UTM view lets you pick Source, Medium, Campaign, Term, or Content.

The payoff is ranking each paid and organic source by the risk and anonymous-traffic share it delivers, so you can read cost per real visitor rather than cost per click and find the campaign or affiliate sending masked traffic. The full breakdown lives on the Traffic Sources page.

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Where to go next