What is ShieldLabs Bot Detection?
ShieldLabs Bot Detection identifies automated activity on your website, including AI agents, AI assistants, search crawlers and browser automation. It analyzes device, browser, network and IP signals, then returns bot detections with the identification and Risk Score. The dashboard groups bot detections as follows:- Good bot: recognized search bots, AI bots and AI browsers. The dashboard groups these detections under Good bot, and their Risk Score is always 0. The provider name appears when available.
- Bad bot: Browser Automation, Device spoofing or JavaScript Disabled was detected. The dashboard groups these signals under Bad bot. Each signal has weight 90; their combined contribution is capped at 90. Read the active signals and request context when protecting an action.
View bot traffic in the dashboard
Open Overview to see Good bots and Bad bots in the visitor breakdown. Use Analytics to investigate individual identifications and their risk signals. Open an identification card for the details of a check. Recognized search and AI bot signals display the provider when available. The dashboard’s Good bot and Bad bot groups summarize the underlying detections.How ShieldLabs detects bots
ShieldLabs analyzes device, browser, network and IP signals to detect automated activity. The result distinguishes automation and spoofing signals from recognized bot traffic.Browser automation and spoofing
Browser checks identify signs of automation, altered device characteristics and unavailable browser capabilities:
JavaScript Disabled describes the availability of capabilities required by the check. Use these detections with the protected action and account context.
Recognized search and AI traffic
ShieldLabs recognizes supported clients from their presented identity and available network evidence. Supported browser platforms can also establish their identity through request signatures.
The provider name appears when available. Optional
client_identity distinguishes recognized names from verified attribution. A known name alone does not establish verified identity; verification coverage depends on the client and evidence.
Browse the bot directory for supported clients. Read AI agent detection for browser-platform verification and AI assistant detection for assistant fetchers and crawlers.
How to integrate ShieldLabs bot detection
Bot detection uses your ShieldLabs integration and returns results with the identification. Follow these steps to connect the result to your application:1
Create an account and get your API key
Create your ShieldLabs account, add your domain and copy its public API key. The quickstart walks through account setup and your first identification.
2
Install the browser integration
Add the JavaScript snippet or a supported frontend SDK. Use authenticated checks when you have a signed-in user and anonymous checks otherwise.
3
Receive and use the server result
Configure a scored webhook, verify its signature and read the bot flags in
data.detection_flags. Match the result to your action using the Identification ID and validate the expected domain and user context on your backend.Read a webhook result
This shortened example shows Browser Automation in the scored webhook’sdata object:
signals for their reported weights and risk_score for the overall result. The complete webhook reference describes the envelope, delivery identifier and other fields.
Recognized good-bot traffic has search_bot, ai_bot or ai_browser set to true and a Risk Score of 0. Apply the result to the access policy for the action your application protects.
Bot results in webhooks and History
Use a scored webhook for the full bot detection result. History provides a stored identification with a smaller set of fields:
History rows do not include the
ai_bot and ai_browser flags. Read these flags from the scored webhook rather than treating a missing History field as a negative detection. History API describes the row format.
The table uses webhook JSON field names. With a server SDK, read the preserved raw webhook data for provider names and client_identity when using a normalized identification.
Next steps
Bot directory
Browse supported search crawlers, AI bots and browser platforms.
Risk signals
Read detection keys, weights and dashboard groups.
AI agent detection
Understand browser-platform signatures and verified attribution.
AI assistant detection
Interpret assistant fetchers, AI crawlers and their identity metadata.