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**event_id** | **str** | Unique identifier of the user's request. The first portion of the event_id is a unix epoch milliseconds timestamp For example: `1758130560902.8tRtrH` |
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**timestamp** | **int** | Timestamp of the event with millisecond precision in Unix time. |
**linked_id** | **str** | A customer-provided id that was sent with the request. | [optional]
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**environment_id** | **str** | Environment Id of the event. For example: `ae_47abaca3db2c7c43` | [optional]
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**suspect** | **bool** | Field is `true` if you have previously set the `suspect` flag for this event using the [Server API Update event endpoint](https://docs.fingerprint.com/reference/server-api-v4-update-event). | [optional]
@@ -42,11 +43,15 @@ Name | Type | Description | Notes
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**privacy_settings** | **bool** | `true` if the request is from a privacy aware browser (e.g. Tor) or from a browser in which fingerprinting is blocked. Otherwise `false`. | [optional]
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**root_apps** | **bool** | Android specific root management apps detection. There are 2 values: * `true` - Root Management Apps detected (e.g. Magisk). * `false` - No Root Management Apps detected or the client isn't Android. | [optional]
**simulator** | **bool** | iOS specific simulator detection. There are 2 values: * `true` - Simulator environment detected. * `false` - No signs of simulator or the client is not iOS. | [optional]
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**suspect_score** | **int** | Suspect Score is an easy way to integrate Smart Signals into your fraud protection work flow. It is a weighted representation of all Smart Signals present in the payload that helps identify suspicious activity. The value range is [0; S] where S is sum of all Smart Signals weights. See more details here: https://docs.fingerprint.com/docs/suspect-score | [optional]
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**tampering** | **bool** | Flag indicating browser tampering was detected. This happens when either: * There are inconsistencies in the browser configuration that cross internal tampering thresholds (see `tampering_details.anomaly_score`). * The browser signature resembles an \"anti-detect\" browser specifically designed to evade fingerprinting (see `tampering_details.anti_detect_browser`). | [optional]
**tampering_ml_score** | **float** | A score that indicates the models calculated probability that an event is coming from an anti detect browser. * Values above `0.8` indicate that the request is an anti detect browser based on the ml model * Values below `0.8` indicate that the request is not an anti detect browser based on the ml model | [optional]
**virtual_machine** | **bool** | `true` if the request came from a browser running inside a virtual machine (e.g. VMWare), `false` otherwise. | [optional]
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**virtual_machine_ml_score** | **float** | Machine learning–based virtual machine score, represented as a floating-point value between 0 and 1 (inclusive), with up to three decimal places of precision. A higher score means a higher confidence in the positive `virtual_machine` detection result | [optional]
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**vpn** | **bool** | VPN or other anonymizing service has been used when sending the request. | [optional]
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