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TamperingDetails Class

Properties

Name Type Description Notes
anomaly_score float The output of this model is captured as anomaly_score, a statistical score indicating how rare the visitor's browser signature is compared to the overall population. Values close to 1 signify highly anomalous browsers and we consider anything above the threshold of 0.5 to be actionable (the result field conveniently captures that fact). [optional]
anti_detect_browser bool Detects whether the request shows evidence of anti-detect browser usage. This field may be triggered by: * heuristic detection of known anti-detect browser behavior * machine learning detection of anti-detect browser patterns Examples of anti-detect browsers include tools such as AdsPower, DolphinAnty, OctoBrowser, and GoLogin. [optional]

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