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Comprehensive and In-Depth Detection

MaxiSafe conducts full-path detection, covering all stages from client-side initialisation to HTTP request processing and HTTP response delivery. This multi-phase inspection ensures accurate identification of abnormal behaviour, bots, and threats across the entire interaction chain.

Detection is performed in three stages:

  • Client-Side Detection:
    Captures real-time behaviour and environment signals before a request is issued.

  • HTTP Request Detection:
    Inspects and classifies incoming traffic based on headers, payloads, and behavioural indicators.

  • HTTP Response Detection:
    Identifies data leakage, scraping patterns, and abnormal response access.

MaxiSafe integrates detection results with risk-based scoring and enforces adaptive policies at the edge through bot control, contextual detection, and fingerprint profiling.

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Client-Side Detection​

Client-side detection enhances accuracy and context awareness before request processing. The detection is done via lightweight interrogation executed in the client environment and fingerprinting mechanisms that gather execution signals.

  • Environment Fingerprint Collection
    Collects device/browser characteristics, including canvas, font, audio, and WebGL fingerprints.

  • Browser Identification
    Validates browser integrity and detects headless or emulated environments to prevent spoofing.

  • JavaScript Execution Verification
    Confirms client-side script execution and interaction capability.

  • Platform Authentication Check
    Evaluates OS, browser, and hardware authentication against expected combinations.

  • Challenge Response Handling
    Issues challenge pages to evaluate automation resistance.

Detection result:

  • Risk level is determined (normal, suspicious, high-risk).
  • Requests from non-compliant clients are redirected, challenged, or blocked.
  • Fingerprint IDs and risk scores are logged for downstream correlation.

HTTP Request Detection​

MaxiSafe inspects each inbound HTTP request at the edge before forwarding it to the origin server. This stage includes protocol compliance checks, behavioural analysis, and policy-based filtering:

  • Bot Control
    Detects and mitigates traffic from malicious or non-compliant bots using signature matching, fingerprint behaviour, and challenge-based validation.

  • Contextual Detection
    Analyses request context including navigation flow, referer chain, user interaction history, and time anomalies to identify suspicious behaviour patterns.

  • Custom Rules Detection
    Enforces user-defined rules based on HTTP headers, parameters, paths, cookies, or query values. Supports logic conditions and regex matching.

  • Header Inspection
    Identifies malformed, spoofed, or missing headers such as User-Agent, Referer, Host, and Accept-Language to detect automation or evasion tactics.

  • Rate Limiting and Frequency Analysis
    Flags abnormal request frequency from a given client or IP range. Supports path-specific and burst-based thresholds.

Advanced Detections

  • HTTP Method Validation
  • IP Reputation Check
  • Request Payload Anomaly Detection
  • Parameter Tampering Detection
  • Protocol Abuse Detection

HTTP Response Detection​

Response-stage detection ensures sensitive content is not unintentionally exposed and helps detect scraping or automated content mining, including:

  • Data Leakage Detection
    Scans response payload for exposed tokens, keys, or configuration values.

  • Content Scraping Pattern Detection
    Detects repeated or automated access to structured content, such as product pages or price listings.

  • Behavioural Loop Detection
    Identifies repetitive access patterns consistent with scraping or brute-force cycles.