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Self-Reinforcing Protection

MaxiSafe provides continuous protection that not only detects and mitigates threats but also self-reinforces its defence capabilities. This adaptive approach enables MaxiSafe to evolve with emerging threats through a dynamic cycle of sensing, profiling, mitigating, and remediating.

By leveraging Bot Management, AI-WAF, API Protection, and DDoS mitigation, MaxiSafe adapts to evolving threats and optimizes its protection mechanisms in real-time.

Collect Information​

MaxiSafe collects multi-dimensional data to detect abnormal patterns and potential threats across traffic and request layers.

  • Traffic Analysis:
    • Analyses inbound and outbound traffic to identify anomalies in request volume, source IP distribution, and protocol usage.
    • Integrates DDoS Mitigation to track volumetric spikes and malicious traffic surges.

  • Client Fingerprinting:
    • Gathers device, browser, and network signatures to establish unique identifiers for each client.
    • Utilises Bot Management to detect automated tools and identify malicious scripts.

  • Content Inspection:
    • Scans request payloads and response bodies to detect suspicious data structures and code injection attempts.
    • Applies AI-WAF for dynamic rule analysis and signature-based detection.

Profile the Threat​

MaxiSafe builds a detailed threat profile based on data gathered during the sensing phase, allowing for more accurate response actions.

  • behaviour Analysis:
    • Monitors request behaviour patterns, such as navigation flows, frequency of requests, and response access sequences.
    • Correlates behaviour using API Protection to identify potential abuse patterns targeting specific endpoints.

  • Risk Scoring:
    • Assigns risk scores to each request based on the client’s fingerprint, historical behaviour, and traffic origin.
    • Cross-references with Bot Management to classify threats as low, medium, or high risk.

  • Contextual Mapping:
    • Constructs attack paths to identify threat origin, entry points, and targeted assets.
    • Implements AI-WAF to map multi-stage attacks and correlate activity across endpoints.

Mitigate: Take Actions to Mitigate Threats​

MaxiSafe executes real-time protective actions based on the threat profile and risk assessment.

  • Dynamic Blocking:
    • Blocks IPs, ranges, or specific request patterns based on predefined rules and threat profiles.
    • Applies API Protection to restrict access to sensitive endpoints and enforce rate limits.

  • Challenge-Response Mechanism:
    • Issues CAPTCHA or JavaScript challenges to suspicious clients identified through Bot Management.
    • Redirects high-risk requests to decoy pages or honeypots for further analysis.

  • Payload Sanitisation:
    • Filters malicious payloads through AI-WAF, blocking or modifying response data to prevent data leakage or exploitation.
    • Enforces Request Parameter Validation to detect and neutralise malicious inputs.

Remediate: Fix by Eliminating and Reducing​

MaxiSafe refines its detection models and security policies based on post-incident analysis, ensuring continuous improvement.

  • Threat Intelligence Integration:
    • Updates detection signatures and heuristic models based on new threat data and incident feedback.
    • Enhances AI-WAF with adaptive learning to recognize new attack patterns and adjust rule sets.

  • Incident Analysis and Reporting:
    • Analyses attack data to identify persistent threats and evolving tactics.
    • Utilises API Protection to log and trace API-based attacks, providing forensic data for investigation.

  • Adaptive Policy:
    • Adjusts Bot Management rules to account for new attack vectors and emerging automation tools.
    • Refines DDoS Mitigation thresholds based on observed attack frequencies and volumetric trends.