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Three-Layered Protection

MaxiSafe employs a three-layered protection framework designed to provide comprehensive and in-depth detection of vulnerabilities and threats. By integrating behaviour-based, rule-based, and AI-powered protection, MaxiSafe enhances its defense capabilities to effectively address various threat types, from automated attacks to sophisticated zero-day exploits.

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Behaviour-Based Protection​

This layer focuses on identifying automated and non-automated threats through behavioural analysis, enabling MaxiSafe to detect and respond to emerging attack patterns in real-time.

  • Automated Attacks:
    • Detects and mitigates high-frequency requests and bot-driven attacks through Bot Management.
    • Applies rate limiting and interaction analysis to identify scraping tools and credential-stuffing bots.

  • Automated and Non-Automated OWASP Top Threats:
    • Monitors request payloads for signature-based threats, such as SQL Injection, Cross-Site Scripting (XSS), and Cross-Site Request Forgery (CSRF).
    • Utilises AI-WAF to recognise attack patterns even in modified or obfuscated payloads.

  • Automated and Non-Automated Business Threats:
    • Identifies fraudulent transactions and unauthorised access attempts using Contextual Detection and IP Reputation Analysis.
    • Tracks session activity to detect abnormal behaviour associated with account takeover or session hijacking.

  • Automated and Non-Automated 0-Day Exploits:
    • Applies heuristic analysis and anomaly detection to identify unknown attack patterns not covered by existing signatures.

Rule-Based Protection​

This layer leverages predefined security rules to block specific types of non-automated threats, providing a baseline defense against well-known vulnerabilities and attack vectors.

  • Non-Automated OWASP Top Threats:
    • Enforces WAF rules to detect and block common attack patterns, such as command injection, XML External Entities (XXE), and Remote File Inclusion (RFI).
    • Applies Content Scraping Detection to prevent unauthorized data extraction from critical endpoints.

  • Non-Automated Business Threats:
    • Implements Custom Rule Detection to enforce policies based on business logic, such as purchase limit validation and login frequency control.
    • Monitors sensitive paths and transaction pages to prevent unauthorized access or data manipulation.

  • Non-Automated 0-Day Exploits:
    • Provides custom rule sets to monitor for emerging threats based on known vulnerabilities.
    • Integrates Threat Intelligence Feeds to update rule sets and address newly discovered attack techniques.

AI-Powered Protection​

This layer focuses on detecting complex, non-automated threats using advanced AI algorithms, enabling real-time adaptation to evolving attack tactics.

  • Non-Automated Business Threats:
    • Leverages Machine Learning Models to identify anomalous behaviour patterns indicative of account abuse or data exfiltration.
    • Executes Behavioural Profiling to correlate session data across multiple interactions, detecting stealthy attacks that bypass rule-based protection.

  • Non-Automated 0-Day Exploits:
    • Applies AI-WAF to dynamically adjust protection rules based on detected anomalies.
    • Conducts Payload Analysis to identify rare or suspicious request structures that deviate from normal traffic patterns.

MaxiSafe’s three-layered protection framework ensures comprehensive coverage against both common and advanced threats. By combining behaviour-based, rule-based, and AI-powered detection mechanisms, MaxiSafe creates a robust security posture capable of addressing both known and emerging attack vectors effectively.