EXPLIoT CloudFuzz

We know your AI is intelligent

But is it secure?

Testing AI/ML systems requires domain knowledge. At Payatu, our AI/ML domain experts have orchestrated ways to help you secure your intelligent application against esoteric and potentially severe security and privacy threats.

ML Security assessment coverage

  • Understanding the Application

    • Use-case
    • Product Capabilities
    • Implementations
  • Attack Surface Identification

    • Understanding the ML Pipeline
    • Gather Test Cases If Any
  • Threat Modeling

    • Actors and Entity Boundaries
    • Possible Attacks identification on Exposed endpoints
    • Possible attack vectors
  • Model Endpoints

    • Understand ways with which end users communicate with model
    • Simulate end user interaction
  • Adversarial Learning Attack

    • Craft inputs to bypass fool classifiers
    • Use custom built tools
    • Automated generation of theoretically infinite zero day samples as possible
  • Model Stealing Attack

    • Model deployed locally or remotely
    • Reverse engineer deployed application
    • Custom built scripts for black-box model stealing attacks
  • Model Skewing and Data poisoning Attack

    • Simulate Feedback loops abused by attackers
    • Quantify the skewness of model
  • Model Inversion and inference

    • Get access to model via valid or compromised communication channels
    • Infer sensitive samples from training dataset from model
  • Framework/ Network/Application assessment

    • Identify traditional vulnerabilities in application
    • Leverage them for above attacks
  • Reporting and Mitigation

    • Comprehensive Mitigation Proposal
    • Work With Developer/SME for implementations


Get to know more about our process, methodology & team!

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