KubeArmor
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      • Security Policies (KSP, HSP, CSP)
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  • Use-Cases
    • Harden Infrastructure
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      • Pickle Code Injection PoC
      • Adversarial Attacks on Deep Learning Models
  • Documentation
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    • Policy Spec for Containers
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On this page
  • TensorFlow Based Use Cases
  • FGSM Attack on a TensorFlow Model
  • Keras Inject Attack and Apply Policies
  • Securing NVIDIA NIM

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  1. Use-Cases

ModelArmor Overview

PreviousAdvancedNextPickle Code Injection PoC

Last updated 21 days ago

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ModelArmor uses KubeArmor as a sandboxing engine to ensure that the untrusted models execution is constrained and within required checks. AI/ML Models are essentially processes and allowing untrusted models to execute in AI environments have significant risks such as possibility of cryptomining attacks leveraging GPUs, remote command injections, etc. KubeArmor's preemptive mitigation mechanism provides a suitable framework for constraining the execution environment of models.

ModelArmor can be used to enforce security policies on the model execution environment.

TensorFlow Based Use Cases

FGSM Attack on a TensorFlow Model

Keras Inject Attack and Apply Policies


Securing NVIDIA NIM

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▶️ Watch FGSM Attack Video
▶️ Watch Keras Inject Video
View PDF: Securing_NVIDIA_NIM.pdf