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Securing AI Factories

AccuKnox secures on-prem and cloud GPU fleets with policy-driven isolation.

Ai Factory

What are AI Factories?

What are AI Factories
  • AI Factories are large-scale, GPU-powered infrastructure platforms
  • Enables organizations to train, deploy, and manage AI models at enterprise scale
  • Combines massive compute resources with collaborative development environments
  • Creates new security and compliance challenges

Security Challenges in AI Factories

AI factories and GPUaaS introduce new risk vectors — data, model and compute need controls that go deeper than traditional cloud security.

Weak tenant isolation

Weak tenant isolation

Kubernetes offers namespace-level separation but not strong process/LSM-based isolation — attackers can attempt tenant escape and lateral movement.

Data & model exfiltration

Data & model exfiltration

Large datasets and trained weights are high-value targets — need provenance, access controls and telemetry to prevent leaks.

Model poisoning & supply-chain risks

Model poisoning & supply-chain risks

Compromised images or data inputs can introduce backdoors and biased behavior in models.

GPU misuse (cryptomining)

GPU misuse (cryptomining)

GPU workloads are attractive targets for miners — controlling access to CUDA and monitoring kernel behavior is essential.

Compliance & audit gaps

Compliance & audit gaps

Missing model provenance, weak logging and absent canary testing make audits and regulatory reporting difficult.

Telemetry blind spots

Telemetry blind spots

Lack of GPU-level, process-level and dataset-access telemetry limits detection and containment.

Deployment Modes

Deployment models designed to work for on-prem and cloud environments.

On‑Prem / Private Cloud

Block unsafe mounts, prevent RCE, enforce session timeouts and quotas.

Hybrid (Edge–Cloud)

Hybrid (Edge–Cloud)

Central policy plane with distributed enforcement and selective cloud burst to GPUaaS.

Cloud & GPUaaS

Cloud & GPUaaS

Agent-based runtime enforcement across hyperscalers and specialized GPU providers.

Deployment Modes

Supported AI / ML / LLM Platforms

Plug-ins and policy templates secure common platforms and runtimes.

NVIDIA CUDA

NVIDIA CUDA & Drivers

JupyterHub

JupyterHub / Notebooks

runai

Run:AI / Kubeflow

pytorch

PyTorch / TensorFlow

Hugging Face

Hugging Face / Transformers

tensorflow

TF Serving / Triton

kubernetes

Kubernetes (K8s)

modelhubs

Model Hubs (HF, S3)

Watch How AccuKnox Helps you
Achieve Al Factory Security

Demo scenarios covered in this video:

  • Hardening JupterNotebooks: Preventing Crypto Miners
  • Preventing data poisoning attacks in Kubeflow pipelines
  • Hardening inference engines: Preventing reverse shell in sklearn inference engine
  • Preventing lateral movement within the Kubeflow cluster

AccuKnox AI Factory – Security Platform

Mission-driven security that adapts to your environment.

security platform diagram

Use Cases - AccuKnox for AI Factories

Practical outcomes: safer notebooks, GPU governance, model integrity and faster compliance.

  • Notebook Sandbox & Guardrails

    Block unsafe mounts, prevent RCE, enforce session timeouts and quotas.

  • GPU AuthZ & CUDA Gating

    Grant CUDA access only to approved runtimes — stop miners and rogue kernels.

  • Model Protection & Provenance

    Sign models, track dataset lineage and run canary evaluations before rollout.

  • Runtime Microsegmentation

    Process-aware network rules, egress control and automated containment.

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AI Factory Schematic

Layered controls from CI → runtime with centralized policy lifecycle and scalable control plane.

ai factory schematic

AI Model Cards for Continuous Governance

Transform your model documentation from static reports into a real-time security and risk dashboard.

  • Continuous Security & Supply Chain
    Get a live Software Bill of Materials (SBOM), real-time vulnerability scanning, and ongoing license compliance checks for all model components.
  • Automated Validation & Risk Scoring
    Use sandbox-driven assessments for automated red teaming, evaluating safety, bias, toxicity, jailbreak resilience, and assigning a dynamically changing risk score.
  • Runtime Observability & Fencing
    Establish behavior baselines and monitor operational activity to detect policy violations and ensure real-time data isolation and fencing of model data stores.
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Key Differentiators

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Automated Red Teaming

Detects model vulnerabilities before attackers do.

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LLM Prompt Firewall

Ensure safe and controlled AI-driven interactions.

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Compliance & GRC

Out-of-box coverage for EU AI ACT, NIST, MITRE, OWASP & more

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Seamless Integration

Works with existing AI tools and workflows.

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Holistic AI Security

End-to-end protection for AI/ML workloads.

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Real-time Monitoring

Continuous threat detection and response.

AI Security Competitive Stack Ranking

ai security stack ranking
Agentic AI Security

Secure data/AI pipelines end-to-end with dataset lineage, secrets scanning, and runtime guardrails for inference endpoints.

Get Agentic AI Security eBook

Ready for a personalized security assessment?

“Choosing AccuKnox was driven by opensource KubeArmor’s novel use of eBPF and LSM technologies, delivering runtime security”

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Golan Ben-Oni

Chief Information Officer

“At Prudent, we advocate for a comprehensive end-to-end methodology in application and cloud security. AccuKnox excelled in all areas in our in depth evaluation.”

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Manoj Kern

CIO

“Tible is committed to delivering comprehensive security, compliance, and governance for all of its stakeholders.”

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Merijn Boom

Managing Director

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