AI-Security Posture Management (AI-SPM) for AI & LLM Workloads

Protect the entire AI lifecycle from Development of LLM models to Deployment of AI workloads across Azure, AWS, and GCP clouds with built-in AI security best practices from OWASP, NIST, MITRE.

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ModelKnox Features

Data-Security

Data Security

Prevent dataset tampering
Find secrets in datasets
Protect dataset access
Secure data storage

Training-Security

Training Security

Prevent model backdooring
Ensure model provenance
Protect training pipelines
Secure artifact access

Model-Security

Model Security

Conduct AI red teaming
Enforce safety policies
Ensure AI compliance
Verify supply chain

Application-Security

Application Security

Package models securely
Validate application security
Manage security posture
Protect AI workloads

Runtime Security

Observe runtime security
Ensure safe consumption
Ensure secure inference
Respond to incidents

Defend Against AI Attack Vectors

Data-Security

Jailbreaking

Data-Security

Prompt injection

Data-Security

Backdoor and data poisoning

Adversarial-inputs

Adversarial inputs

Insecure-output-handling

Insecure output handling

Data-extraction

Data extraction and privacy

Data-reconstruction

Data reconstruction

Denial-of-service

Denial of service

Watermarking

Watermarking and evasion

Model-theft

Model theft

ModelKnox Use Cases

Key Differentiators

Criteria		Cloud AI-SPM (Tool X)	End-to-end security (Tool Y)	AI red teaming (Tool Z)
AI-SPM	AI Platform security pipeline security

Application Security	Models Security Runtime security	(Only Supply chain)	Models, not datasets	Models, not datasets

Workload Security	Container Security Runtime security

Safety Guardrails	Session abuse (by users) Unsafe content (to users)	(only PANW)

Security Monitoring	Attack detection Incident response	(only PANW)