Secure AI models and data
The Problem
AI raises security risks and concerns
80%
65%
40%
Solution Overview
Secure data, AI, and LLMs with confidence
Natively integrated with the Zscaler Data Security platform, Zscaler AI-SPM enables you to confidently secure data, AI and LLMs in the cloud.
Broad coverage and native integration
Natively protect resources associated with platforms like Amazon Bedrock, Microsoft Azure Foundry AI, and Google Vertex AI, as well as unmanaged AI services like Hugging Face and Ollama.
AI-powered auto-discovery and classification
Automatically discover, classify, and inventory AI-related services and connected data assets, including models, datasets, and vectors.
AI and data risk mitigation
Correlate risks such as data poisoning, misconfigurations, data exposure, misuse, and entitlements, and mitigate AI and data risks with guided remediation.
Regulatory compliance assurance
Meet standards and mandates like NIST AI RMF 600-1, EU AI Act, HIPAA, GDPR, and more through continuous monitoring and compliance reporting.
Instantly assess your data risk
Our Data Risk Assessment is fast and easy. Get instant visibility of your data, risk, and exposure, and receive expert guidance on security issues.
Solution Details
Secure a diverse AI and data landscape
Discover your entire AI landscape
Easily manage your growing AI ecosystem with simplified oversight as well as robust visibility and control over AI deployments, resources, and components.
KEY FEATURES
Understand AI models, agents, and services used across your organization, where they are deployed, and the resources they rely on.
Uncover AI deployments that may not be formally sanctioned or known to your IT or security teams.
Get additional information and context on AI technologies, such as publisher, country of origin, licensing terms, and risk factors.
Ensure coverage of major cloud providers' AI services, such as Microsoft Azure Foundry AI, Amazon Bedrock, and Google Vertex AI.
Assess your AI risk and posture
Analyze and prioritize risk with AI. Identify misconfigurations, access risk, and vulnerabilities in AI agents, deployments, and retrieval-augmented generation (RAG) frameworks.
KEY FEATURES
Map the entire AI supply chain to expose misconfigurations, excessive permissions, and vulnerabilities for AI services and related assets.
Filter out the noise and prioritize incidents based on risk likelihood and impact through in-depth analysis.
Minimize risk by using AI/ML to correlate threats that determine hidden attack paths, leveraging the world’s largest security cloud.
Get a granular, risk-based, user-centric view of all AI access paths to mission-critical data assets and their configurations.
Ensure responsible use of AI
Remediate AI/LLM risks and streamline risk management with context-based guided remediation, enabling security teams to easily fix issues and violations at the source.
KEY FEATURES
Enforce security best practices and guardrails to secure AI deployments.
Remediate data exposure, misconfigurations, and security risk by leveraging step-by-step guided remediation with complete context.
Configure real-time alerts to keep pace with rapid change to the AI environment, reducing investigation and response times.
Minimize the attack surface by remediating overprivileged access and risky AI access paths to sensitive data.
Integrate with DSPM/DLP solutions or ITSM tools to improve operational efficiency.
Secure AI models and training data
Monitor and protect data usage by AI model to safeguard sensitive or regulated data used in training datasets against inadvertent leaks or adversarial attacks.
KEY FEATURES
Leverage auto-data discovery and AI-powered classification to build precise training datasets and prevent oversharing while reducing the attack surface and improving your risk posture.
Monitor data flows, access to sensitive data, alert on critical and regulated data used in AI training, and reduce the risk of data misuse or exposure.
Monitor data compliance and security risks with prebuilt policies to automatically flag critical issues.
Review prompt and output logs to detect model misuse and mitigate potential data exposure risks.
Discover, analyze, and remediate overexposed data used in AI training models. Revoke access from overprivileged users, whether internal or external, to reduce insider risk.
Align with AI governance frameworks
Ensure AI and data usage is protected without geographical or regulatory differences with robust, real-time data compliance and governance, no matter where the data resides.
Key Features
Get comprehensive visibility into AI and data compliance posture with a dynamic view of compliance status, configuration drifts, and policy violations.
Automatically benchmark against regulations like GDPR or HIPAA as well as AI-specific standards like NIST AI RMF 600-1.
Drill down on compliance violations to prioritize remediation efforts, minimizing the risk of data breaches and associated legal liabilities.
Take advantage of comprehensive compliance data, analytics, and automated reporting for technical compliance audits.
Experimente el poder de Zero Trust Exchange de Zscaler
Una plataforma integral para proteger, simplificar y transformar su empresa.
01 Operaciones de seguridad
Reduzca el riesgo y detecte y contenga las infracciones, con información procesable de una plataforma unificada
02 Protección contra la amenaza cibernética
Proteja a los usuarios, los dispositivos y las cargas de trabajo para evitar verse comprometido y el movimiento lateral de amenazas
03 Seguridad de los datos
Aproveche la inspección completa de TLS/SSL a escala para una seguridad completa de los datos en toda la plataforma SSE
04 Zero Trust para sucursales y la nube
Conecte usuarios, dispositivos y cargas de trabajo en la sucursal, la nube y el centro de datos, y entre estos elementos.