AI Security (Automation)
The increasing use of artificial intelligence in organizations brings with it new security risks such as model access, handling of sensitive data, unauthorized AI applications, and interaction with untrusted content. AI Security solutions help identify and control risky behaviors by making access to AI applications and data movements visible.
With capabilities like AI Guardrails, AI Access Management, and AI Red Teaming, organizations can use both their own proprietary and third-party AI applications more securely. This minimizes data leaks, unauthorized access, misuse, and AI-related security risks.
Zscaler - AI Access Security
Zscaler AI Asset Management enables organizations to gain visibility and control over AI applications, services, and related assets used within their structure. Knowing which AI tools are being used is the first step in risk management. By providing this visibility, Zscaler reduces the use of shadow AI and offers security teams centralized management capabilities.
Zscaler - AI Red Teaming
Zscaler AI Red Teaming helps proactively test for vulnerabilities and exploitation scenarios in AI systems. This allows organizations to identify potential risks posed by AI-based applications at an earlier stage. It's a valuable capability for organizations that want to design their AI processes securely from the outset, rather than adding security later.
Zscaler - AI Guardrails
By monitoring prompts and responses in AI applications in real time, it provides protection against risks such as prompt injection, jailbreaking, malicious content, and sensitive data leaks. It supports the implementation of secure and compliant AI usage policies.
Xage Unified Zero Trust For AI
Xage Unified Zero Trust for AI offers a Zero Trust security model for AI systems and data flows. Access to AI applications, data usage, and model interactions are controlled based on identity and policy. This prevents the leakage of sensitive data through AI systems, ensuring secure and controlled AI usage.
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