5 ways DNS filtering strengthens your AI security strategy
Secure the use of AI and mitigate emerging threats with the power of the connectivity cloud
As organizations race to integrate artificial intelligence into their workflows, security teams are facing a new frontier of risk. From "Shadow AI" adoption to the weaponization of generative AI by threat actors, traditional security perimeters are no longer enough.
To move fast and stay secure, leaders need a lightweight, scalable way to gain visibility and control over how their data and users interact with AI.
Explore this ebook to discover insights on:
- Eliminating shadow AI blind spots: How to use DNS query visibility to identify unsanctioned AI tools and evaluate their trustworthiness using application confidence scores.
- Neutralizing AI-enhanced threats: Why DNS-level protection is your first line of defense against AI-driven phishing, C2 callbacks, and algorithmically generated domains.
- Protecting the AI development lifecycle: Strategies to prevent model weight exfiltration, data poisoning, and indirect prompt injections.
- The path to deeper security: How to transition from DNS filtering to granular HTTP inspection and data loss prevention (DLP) to create total guardrails for AI prompts.
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