Netskope AI Security Forum | Netskope One Community Hub

Kong AI Gateway with Netskope AI GuardrailsIntegration Guide: AI Guardrails on DemandKong AI Gateway routes and manages traffic to large language models, but provides limited native content security. This guide shows how to add Netskope AI Guardrails on Demand as a real-time inspection layer, so that every prompt flowing through Kong is checked for policy violations — prompt injection, jailbreaks, unsafe content, and more — and blocked before it reaches the model.A reference implementation of the plugin described here is published and ready to use: github.com/sandiegojenkins/kong-plugin-netskope-ai-guardrail (Apache-2.0). It has been verified end-to-end, including with a real LLM provider behind the gateway — see Step 6.Why add Netskope to KongInspect prompts in real time. Each request is evaluated against your Netskope AI Guardrail profiles before it reaches the LLM. Block policy violations at the gateway. Unsafe prompts are stopped centrally — no application code changes required. Re

Claude Desktop's third-party inference mode (generally available as of July 9, 2026) lets you point the app at your own cloud inference provider instead of Anthropic's first-party API - such as Amazon Bedrock, Google Cloud's Agent Platform, Microsoft Foundry, or any compatible gateway you operate. That's a big deal for regulated or security-conscious organizations: you get the full Claude Desktop experience (Chat, Cowork, and Code tabs, file creation, multi-step research) while inference and billing run through infrastructure you already control.What it doesn't give you out of the box is visibility and control over what's actually going over the wire - which prompts contain sensitive data, whether someone's about to leak a secret into a conversation, or whether a jailbreak attempt just landed. That's exactly the gap Netskope AI Gateway is built to close - sitting in front of your chosen inference provider as the policy and visibility layer that direct inference access doesn't give you.

As teams scale AI agents beyond basic chatbots, machine-to-machine traffic becomes much harder to govern.This recording covers how AI Gateway handles that agentic traffic, including a walkthrough of real-time token inspection, DLP guardrails, and model routing, plus a live demo of policy setup inside Netskope.If you're evaluating AI Gateway for your own environment, the session is a solid starting point before requesting a technical review or Proof of Value sandbox.▶ Watch here: https://netskopeacademy.skilljar.com/csg-customer-webinar-ai-gatewayOriginally shared in Community News & Announcements —  

This session tackles a gap most security teams are only now running into: conventional testing tools weren't designed for LLMs, so a chatbot can pass every check and still leak data on an edge case.The recording covers why standard scans and manual pen tests fall short for AI systems, how continuous adversarial testing replaces slower manual audits, how teams are folding this testing into their AI development workflows, and how to use a Proof of Value sandbox to safely stress-test proprietary models.▶ Watch here: https://netskopeacademy.skilljar.com/csg-customer-webinar-netskope-ai-red-teaming Originally shared in Community News & Announcements —  

Watch this recording to see how Netskope helps keep AI tools safe for everyday use. It checks conversations with AI as they happen, catching people trying to trick the AI into saying something it shouldn't, and blocking harmful or private information from slipping through.The session starts by explaining the risks in simple terms, then shows how the protection actually works. Good watch whether you're new to this or already using it.🎥 Watch here: https://netskopeacademy.skilljar.com/csg-customer-webinar-ai-guardrails💬 Questions after watching? Drop them below and the team will get back to you. Originally shared in Community News & Announcements —