AI Gateways Inspect Prompts, But Who Secures the Connection to Your Infrastructure?
Blog post from Twingate
AI gateways are designed to manage the interaction between applications and large language model (LLM) providers by offering features such as prompt filtering, rate limiting, content filtering, key rotation, and centralized API key management. However, these gateways do not address the network access challenges of connecting AI agents to internal resources like databases or APIs, which is where Zero Trust Network Access (ZTNA) becomes relevant. ZTNA focuses on securing the resource path by ensuring that agent processes have identity-based, least-privilege access to specific resources without exposing them to the internet, a necessity given the autonomous nature and potential privilege requirements of AI agents. The combination of AI gateways for prompt security and ZTNA for network security creates a comprehensive AI security stack that manages requests from user interactions to database queries. This layered approach addresses the distinct problems of securing both the communication with LLMs and the connection to internal infrastructure, drawing on practices traditionally used for managing access for remote employees, contractors, and inter-service communications.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Zero Trust | 11 | 201 | 78 | 35 | -21% |
| MCP | 6 | 7,755 | 862 | 214 | 0% |
| Platform Engineering | 5 | 1,615 | 247 | 89 | +4% |
| AI Agents | 2 | 6,200 | 1,430 | 272 | +10% |
| LLM | 2 | 6,292 | 1,205 | 252 | -36% |
| Observability | 2 | 4,261 | 791 | 201 | +16% |
| Edge Computing | 1 | 50 | 22 | 16 | +6% |
| Kubernetes | 1 | 2,083 | 321 | 111 | +3% |
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