PromptShield Gateway: Open-source LLM Security for Apps

PromptShield Gateway: Open-Source LLM Security for Apps

PromptShield Gateway is an open-source solution designed to enhance the security and observability of your Large Language Model (LLM) integrations. It acts as a gateway, intercepting requests to your LLM endpoints and applying crucial security and monitoring features without requiring modifications to your application's codebase. This allows developers to implement robust LLM security and gain valuable insights into their usage patterns.

What it Does

PromptShield Gateway provides a layer of protection and monitoring between your applications and LLM APIs. It intercepts API calls, allowing you to enforce security policies and collect operational data. The primary functions include rate limiting to prevent abuse and manage costs, comprehensive auditing of requests and responses for compliance and debugging, and detailed token tracking to monitor LLM consumption. Additionally, it exposes Prometheus metrics, enabling integration with existing monitoring and alerting systems.

Key Features

• Rate Limiting: Configure limits on the number of requests per user, API key, or IP address to prevent denial-of-service attacks and manage API costs.
• Audit Logging: Record all incoming requests and outgoing responses for security analysis, compliance, and troubleshooting.
• Token Tracking: Monitor the number of tokens consumed by each request, providing visibility into LLM usage and associated expenses.
• Prometheus Metrics: Expose key operational metrics in Prometheus format, facilitating integration with popular monitoring tools like Grafana.
• No App Code Changes: Designed to be deployed as a separate service, it requires no modifications to your existing application code.
• Open-Source: Freely available and customizable, offering transparency and flexibility for developers.

Who it's For

PromptShield Gateway is an essential tool for AI builders and developers integrating LLMs into their applications. It is particularly beneficial for:

• Teams looking to secure their LLM deployments against abuse and unauthorized access.
• Developers needing to monitor and control LLM API costs through effective rate limiting and token tracking.
• Organizations requiring audit trails for compliance and security incident investigation.
• DevOps engineers aiming to integrate LLM usage metrics into their existing observability stacks.