How we use Lakera Guard to secure our LLMs

This post details the integration of Lakera Guard to secure LLMs used in Dropbox's AI-powered features. It describes the evaluation criteria for LLM security solutions, focusing on in-house deployability, low latency, support for long context lengths, and confidence scores. The testing methodology involved using Garak for vulnerability scanning and measuring net security improvement against LLM mitigations. The integration architecture uses LangChain and Lakera Guard as an internal Docker service, with RPC calls to Lakera's prompt injection and content moderation APIs. Key technical achievements include a 7x latency improvement for prompts over 8,000 characters and collaboration with Lakera on detecting novel LLM vulnerabilities. The post also outlines plans for broader integration across Dropbox products.