Cloud.ru Open-Sources Guardrails Filter Reverse Proxy to Prevent Sensitive Data Leaks When Using Any LLM

Cloud.ru has released the source code of Guardrails Filter as an open-source project. The tool functions as a transparent reverse proxy positioned between clients and LLM providers. It automatically strips sensitive data such as names, addresses, phone numbers, INN identifiers, passport details, bank account information, and API keys from user prompts before they reach any language model. The original data is then restored in the model's responses. The solution was initially developed for Cloud.ru's Evolution Foundation Models platform to ensure customer data never leaves the company's infrastructure. It particularly addresses strict requirements from banks, insurers, and e-commerce companies that demand data remain inside their own perimeters rather than entering any public cloud environment.

HabrTranslated from Russian

Read at source

Cloud.ru has made the source code of Guardrails Filter publicly available. The tool serves as a transparent reverse proxy placed between the client and any LLM provider. It removes sensitive information from requests sent to language models and restores the original data in the responses returned to users.

Users frequently paste chat logs, call summaries, medical test results, medical histories, and contract texts into popular LLMs without considering the risks. These inputs often contain personal names, addresses, phone numbers, INN numbers, passport data, bank account details, and API keys. Guardrails Filter was created to eliminate reliance on manual data sanitization by users.

The project originated as an internal component of Cloud.ru’s Evolution Foundation Models platform. It was designed to guarantee that data processed through external LLMs would not be stored abroad or used for subsequent attacks. Banks, insurance companies, and e-commerce businesses required an even stricter guarantee that data would never leave their own corporate network, not even when routed through Cloud.ru’s public cloud infrastructure.

Developers therefore enhanced the internal solution and decided to publish it as open source. The release allows any organization to deploy Guardrails Filter in its own environment and maintain full control over data flows to language models from any provider.

Meridian digestThe week's most consequential security stories, distilled into one briefing.See the digest

More in AI Security

Logical Argument Claims Full Alignment of Superintelligent AGI Is Fundamentally Impossible
Claude Account Bans Linked to IP Reputation, Device Environment and Payment Channels, But No Confirmed Formula
Local LLMs in AppSec: What Open Tools and Models Can Handle in Application Security