Cloud.ru

Cloud.ru Unveils Evolution Protection Platform for Detecting Cloud Misconfigurations

Cloud.ru has introduced its Evolution Protection Platform, a Cloud-Native Application Protection Platform (CNAPP) designed to identify risky configurations in cloud environments. The solution targets issues such as public storage buckets containing private data, excessive permissions on service accounts, and virtual machines with unnecessary internet exposure. A dedicated CSPM module continuously monitors configuration changes and runs automated checks without requiring agents on virtual machines. Organizations can apply predefined rule sets or build custom policies, with results accessible through the cloud platform interface and alerts delivered via email, APIs, or webhooks. The current release also incorporates security checks for AI agents built on Cloud.ru Evolution products. Additional features including DSPM for sensitive data discovery, vulnerability scanning for VMs and containers, and an AI risk prioritization assistant remain in development.

Sergey Volkov of Cloud.ru Named Top CISO in Russian IT Sector Ranking

Sergey Volkov, Director of the Cyber Protection Center at Cloud.ru, has secured first place in the information security category of the annual Top-1000 Russian Managers ranking. The ranking, published by the Association of Managers in the Kommersant newspaper since 2001, is compiled through peer evaluations by top executives followed by review from expert commissions. Volkov oversees information security strategy and operations for Cloud.ru, and his top position reflects professional recognition of his leadership results. The Association also analyzed broader achievements among laureates and identified key trends in Russian management. Artificial intelligence adoption for business process optimization appeared in 80 percent of reviewed accomplishments. Client orientation through user experience analysis and personalized solutions ranked second, while operational efficiency via cost reduction, automation, and digitalization took third place.

Guardrails Filter Tackles Complex LLM Streaming and Tool Call Challenges to Protect Sensitive Data

Developers at Cloud.ru built Guardrails Filter to mask personal data such as phone numbers, emails, passport details and names before they reach large language models. The system replaces detected values with consistent placeholders like <PHONE_1> and maintains a mapping table so original data can be restored after the model responds. Simple replacement proved insufficient because identical values must receive the same placeholder across an entire conversation history, and the model receives the full message array on every request. Streaming responses using SSE create additional difficulties since placeholders can be split across multiple chunks, requiring buffering of 10-15 characters and state tracking for reasoning, content and tool_calls. The team also had to handle JSON-inside-JSON arguments for tool calls, different field names across providers, and edge cases such as escaped newlines matching email patterns. Separate implementations were written for OpenAI Chat Completions and Anthropic Messages APIs, resulting in roughly 1,500 lines of streaming code and more than 4,000 lines of tests to ensure agent pipelines remain intact.

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.