Russia's MinTsifry to Begin Issuing State Code Signing Certificates in 2027

Google to Back Unified robots.txt Standard for Blocking AI Training Data Use Starting in 2027

Google has announced plans to support a common mechanism in robots.txt that lets website owners set a single preference against the use of their content for training generative AI models. The feature will rely on work from the AIPREF working group at IETF and is scheduled for rollout in 2027. Under the proposal, a general policy marker will be introduced so that sites can express preferences regarding AI training without issuing separate directives to each provider. Google intends to treat a general prohibition the same way it currently handles the Google-Extended directive when no specific instruction exists. Existing per-company settings will remain available, allowing publishers to combine a broad rule with targeted exceptions for individual AI providers. The company noted that robots.txt only communicates usage preferences and does not technically block crawler access, so effectiveness will depend on which organizations adopt and honor the new standard.

Rostelecom Explores Underground Data Centers in Partnership with Nornickel for Enhanced Physical Protection

Rostelecom is developing plans for underground data centers as a third layer of protection against increasingly serious external threats. The first layer involves backup sites with data copies, while the second relies on distributing infrastructure across geographically separated locations. The operator is in discussions with Nornickel, whose own power generation and spare capacity could support the energy needs of such facilities. According to iKS-Consulting estimates, an underground data center could cost 30-40% more than a comparable surface facility due to requirements for waterproofing, ventilation, gas monitoring, specialized fire suppression, evacuation systems, and underground equipment transport. No specific timelines, locations, or technical parameters for the project have been disclosed. The initiative reflects a broader focus on physical security measures for critical IT infrastructure beyond traditional digital safeguards.

Who Pays When AI Agents Err: Insurance Gaps for AI Risks Emerge in Russia and the West

Russian legislation places responsibility for AI harm on humans or organizations under the Civil Code, with no specific AI liability norms yet in force. Experimental legal regimes since 2025 require mandatory insurance for AI-driven systems like drones and telemedicine, while the 2026 Federal Law No. 243-FZ grants sovereign model developers rights to insure risks but leaves AI agents outside its scope. A March 2026 draft bill outlined detailed liability chains and exemptions for hidden defects, yet the final law retained only a generic reference to existing legislation. Western markets feature voluntary products from Armilla, Munich Re aiSure and AIUC-1 that cover hallucinations and agent actions, while EU AI Act and U.S. state laws like TRAIGA and AB 316 focus on oversight rather than compulsory insurance. Real incidents, including Mythos 5's unintended real-world actions during AISI testing, highlight the need for black-box logging and parametric coverage when no party is clearly at fault.