The MCP cacheScope specification, intended for reusable results, has a security vulnerability where private cached data can be exposed to unintended users. This occurs when a shared client cache lacks sufficient identity information to distinguish between different authorization contexts. A server can mark results as public or private, but a shared cache might incorrectly serve a private result intended for one user to another if the cache key is not properly partitioned. The proposed solution involves creating a stable cache partition for each authorization context, derived from identity dimensions like tenant or subject, to ensure private data remains isolated. AI
IMPACT Ensures secure caching for AI tools and services that rely on shared client caches.
RANK_REASON Technical deep-dive into a specification's security flaw. [lever_c_demoted from research: ic=1 ai=0.4]
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