Why can one specialized agent in my pipeline read every other agent's private data?
機会
Multi-agent frameworks like LangGraph, CrewAI, and AutoGPT maintain a single shared state object that all agents in a pipeline can read and write. There is no field-level access control: a billing agent and a customer-service agent share the same memory store with nothing separating them. AgentLeak, a 2026 benchmark covering 4,979 execution traces across healthcare, finance, and legal scenarios, found that inter-agent communication channels leak sensitive data in 68.8% of runs, compared with 27.2% for final outputs alone. Output-only audits therefore miss 41.7% of privacy violations that have already occurred inside the pipeline. No major framework ships an information-flow control layer between agents.
重要な理由
A governed shared-memory layer with field-level access control is the missing primitive that makes multi-agent pipelines safe to deploy on real user data.
機会をどう評価するか
Opportunity Scoreは測定値ではなく、私自身の見解です。どれほど痛みを伴うか、どれほど頻繁に影響を与えるか、そして今日時点で解決策がいかに少ないか。スコアが高いほど、構築する価値が高いと私は考えています。
それが現れたときにどれほどの痛みをもたらすか。
実際にどれほど頻繁に人々がそれに直面するか。
今日時点で、それに対する優れたツールがいかに少ないか。