Why do the secrets scattered across my project end up inside my coding agent's prompt?
機会
AI coding agents read entire project directories before generating or editing code. That context routinely includes .env files, config YAML, shell history, and CI secrets, all of which get packed into the prompt sent to an external LLM API. On the code-generation side, agents write code that hardcodes the credentials they saw in context. GitGuardian's 2026 State of Secrets Sprawl report found 28.65 million new hardcoded secrets pushed to public GitHub in 2025, up 34% year over year, with AI-assisted commits leaking secrets at roughly twice the rate of human-written commits, and 24,008 unique secrets found sitting in public MCP configuration files. No coding agent today ships a secrets-aware context filter that strips or vaults sensitive values before they enter the prompt.
重要な理由
A secrets-aware context layer built into the agent toolchain is the only fix that scales as AI-generated code becomes the default.
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。