# Industry: Google DeepMind - AI Control Roadmap for Agents

---
type: industry
company: Google DeepMind
team:
title: Securing the future of AI agents
url: https://deepmind.google/blog/securing-the-future-of-ai-agents/
source_name: Google DeepMind
source_type: technical-report
source_quality: official
published_at:
collected_at: 2026-07-08
status: analyzed
topics:
  - agent-safety
  - agent-security
  - governance
implementation_signals:
  - defense-in-depth
  - sandboxing
  - permission-control
  - prompt-injection-resistance
product_area:
  - internal-agents
  - enterprise-agent
models:
  -
tools:
  -
benchmarks:
  -
related_papers:
  - 2025-vijayvargiya-openagentsafety
  - 2026-agent-safety-benchmark-taxonomy
related_jobs:
  - 2026-07-08-tencent-cloud-ai-agent-test-engineer
related_experiments:
  -
related_projects:
  -
evidence_level: high
relevance: high
---

## One-line Takeaway

Agent 安全需要把内部 Agent 当作潜在 insider threat 来设计权限、沙箱和逐步授权。

## What They Built or Claimed

Google DeepMind 介绍 AI Control Roadmap，用 defense-in-depth 保护 Google 内部系统，应对能力增强但不完美对齐的 Agent。

## Technical Signals

- architecture: alignment + system-level AI control + cybersecurity-style threat modeling。
- tool use:
- memory:
- evaluation: 通过行为验证逐步授予权限。
- safety: sandboxing、endpoint security、prompt injection resistance、权限分层。
- deployment: 内部 Agent 系统治理。
- data:

## Evidence Quality

官方技术/治理材料，适合作为 Agent 安全架构参考。

## Gaps for Us

- 需要把 Agent 权限分层写入实践 playbook。
