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DCC · DATA COMPLIANCE CHINA China data law, for overseas counsel.
§ TAG · AI-AGENTS

Filed under ai-agents

Every brief tagged "ai-agents".

  • § 01 · AI-AGENTS

    TC260's Practice Guide on AI-Agent Deployment: A Five-Stage Lifecycle Checklist, Read Against PIPL, DSL, and CSL Obligations

    On July 1, 2026 the National Cybersecurity Standardization Technical Committee (TC260) issued the Cybersecurity Standards Practice Guide — Security Guidelines for the Deployment and Use of AI Agents (网络安全标准实践指南——智能体部署使用安全指引), covering the full lifecycle of high-permission, LLM-based personal-assistant agents across five stages: assessment, preparation, deployment, use, and decommissioning, plus a star-rated security checklist (Appendix A) and an organizational management framework including shadow-agent discovery (Appendix B). This DCC brief adapts the HexCode reading published on 数据何规 — itself generated, the account notes, by its own AI agent — which maps each stage onto hard-law anchors: PIPIA duties under PIPL Article 55 and DSL Article 27 risk monitoring at assessment; the GenAI Measures' filed-model requirement and the ban on unverified API relays at preparation; least privilege, directory isolation, CSL Article 21 log retention, and high-risk-operation confirmation lists at deployment; minimum-necessary provision of personal information and long-term-memory management in use; and credential revocation and data disposal at decommissioning. Practice guides are soft law — but in Chinese enforcement practice they calibrate what 'necessary measures' means, and this one is the first lifecycle baseline for the agent era.

    ai-agents · ai-governance · tc260
  • § 02 · AI-AGENTS

    Mapping the AI Agent Risk Surface — A Ten-Category Taxonomy Under China's New 智能体新规

    China's Cyberspace Administration jointly issued the Implementation Opinions on Standardized Application and Innovation Development of AI Agents (the '智能体新规' or 'Agent Rules') on May 8, 2026 — the first dedicated regulatory document on AI agents anywhere in the world. This DCC brief works through the ten-category risk taxonomy that practitioners are now using to map the agent attack surface: goal hijacking, tool misuse, identity/permission abuse, supply-chain compromise, unintended code execution, memory and context poisoning, inter-agent communication insecurity, cascade failures, human-machine trust exploitation, and rogue agents. With the agent risk mapped, the brief works the legal-liability vector: how each risk maps to administrative, civil, and criminal exposure under existing PIPL, CSL, Anti-Unfair Competition, and trade-secret regimes. Closes with the Guangzhou Internet Court's recent dual-authorization ruling against an open-source agent that bypassed a chat platform's risk controls — the first Chinese case to articulate the dual-authorization principle for AI agents accessing third-party platforms.

    ai-agents · ai-governance · genai
  • § 03 · AI-AGENTS

    Operationalizing AI Agent Governance — A Ten-Step Internal Control Framework

    Part 2 of DCC's brief on the Chinese Agent Rules (《智能体规范应用与创新发展实施意见》, May 2026). After mapping the ten-category risk taxonomy in Part 1, this brief works through the ten-step internal governance framework practitioners are now building to operationalize agent compliance: cross-functional governance organization + agent asset inventory; use-case admission and classification (L1 read-only / L2 limited-write / L3 sensitive-data / L4 high-impact); security assessment and AI red-team testing; identity authorization and permission control (with the under-discussed 'permission inheritance' trap); data protection; tool and protocol security; human-in-the-loop design; supply-chain security; continuous monitoring; and AI-specific incident response. Closes with five operational priorities for teams that need to start now without waiting for the 'big-and-comprehensive' regime build.

    ai-agents · ai-governance · genai
  • § 04 · AI-GOVERNANCE

    AI Agents and the Limits of Consent — When 'Authorisation' Stops Being One Click

    Li Wenlong (科技利维坦) takes the Doubao phone assistant — an AI that 'reads your screen' and acts across apps — and asks whether the consent/authorisation mechanism that traditional data law leans on can survive the agent era. His four challenges: the app-bounded 'private' environment dissolves as data and permissions move across apps (with Nissenbaum's Contextual Integrity as the only real conceptual anchor, and far from operational); agents that *act* (not just retrieve) push informed consent past the point of failure already reached by personalised ads; purpose limitation collapses because an agent chooses its own path, means and decisions from a low-information instruction, edging into automated decision-making; and ultra vires agency shifts liability from user to platform, with China's 'hallucination case' and the Air Canada case as the only thin precedents. For overseas counsel building or advising on agentic AI in China: a map of why 'authorisation' is becoming a problem of agency, system control, liability allocation and autonomy — not a checkbox — and why transparency is now a prerequisite, not a feature.

    ai-governance · ai-agents · pipl
  • § 05 · AI-GOVERNANCE

    Reverse Interoperability: Li Wenlong's Frame for the Doubao On-Device Agent Fight

    ByteDance's Doubao phone assistant — preinstalled at the device layer to operate other apps on a user's behalf — was met with pop-up blocks from WeChat and others citing security and risk-control. Li Wenlong (科技利维坦) argues the dispute is, at bottom, a question of how China's competition-law toolkit (反不正当竞争法 / 反垄断法) absorbs the idea of interoperability — and specifically what he calls 'reverse interoperability (反向互操作性)'. The classic interoperability problem is a platform refusing to open up, with antitrust used as a market remedy to force access. Doubao inverts it: interoperability is fully achieved at the device level, and the legal question becomes whether the law should restrict 'over-interoperation.' Li maps interoperability's journey from the Microsoft case through GDPR data portability and the DMA to the agent era, distinguishes the Doubao fight from the decade-old 3Q War, and predicts on-device-agent governance will look less like classic antitrust and more like the ex-ante, conditional-use compliance model emerging for AI training data. For overseas counsel: a structural read on the platform-access war that on-device AI agents are about to intensify.

    ai-governance · ai-agents · interoperability
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